Accurate and efficient estimation of Channel State Information (CSI) is critical for next-generation wireless systems operating under non-stationary conditions, where user mobility, Doppler spread, and multipath dynamics rapidly alter channel statistics. Conventional pilot aided estimators incur substantial overhead, while deep learning approaches degrade under dynamic pilot patterns and time varying fading. This paper presents a pilot-aided Flash-Attention Transformer framework that unifies model-driven pilot acquisition with data driven CSI reconstruction through patch-wise self-attention and a physics aware composite loss function enforcing phase alignment, correlation consistency, and time frequency smoothness. Under a standardized 3GPP NR configuration, the proposed framework outperforms LMMSE and LSTM baselines by approximately 13 dB in phase invariant normalized mean-square error (NMSE) with markedly lower bit-error rate (BER), while reducing pilot overhead by 16 times. These results demonstrate that attention based architectures enable reliable CSI recovery and enhanced spectral efficiency without compromising link quality, addressing a fundamental bottleneck in adaptive, low-overhead channel estimation for non-stationary 5G and beyond-5G networks.

6G envisions massive cell-free networks with spatially nested multiple access (MAC) and broadcast (BC) channels without centralized coordination. This renders optimal resource allocation—across power, subcarriers, and decoding orders crucial for interference channels (ICs), where neither transmitters nor receivers can cooperate. Current orthogonal multiple access (OMA) methods, as well as non-orthogonal (NOMA) and rate-splitting (RSMA) schemes, rely on fixed heuristics for interference management, leading to suboptimal rates, power inefficiency, and scalability issues. This paper proposes a novel minPIC framework for optimal power, subcarrier, and decoding order allocation in general multi-user ICs. Unlike existing methods, minPIC eliminates heuristic SIC order assumptions. Despite the convexity of the IC capacity region, fixing an SIC order induces non-convexity in resource allocation, traditionally requiring heuristic approximations. We instead introduce a dual-variable-guided sorting criterion to identify globally optimal SIC orders, followed by convex optimization with auxiliary log-det constraints, efficiently solved via binary search. We also demonstrate that minPIC could potentially meet the stringent high-rate, low-power targets of immersive XR and other 6G applications. To the best of our knowledge, minPIC is the first algorithmic realisation of the Pareto boundary of the SIC-achievable rate region for Gaussian ICs, opening the door to scalable interference management in cell-free networks.

Next-generation IoT and cyber-physical systems must deliver fresh updates while keeping queues stable and radios energy-frugal. Existing backlog-centric schedulers minimize delay but ignore data freshness, whereas age-centric policies risk throughput collapse. This work proposes AoI-Queue-Proportional Scheduling (AOI-QPS), an energy-aware extension of classical QPS that allocates service proportional to a weighted sum of queue lengths and Age-of-Information. A Lyapunov-drift analysis proves AOI-QPS is throughput-optimal and bounds average AoI by $\mathcal{O}(1/\alpha )$ while guaranteeing finite delay. Incorporating a IEEE802.15.4-derived energy model further yields an empirical AoI-per-Joule guarantee for queue-stable policies. Extensive simulations under uniform, skewed, and bursty traffic show AOI-QPS cuts network-wide AoI by up to 60% versus QPS, matches Max-AoI’s freshness within 5%, and eliminates the 30% idle-slot energy waste of static schedulers—all without sacrificing queue stability or energy efficiency. AOI-QPS thus addresses the AoI–queue–energy trade-off, offering a practical, analytically grounded knob for balancing freshness, latency, and sustainability in next-generation wireless networks.

This paper proposes a novel joint channel-estimation and source-detection algorithm using successive interference cancellation (SIC)-aided generative score-based diffusion models. Prior work in this area focuses on massive MIMO scenarios, which are typically characterized by full-rank channels, and fail in low-rank channel scenarios. The proposed algorithm outperforms existing methods in joint source-channel estimation, especially in low-rank scenarios where the number of users exceeds the number of antennas at the access point (AP). The proposed score-based iterative diffusion process estimates the gradient of the prior distribution on partial channels, and recursively updates the estimated channel parts as well as the source. Extensive simulation results show that the proposed method outperforms the baseline methods in terms of normalized mean squared error (NMSE) and symbol error rate (SER) in both full-rank and low-rank channel scenarios, while having a more dominant effect in the latter, at various signal-to-noise ratios (SNR).

Currently used resource allocation methods for uplink multicarrier non-orthogonal multiple access (MC-NOMA) systems have multiple shortcomings. Current approaches either allocate the same power across all subcarriers to a user, or use heuristic-based near-far, strong channel-weak channel user grouping to assign the decoding order for successive interference cancellation (SIC). This paper proposes a novel optimal power-subcarrier allocation for uplink MC-NOMA. This new allocation achieves the optimal power-subcarrier allocation as well as the optimal SIC decoding order. Furthermore, the proposed method includes a time-sharing algorithm that dynamically alters the decoding orders of the participating users to achieve the required data rates, even in cases where any single decoding order fails to do so. Extensive experimental evaluations show that the new method achieves higher sum data rates and lower power consumption compared to current NOMA methods.

Upcoming Augmented Reality (AR) and Virtual Reality (VR) systems require high data rates ($\geq \mathbf{500 Mbps}$) and low power consumption for seamless experience. With an increasing number of subscribing users, the total number of antennas across all transmitting users far exceeds the number of antennas at the access point (AP). This results in a low rank wireless channel, presenting a bottleneck for uplink communication systems. The current uplink systems that use orthogonal multiple access (OMA) and the proposed non-orthogonal multiple access (NOMA), fail to achieve the required data rates / power consumption under predominantly low rank channel scenarios. This paper introduces an optimal power sub carrier allocation algorithm for multicarrier NOMA, named minPMAC, and an associated timesharing algorithm that adaptively changes successive interference cancellation decoding orders to maximize sum data rates in these low rank channels. This Lagrangian based optimization technique, although globally optimum, is prohibitive in terms of runtime, proving inefficient for real-time scenarios. Hence, we propose a novel near-optimal deep reinforcement learningbased energy sum optimization (DRL-minPMAC) which achieves real-time efficiency. Extensive experimental evaluations show that minPMAC achieves$\mathbf{2 8 \%}$and 39% higher data rates than NOMA and OMA baselines. Furthermore, the proposed DRL-minPMAC runs 5 times faster than minPMAC and achieves 83% of the global optimum data rates in real time.*

Channel estimation poses significant challenges in millimeter-wave massive multiple-input multiple-output systems, especially when the base station has fewer radio-frequency chains than antennas. To address this challenge, one promising solution exploits the beamspace channel sparsity to reconstruct full-dimensional channels from incomplete measurements. This paper presents a model-based deep learning method to reconstruct sparse, as well as approximately sparse, vectors fast and accurately. To implement this method, we propose a trimmed-ridge regression that transforms the sparse-reconstruction problem into a least-squares problem regularized by a nonconvex penalty term, and then derive an iterative solution. We then unfold the iterations into a deep network that can be implemented in online applications to realize real-time computations. To this end, an unfolded trimmed-ridge regression model is constructed using a structural configuration to reduce computational complexity and a model ensemble strategy to improve accuracy. Compared with other state-of-the-art deep learning models, the proposed learning scheme achieves better accuracy and supports higher downlink sum rates.

This article investigates the joint codebook selection and modulation-coding-scheme (MCS) adaptation issue for the enhanced mobile broadband (eMBB) service in millimeter-wave (mmWave) cellular systems. The proposed scheme guarantees efficient mmWave eMBB service through an intelligent joint codebook selection and MCS adaptation scheme that exploits deep reinforcement learning (DRL), referred to as DeepCM. DeepCM’s objective maximizes the transmission data rate while satisfying a target block error rate (BLER) constraint. A first step formulates this joint problem into a two-time-scale system that performs MCS adaptation on a small-time scale, whereas a second step optimizes the codebook on a large-time scale. DeepCM introduces a new DRL algorithm, termed dual-deep Q-network (DQN), by incorporating the operations on two time scales into the original DQN. Dual-DQN essentially enables the operations on different time scales to benefit from each other, through closed-loop decision guidance and reward evaluation. Thereafter, to fulfill the preset BLER constraint, DeepCM uses a constrained$\epsilon $-greedy strategy for decision-making and further modifies the conventional DRL training mechanism. Basically, DeepCM continuously adjusts the agent’s feasible-action space toward the system objective. With the constrained dual-DQN, DeepCM can attain its goal even without any prior network information. Simulation results show that DeepCM, compared with Thompson Sampling-DRL, DRL-OLLA, and TS2 schemes, guarantees the target BLER requirement while yielding a much higher data rate. Various simulations demonstrate the powerful robustness of DeepCM under miscellaneous scenarios. Furthermore, DeepCM can handle well dynamic target-BLER change.

Nonsingular worst-case noise in multiuser broadcast (or “downlink”) communication channels effectively characterizes the users' rate sum. This paper elaborates upon that worst-case-noise characterization for the special singular case. This elaboration is synergistic with the cognitive-radio concept of primary and secondary broadcast-channel users, allowing a mathematical, channel-dependent, and intuitively appealing labeling of user components. The multidimensional singular case adds additional term to the well-known worst-case-noise equation, which term is zero only when the noise is nonsingular. This generalizes a 2004 singular-worst-case-noise result due to Yu [1]. This generalized concept then also enables a new dual multiple-access characterization of a worst-case user-input autocorrelation. Examples appear, along with implications for evolving next-generation cellular-network optimization and policy, focusing on the channel-dependent primary/secondary user-component interpretation.

While constructing polar codes for successive-cancellation decoding can be implemented efficiently by sorting the bit channels, finding optimal polar codes for cyclic-redundancy-check-aided successive-cancellation list (CA-SCL) decoding in an efficient and scalable manner still awaits investigation. This paper first maps a polar code to a unique heterogeneous graph called the polar-code-construction message-passing (PCCMP) graph. Next, a heterogeneous graph-neural-network-based iterative message-passing (IMP) algorithm is proposed which aims to find a PCCMP graph that corresponds to the polar code with minimum frame error rate under CA-SCL decoding. This new IMP algorithm’s major advantage lies in its scalability power. That is, the model complexity is independent of the blocklength and code rate, and a trained IMP model over a short polar code can be readily applied to a long polar code’s construction. Numerical experiments show that IMP-based polar-code constructions outperform classical constructions under CA-SCL decoding. In addition, when an IMP model trained on a length-128 polar code directly applies to the construction of polar codes with different code rates and blocklengths, simulations show that these polar-code constructions deliver comparable performance to the 5G polar codes.

This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement-learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit-channels by reliability, as in most current algorithms. Instead, this technique decides whether the input bits should be frozen in a purely sequential manner. The equivalence of optimizing the polar-code construction for the SCL decoder under this technique and maximizing the expected reward of traversing a maze is drawn. Simulation results show that the standard polar-code constructions that are designed for the successive-cancellation decoder are no longer optimal for the SCL decoder with respect to the frame error rate (FER). In contrast, the proposed game-based construction method finds code constructions that have similar or lower FER for various code lengths and various list sizes of the SCL decoder, compared to the state-of-the-art construction methods. The advantage of the game-based constructions over the standard constructions increases with the channel signal-to-noise ratio and the list size of SCL decoding. Moreover, the learning is highly efficient in terms of the number of required training samples and computational operations.

This paper characterizes the latency of the simplified successive-cancellation (SSC) decoding scheme for polar codes under hardware resource constraints. In particular, when the number of processing elements$P$that can perform SSC decoding operations in parallel is limited, as is the case in practice, the latency of SSC decoding is$O\left(N^{1-1/\mu}+ \frac{N}{P}\log_{2}\log_{2}\frac{N}{P}\right)$, where$N$is the block length of the code and$\mu$is the scaling exponent of polar codes for the channel. Three direct consequences of this bound are presented. First, in a fully-parallel implementation where$P=\frac{N}{2}$, the latency of SSC decoding is$O\left(N^{1-1/\mu}\right)$, which is sublinear in the block length. This recovers a result from an earlier work. Second, in a fully-serial implementation where$P=1$, the latency of SSC decoding scales as$O(N\, \log_{2}\log_{2}N)$. The multiplicative constant is also calculated: we show that the latency of SSC decoding when$P=1$is given by$(2+o(1))N\, \log_{2}\log_{2}N$. Third, in a semi-parallel implementation, the smallest$P$that gives the same latency as that of the fully-parallel implementation is$P=N^{1/\mu}$. The tightness of our bound on SSC decoding latency and the applicability of the foregoing results is validated through extensive simulations.

Fast SC decoding overcomes the latency caused by the serial nature of the SC decoding by identifying new nodes in the upper levels of the SC decoding tree and implementing their fast parallel decoders. In this work, we first present a novel sequence repetition node corresponding to a particular class of bit sequences. Most existing special node types are special cases of the proposed sequence repetition node. Then, a fast parallel decoder is proposed for this class of node. To further speed up the decoding process of general nodes outside this class, a threshold-based hard-decision-aided scheme is introduced. The threshold value that guarantees a given error-correction performance in the proposed scheme is derived theoretically. Analysis and hardware implementation results on a polar code of length 1024 with code rates 1/4, 1/2, and 3/4 show that our proposed algorithm reduces the required clock cycles by up to 8%, and leads to a 10% improvement in the maximum operating frequency compared to state-of-the-art decoders without tangibly altering the error-correction performance. In addition, using the proposed threshold-based hard-decision-aided scheme, the decoding latency can be further reduced by 57% at Eb/N0= 5.0 dB.

This work analyzes the latency of the simplified successive cancellation (SSC) decoding scheme for polar codes proposed by Alamdar-Yazdi and Kschischang. It is shown that, unlike conventional successive cancellation decoding, where latency is linear in the block length, the latency of SSC decoding is sublinear. More specifically, the latency of SSC decoding is O(N1-1/μ), where N is the block length and μ is the scaling exponent of the channel, which captures the speed of convergence of the rate to capacity. Numerical results demonstrate the tightness of the bound and show that most of the latency reduction arises from the parallel decoding of subcodes of rate 0 or 1.

This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit-channels by reliability. Instead, this technique decides whether the input bits should be frozen in a purely sequential manner. The equivalence of optimizing the polar-code construction for the SCL decoder under this technique and maximizing the expected reward of traversing a maze is drawn. Simulation results show that the standard polar-code constructions that are designed for the successive-cancellation decoder are no longer optimal for the SCL decoder with respect to the frame error rate. In contrast, the simulations show that, with a reasonable amount of training, the game-based construction method finds code constructions that have lower frame-error rate for various code lengths and decoders compared to standard constructions.

An adaptive bandwidth allocation mechanism for the calendar associated with the Flexible Ethernet (FlexE) standard is proposed. The proposed method bases the FlexE calendar design on the clients' real transmit data rates. In particular, the proposed method treats clients with very low bandwidth utilization as minor clients and allows them to transmit in an opportunistic manner. Experiments on real Ethernet packet traces indicate that by using the proposed calendar scheme to allocate bandwidth to clients, the total required FlexE bandwidth can be reduced by up to 60% while meeting packet drop requirements.

This paper focuses on fast successive-cancellation (SC) decoding of polar codes. A threshold-based hard-decision-aided scheme is proposed to speed up the decoding process, especially when the communications channel has low noise. In addition, to eliminate the error-correction performance degradation caused by hard decisions, a backtracking strategy is introduced. Simulation results on a polar code of code length 1024 and rate 1/2 show that, with the help of the proposed scheme, the average decoding latency of existing fast SC decoding algorithms can be reduced by 53% at an Eb/N0 = 5.0 dB with negligible error-correction performance degradation.

This work analyzes the latency of the simplified successive cancellation (SSC) decoding scheme for polar codes proposed by Alamdar-Yazdi and Kschischang. It is shown that, unlike conventional successive cancellation decoding, where latency is linear in the block length, the latency of SSC decoding is sublinear. More specifically, the latency of SSC decoding is O(N1-1/μ), where N is the block length and μ is the scaling exponent of the channel, which captures the speed of convergence of the rate to capacity. Numerical results demonstrate the tightness of the bound and show that most of the latency reduction arises from the parallel decoding of subcodes of rate 0 and 1.

Ergodic Spectrum Management (ESM)'s basic features are introduced as a cloud-based management of wireless connectivity that targets improvement of internet-user's quality of experience. Ergodic Spectrum Management (or ESM) learns and exploits near-ergodicity, or time-consistency, to improve a communication-link connection's stable and efficient use in time, space, and frequency; while using consumer quality of experience as the target metric. ESM methods can also improve existing radio resource management, particularly advancing unlicensed spectrum-use efficiency to levels at or exceeding those associated with licensed spectra, as shown herein. ESM's use of learned probability distributions' dimensional (time, space, and frequency) consistencies enables latency-insensitive remote-cloud-based resource management to be applied to wireless multi-user transmission. ESM methods are developed for 3 increasingly more effective stages that correspondingly increasingly rely on data collection and functional-profile (policy) guidance of physical-layer design choices. ESM application to either and both of existing and future unlicensed- and licensed-spectra networks is suggested as a means to improve overall wireless performance. Examples and field data are provided to show the potential of very large improvements in wireless system connectivity, throughput, and quality of experience.

Wireless-wireline convergence and cellular wireless deployment can economically accelerate through partial transmission of wireless 4G, 5G (generally 3GPP-standards-compliant), and/or Wi-Fi 6 baseband signals on the billions of copper phone, Ethernet, coaxial cable, and other wireline connections. This article poses such a Cellular Subscriber Lines (CSL) re-use architecture and investigates large bandwidth-efficiency gains, as well as the consequent cost-efficiency improvement that accrues for CSL's deployment infrastructure. In-home wireless signals' seamless distribution partially over copper links can achieve good data-rate-versus-distance profile. Results here also expand to Wi-Fi (possibly with MIMO use) on Ethernet multi-pair cables, finding very large gains over existing enterprise mesh (ad-hoc or otherwise) approaches.

This study investigates the impact of imperfect channel state information that is caused by feedback delay with time‐variant channels and also by channel estimation errors with an opportunistic source‐pair selection strategy. The investigation considers multi‐user bi‐directional wireless relaying networks. The opportunistic source‐pair selection strategy selects the appropriate source‐pair node among N available nodes. The selection strategy is based on each source pair's maximum sum‐rate in each time slot. According to analytical, asymptotic, and Monte–Carlo simulation results, the opportunistic source‐pair selection strategy, besides achieving a near‐optimal solution for inter‐cell interference that is caused by other user‐pairs in the system model, also achieves diversity order in high signal‐to‐noise regimes. Moreover, the opportunistic source‐pair selection strategy outperforms the max–min‐based selection strategy in such a system model. Results also show that feedback delay degrades the achievable diversity order from N to 0 while affecting coding gain. The results also show that the channel estimation error case does not affect the achievable diversity order, but it does affect the system coding gain in low‐signal‐to‐noise regimes. Moreover, the channel estimation error effects upon system coding gain become negligible at high‐signal‐to‐noise regimes.

By suppressing repeated content deliveries, wireless caching has the potential to substantially improve the energy efficiency (EE) of the fifth-generation communication networks. In this paper, we propose two novel energy-efficient caching schemes in heterogeneous networks, namely, scalable video coding (SVC)-based fractional caching and SVC-based random caching, which can provide on-demand video services with different perceptual qualities. We derive the expressions for successful transmission probabilities and ergodic service rates. Based on the derivations and the established power consumption models, the EE maximization problems are formulated for the two proposed caching schemes. By taking logarithmic approximations of the l0-norm, the problems are efficiently solved by the standard gradient projection method. Numerical results validate the theoretical analysis and demonstrate the superiority of our proposed caching schemes, compared to three benchmark strategies.

An adaptive overhearing protocol is proposed for the two-way multi-antenna-relay network composed of a base station (BS), relay, and two user equipments (UEs), where one UE is in the uplink (UL) transmission mode (UE-Tx) while the other is in the downlink (DL) reception mode (UE-Rx). Specifically, UE-Rx not only receives the DL signal transmitted by BS but also overhears the signal transmitted by UE-Tx, and exploits the overheard signal to improve the detection performance. The transmit adaptive weights of UE-Tx over the two times slots and the precoding matrix at the relay in the second time slot are jointly optimized via the proposed iterative algorithm in the sense of maximizing the minimum signal-to-interference-plus-noise-ratio. Numerical results show that the proposed joint design provides significant sum-rate gain over the existing overhearing scheme.

Broadband Internet service providers (ISPs) are for-profit companies: they provide high-speed Internet service to customers in order to maximize revenue. Their revenue depends on prices they are able to charge the customers, which in turn depends on the data rates provided. This paper defines the `revenue capacity' of a communication channel as the maximum revenue an ISP can achieve by allocating data rates to customers, given an exogenous price function and an underlying physical-layer model. Revenue capacity is the maximum revenue for the ISP constrained only by the physical-layer limitations of the multiuser channel under the assumption that the ISP can dictate data rates to its customers. This paper proposes an algorithm to compute the revenue capacity for multiuser Gaussian channels with staircase price functions, and to produce feasible data rates achieving the revenue capacity. The paper concludes with an analysis of incremental migration of VDSL to vectored VDSL, quantifying the increase in revenue capacity with the increase in the percentage of vectored users.

Two‐way relaying systems efficiently accomplish transmissions in both directions within dual‐hop, hence, two time slots can be saved compared with one‐way relaying. However, the conventional two‐way relaying protocol requires the assumption of symmetric traffic demands, that is, each transmitter node has to act as a receiver in latter slot. This assumption restricts applying two‐way relay to general and practical scenarios. In this study, the authors release this unpractical constraint by assuming that the transmitter in slot 1 and receiver in slot 2 can be any nodes, which are not necessarily being the same. For this scenario, a novel transmission protocol exploiting the overhearing link to suppress the interference caused by asymmetric traffic, denoted as overhearing transmission, is proposed. With the overhearing transmission protocol, and in the light of green communications, the precoding matrices at the decode‐and‐forward multi‐antenna relay are optimised to improve energy efficiency in both uplink and downlink (DL) transmission directions, where the objective is to minimise the transmit power at the relay while guaranteeing a target transmission rate. The authors transform the original non‐convex problem to an equivalent form, which can be readily solved by typical semi‐definite relaxation approaches. An efficient algorithm is further proposed to implement the precoding design in practice. Simulation results show that the proposed algorithm is able to minimise the power consumption at the relay, with the minimum rate constraints of both the uplink and DL transmissions being satisfied.

A primary source of increased read time on NAND flash comes from the fact that, in the presence of noise, the flash medium must be read several times using different read threshold voltages for the decoder to succeed. This paper proposes an algorithm that uses a limited number of rereads to characterize the noise distribution and recover the stored information. Both hard and soft decoding are considered. For hard decoding, this paper attempts to find a read threshold minimizing bit error rate (BER) and derives an expression for the resulting codeword error rate. For soft decoding, it shows that minimizing BER and minimizing codeword error rate are competing objectives in the presence of a limited number of allowed rereads, and proposes a tradeoff between the two. The proposed method does not require any prior knowledge about the noise distribution but can take advantage of such information when it is available. Each read threshold is chosen based on the results of previous reads, following an optimal policy derived through a dynamic programming backward recursion. The method and results are studied from the perspective of an SLC Flash memory with Gaussian noise, but this paper explains how the method could be extended to other scenarios.

This paper presents an investigation of the secrecy performance of amplify-and-forward (AF) distributed beamforming (DBF) and opportunistic relaying (OR) through K untrustworthy relays. The capacity scaling and achievable diversity order of a secure communication are derived for K → ∞ and in high signal-to-noise-ratio (SNR) regimes, respectively. The DBF is shown to convey confidential messages with a capacity scaling of 1/2 log K regardless of the trustworthiness of the relays, even without intended jamming (IJ), where 1/2 log K corresponds to the maximal capacity scaling of cooperative relaying in non-eavesdropping environments. However, using multiple untrustworthy relays worsens the secrecy performance of the OR, and as K increases, the secrecy capacity converges to zero. When secrecy outage performance with IJ is considered, the achievable diversity order for both the DBF and OR is limited to one. However, only the DBF exploits the benefits using multiple untrustworthy relays, and its secrecy outage probability decreases exponentially as K increases.

This paper introduces an efficient method for communication resource use in dense wireless areas where all nodes must communicate with a common destination node. The proposed method groups nodes based on their distance from the destination and creates a structured multi-hop configuration in which each group can relay its neighbor's data. The large number of active radio nodes and the common direction of communication toward a single destination are exploited to reuse the limited spectrum resources in spatially separated groups. Spectrum allocation constraints among groups are then embedded in a joint routing and resource allocation framework to optimize the route and amount of resources allocated to each node. The solution to this problem uses coordination among the lower-layers of the wireless-network protocol stack to outperform conventional approaches where these layers are decoupled. Furthermore, the structure of this problem is exploited to obtain a semi-distributed optimization algorithm based on the alternating direction method of multipliers (ADMM) where each node can optimize its resources independently based on local channel information.

In this paper, the application of radio over fiber (RoF) based wireless communications for smart metering and power distribution is introduced. A RoF based network has the potential to enhance both the coverage and spectral efficiency of smart grid wireless networks since its major benefit is adaptability to temporal and spatial traffic variations. A clustered architecture is presented which provides signal diversity to enhance the coverage and capacity of smart grid communications. Examples are presented to illustrate the improvement in coverage and latency of a smart grid wireless network when RoF is used instead of a conventional wireless network.

This paper investigates the effect of imperfect channel state information (CSI) on the outage performance of cooperative distributed beamforming (DBF). The acquisition of perfect CSI is disturbed by outdated CSI and channel estimation errors. Decode-and-forward relays are considered with individual power constraints at each relay. Considering a training-and-feedback strategy to acquire CSI, a closed-form approximate expression for outage probability and the achievable diversity gain are first provided under Rayleigh fading channels. Numerical observations verify that the approximation is very tight. It is shown that outdated CSI seriously degrades the performance, and therefore, the outage probability is bounded and no diversity is achieved. Conversely, channel estimation errors cause slight performance degradation, and full diversity order is still achievable. However, even when CSI is outdated, it is shown that the asymptotic outage decreases as the number of relays K increases, where the logarithm of the outage probability decreases at the rate of K log K. This paper shows that, when the destination re-estimates the current CSI for decoding, the effect of outdated CSI is greatly mitigated and consequently achieves a diversity gain of one. To re-estimate the current CSI with small overhead, the beamformed training sequence (BFTS) strategy is proposed, in which a new closed-form formula for minimum-mean-square-error estimation is presented using Gaussian approximation. Numerical results verify that the outage performance with the proposed BFTS scheme is close to that of a perfect estimation. A closed-form outage expression of DBF with the proposed BFTS scheme is also presented under an assumption of high-signal-to-noise ratio (SNR), but the expression is very tight even in low-to-moderate SNR regimes.

This paper investigates the performance gain obtained by creating a hotspot-slave configuration of nodes in densely populated areas. In doing so, a semi-distributed algorithm, referred to as CaSRA (Clustering and Spectrum assignment and Resource Allocation), that allows the hotspots to tether over locally available white-spaces is proposed. CaSRA, performs in three-steps: 1) clusters the nodes based on the K-means clustering algorithm, 2) assigns white-space spectrum to each cluster based on a distributed graph-coloring approach to maximize spectrum reuse, and 3) allocates physical layer resources to individual users based on local channel information. Unlike small cells (femtocells, relays, and WiFi networks), this approach does not require any additions to the existing infrastructure, but allows the nodes, themselves, to act as hotspots. Simulation results show that given fixed amount of network resources, the proposed algorithm can significantly improve the overall performance of network users.

This paper introduces an efficient method for communication resource use in dense wireless areas, where all nodes must communicate with a single destination node. By employing a large number of active radio nodes as relays, and exploiting a common direction of communication toward the single destination, this method groups nodes based on their location and creates a structured multi-hop configuration in which each group can forward its neighbor's data. Such configuration allows spatially separated groups to reuse the limited spectrum resources. Optimum spectral allocation among groups is then embedded in a conventional joint routing and resource allocation framework to obtain a centralized convex optimization problem. This problem's solution achieves optimal coordination among wireless-network lower-layer protocol stack and thereby significantly improves network performance.

Very-high rate Digital Subscriber Lines (VDSL) are beginning to be deployed by competitive network operators. Short lines can radiate high power crosstalk into long lines hence the power transmitted on the short lines should be controlled to limit the degradation they may cause to a competitor's long lines. This paper presents a new method of enhanced upstream power backoff (eUPBO). eUPBO limits the normalized ensemble of transmit power across lines, unlike previous techniques that operated independently per line. This new technique is effective because it limits the weighted sum crosstalk into any given line, and allows flexible optimizations. This paper shows new algorithms for eUPBO optimizing transmit power per band per user (Level 1), and for eUPBO optimizing transmit spectra per user (Level 2). Simulation results show that the flexibility of eUPBO can significantly increase select users' bit rates as chosen by the VDSL operator.

As next generation networks are evolving toward providing the mobile users with higher bandwidth and better Quality of Service, relaying was considered as a solution that will contribute to a better service provisioning to the end users. In a recent paper, grouping the mobile nodes into clusters was proposed as an alternative solution to relaying. This technique allows a coordinated tethering of the wireless nodes in cellular networks controlled by the base station (BS). In this context, for better spectrum usage, some users will relay the information between the BS and other devices using the newly vacated TV white space (TVWS) bands. However, the proposed clustering approach did not take into account the numerous changes that can occur in the cellular network. Therefore, in this paper, we will extend the existing clustering configuration to consider mobile users' requirements and network events by studying the corresponding handover scenarios and signaling schemes. This will reduce the complexity of the clustering algorithm in terms of time and signaling, and it will improve the network performance and service quality as will be also shown via several user case scenarios.

In dense wireless areas where the cellular spectrum resources are insufficient, the conventional approach is to install more base-stations (BS) or offload some of the traffic onto unlicensed WiFi bands. Both approaches require adding new infrastructure that might be necessary for only a short time. Taking advantage of dual-hop communication, frequency reuse policies, and opportunistic use of white-spaces, this paper proposes an algorithm for operator-controlled tethering over TV white-space (TVWS). As such, in a dense wireless area, some nodes can act as hotspots and tether data to and from their corresponding slaves over TVWS. The proposed algorithm iteratively clusters the nodes into hotspots and slaves, and allocates resources with the objective of maximizing spectrum utilization. Evaluations show that the proposed algorithm can effectively exploit TVWS spectra, and given a fixed amount of network resources, it can significantly increase the number of supported users.

This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution using iterative Jacobian method instead of using centralized schemes. A totally asynchronous distributed power allocation for sum-rate maximization on cognitive GMACs is suggested. Simulation results show that this distributed algorithm for power allocation converges to a fixed point and the solution achieves almost the same performance as the exhaustive search.

This paper considers physical-layer network coding (PNC) with M-ary phase-shift keying (MPSK) modulation in two-way relay channel (TWRC). A low complexity detection technique, termed symbol-based PNC (SPNC), is proposed for the relay. In particular, attributing to the outer product operation imposed on the superposed MPSK signals at the relay, SPNC obtains the network-coded symbol (NCS) straightforwardly without having to detect individual symbols separately. Unlike the optimal multi-user detector (MUD) which searches over the combinations of all users' modulation constellations, SPNC searches over only one modulation constellation, thus simplifies the NCS detection. Despite the reduced complexity, SPNC achieves full diversity in multi-antenna relay as the optimal MUD does. Specifically, antenna selection based SPNC (AS-SPNC) scheme and signal combining based SPNC (SC-SPNC) scheme are proposed. Our analysis of these two schemes not only confirms their full diversity performance, but also implies when SPNC is applied in multi-antenna relay, TWRC can be viewed as an effective single-input multiple-output (SIMO) system, in which AS-PNC and SC-PNC are equivalent to the general AS scheme and the maximal-ratio combining (MRC) scheme. Moreover, an asymptotic analysis of symbol error rate (SER) is provided for SC-PNC considering the case that the number of relay antennas is sufficiently large.

Recently, wireless communication industries have begun to extend their services to machine-type communication devices as well as to user equipments. Such machine-type communication devices as meters and sensors need intermittent uplink resources to report measured or sensed data to their serving data collector. It is however hard to dedicate limited uplink resources to each of them. Thus, efficient service of a tremendous number of devices with low activities may consider simple random access as a solution. The data collectors receiving the measured data from many sensors simultaneously can successfully decode only signals with signal-to-interference-plus-noise-ratio (SINR) above a certain value. The main design issues for this environment become how many data collectors are needed, how much power sensor nodes transmit with, and how wireless channels affect the performance. This paper provides answers to those questions through a stochastic analysis based on a spatial point process and on simulations.

On NAND flash, a primary source of increased read time comes from the fact that in the presence of noise, the flash medium must be read several times using different read threshold voltages to find the optimal read location, which minimizes bit-error-rate. This paper proposes an algorithm to estimate the optimal read threshold in a fast manner using a limited number of re-reads. Then it derives an expression for the resulting BER in terms of the minimum possible BER. It is also shown that minimizing BER and minimizing codeword-error-rate are competing objectives in the presence of a limited number of allowed re-reads, and a tradeoff between the two is proposed.

Maximizing the run-time of battery-limited mobile devices is contingent on efficient energy management at the mobile device wireless interface. IEEE 802.11 wireless local area network (WLAN) power save mode (PSM) minimizes the mobile device energy consumption by allowing the device to de-activate its wireless interface periodically while the access point (AP) stores its incoming packets. Further increase in energy conservation occurs through the proposed decision-making algorithm, Intelligent-PSM (IPSM), that determines dynamic, as opposed to fixed, activation times based on the state of the mobile user. IPSM can be implemented with minimal change to the standard PSM transmission scheme. Simulation results show that with a maximum allowable packet delay of 1 second and limited AP buffering capacity, energy conservation of up to about 37% compared to standard PSM can be achieved.

The satisfaction of a mobile user in a heterogeneous wireless environment relies heavily on the appropriate choice of network. With the presence of various wireless technologies and advances in smart mobile devices, the mobile terminal in next generation wireless communications will likely make intelligent handoff decisions to optimize the user Quality of Experience (QoE). This paper investigates network selection and handoff decision with the goal of maximizing user QoE. An algorithm based on Q-learning is obtained that chooses the best network based not only on the current network state but also the potential future network and device states. As opposed to other dynamic programming-based algorithms, this method does not require the knowledge of the statistics of the wireless environment, but learns an optimum policy by utilizing the mobile device's past experience. It is shown that the QoE results of the proposed Dynamic Handoff Decision (DHD) algorithm come very close to the performance of an optimum oracle algorithm, while on average fewer number of network handoffs are required.

This paper studies a multi-carrier based spectrum sharing system, in which two users iteratively update their respective transmit power allocation over parallel subcarriers (SCs) to maximize the individual transmit rate. Unlike the conventional iterative water-filling (IWF) algorithm that adopts the single-user detection (SD) at each user's receiver by treating the interference from all other users as additive noise, this paper proposes a new decentralized resource allocation scheme, namely iterative spectrum shaping (ISS), in which each receiver applies multiuser detection to opportunistically cancel the co-channel interference over selected SCs, thus termed opportunistic multiuser detection (OMD). Two coding schemes are investigated to exploit different forms of "frequency diversity" gains with OMD: carrier independent coding, which applies independent codebooks for different SCs to maximize the interference-decoding diversity; and carrier joint coding, which uses one single codebook across all the SCs to achieve the full coded diversity. For each coding scheme, the optimal transmit power allocation strategy is derived to maximize one user's transmit rate, with the power and rate allocation of the other user being fixed. Simulation results show that the converged system throughput by the proposed ISS algorithm with OMD is significantly improved over that by the conventional IWF with SD, in cognitive radio (CR) based wireless spectrum sharing networks.

The severe interference from neighbor copper lines, commonly known as crosstalk, is a well-known limitation that can reduce the upstream rate of a victim user by 50% or more in dense VDSL (Very high bit-rate Digital Subscriber Lines) deployment. This problem has been partially addressed by the use of UPBO (Upstream Power BackOff). UPBO blindly controls transmit PSD (Power Spectral Densities) based on the pre-defined parameters and channel measurements without considering each user's target data rate. Although UPBO can provide fair protection against crosstalk, it still leaves room for practical improvement. This paper proposes a distributed algorithm that dynamically controls transmit power according to each line's need and capacity. The algorithm effectively improves data rates and line reaches in real VDSL deployment.

The severe interference from neighbor copper lines, commonly known as crosstalk, is a well-known limitation that can cause 50% or larger reduction in the upstream rates of dense VDSL (Very high bit-rate Digital Subscriber Lines) deployments. To handle this problem, UPBO (Upstream Power BackOff) has been studied in literature, and subsequently standardized. UPBO blindly selects transmit PSD (Power Spectral Densities) based on the pre-defined parameters and channel measurement without considering each line's target data rate. Although UPBO can provide significant protection against crosstalk, it still leaves room for practical improvement. This paper proposes a distributed algorithm that dynamically controls transmit power based on each line's need and capability. The algorithm can achieve significant rate and reach gains in real VDSL deployments.

With the coexistence of various wireless technologies, next generation wireless communications will likely consist of an integrated system of networks, where the Access Points (APs) and Base Stations (BSs) work together to maximize the mobile-user Quality of Service (QoS). In such heterogeneous environment where handheld devices with different access technologies are not uncommon, it should be possible to select networks and seamlessly switch from one AP/BS to another in order to elevate user performance. In this paper, this type of network selection and handover mechanism with the goal of maximizing QoS is formulated as a Markov Decision Process (MDP). An algorithm based on Reinforcement Learning (RL) is then obtained that selects the best network based not only on the current network load but also the potential future network states. This algorithm aims at balancing the number of handovers and the achievable QoS. The results illustrate that while the QoS performance of the proposed algorithm is comparable to the performance of the optimum opportunistic selection algorithm, fewer number of network handovers (on average) are required. In addition, compared to the existing predefined network selection strategies with no handover, the MDP-based algorithm offers significantly better QoS.

This papers considers the downlink of a wireless multicell downlink orthogonal frequency division multiple-access (OFDMA) system where neighboring base-stations (BSs) can jointly encode and transmit data signals to their users using zero-forcing (ZF) precoding in each frequency tone, but only a limited backhaul-capacity is available for each BS to share its user's data streams with the neighboring BSs. A numerical algorithm is proposed to maximize the network-wide utility of this system subject to backhaul capacity constraints. The proposed algorithm first selects a subset of frequency tones for each BS to share its user's data streams with the neighboring BSs and then, jointly schedules users and adapts the precoding coefficients and the power spectra of the BSs to effectively utilize the limited backhaul capacity. Numerical results show that using the proposed algorithm, the gain in downlink sum-rate per cell can be made to scale linearly with the available backhaul capacity per BS between the no-cooperation and the full-cooperation scenarios.

A perfect space-time code can provide the optimal performance in many theoretical and practical aspects. For example, a perfect space-time code can utilize the full coding rate to achieve the maximum throughput of a MIMO channel. The property of non-vanishing determinant provides the optimal tradeoff between spatial diversity and multiplexing. On the practical side, each information symbol can be encoded without the necessity of extra energy. The RF power amplifier can also be simplified based on the uniform average power of transmission over all transmit antennas and time slots. This paper proposes a new perfect space-time code for 5 × 5 MIMO channels. The new design can yield an improved minimum determinant over QAM.

The hierarchical network structure was proposed in the early 80s and becomes popular nowadays. The routing complexity and the routing table size are the two primary performance measures in a dynamic route guidance system. Although various algorithms exist for finding the best routing policy in a hierarchical network, hardly exists any work in studying and evaluating the aforementioned measures for a hierarchical network. In this paper, a new mathematical framework to carry out the averages of the routing complexity and the routing table size is proposed to express the routing complexity and the routing table size as the functions of the hierarchical network parameters such as the number of the hierarchical levels and the subscriber density (cluster-population) for each hierarchical level.

A spectral efficient multihop relaying scheme is proposed based on scheduling the source transmission in alternate time slots. Each relay processes its received signal and forwards it in the subsequent time slot. An interference cancellation mechanism is developed to eliminate the interference term at each relay caused by the source alternate-based transmission. The frame error probability and the achievable rate of the proposed scheme are evaluated. It is shown that the individual bit-by-bit detection at the destination performs almost as well as the optimal joint detection, and achieves a data rate that approaches the Shannon channel capacity limit. In addition, the proposed scheme significantly outperforms the conventional orthogonal multihop transmission in terms of the achievable data rate, especially for larger numbers of hops, with slightly inferior frame error rate performance.

This paper proposes an enhanced opportunistic beamforming scheme with power allocation search algorithms over finite feedback channels for a broadcast channel. Instead of continually varying the power allocation for multiple beams based on instantaneous channel state information (CSI) feedback, the proposed scheme determines power allocation in advance solely based on channel statistics and the number of mobile stations (MSs). This scheme maintains power allocation throughout multiple training and data transmission periods as long as channel statistics and the number of MSs are unchanged. As a result, the proposed scheme reduces the complexity for searching power allocation, and becomes robust over finite feedback channels. Computer simulations show that the proposed power allocation search algorithms efficiently find the near optimal power allocation with low complexity. The simulations also show that, although the proposed scheme predetermines power allocation solely based on channel statistics and the number of MSs, it outperforms the opportunistic beamforming scheme using instantaneous CSI feedback with finite feedback rates.

This paper studies the design of decentralized multiuser (MU) multi-antenna/multiple-input-multiple-output (MIMO) systems for wireless spectrum sharing over a fixed frequency band, in which users independently update their transmit covariance matrices for individual transmit-rate maximization in an iterative manner. This design problem was usually investigated in the literature by assuming that each user treats the co-channel interference from all the other users as additional noise at the receiver and, accordingly, the conventional single-user decoder (SUD) is applied. This paper considers a more advanced decoder design approach for decentralized MU-MIMO systems, in which each user opportunistically cancels the co-channel interference from certain subset of coexisting users when their signals are jointly decodable with the desired signal at the receiver. The new decoding scheme is thus termed opportunistic multiuser detection (OMD). This paper derives the optimal transmit covariance matrix for users' iterative maximization of individual transmit rates with the proposed OMD at the receiver, and evaluates the achievable throughput gains for decentralized MU-MIMO systems against the conventional SUD. Promising applications of the OMD for achieving maximum interference mitigation gains in spectrum sharing based wireless systems such as cognitive radio networks and cellular networks are demonstrated.

Cyclic division algebras have been extensively utilized to design approximately universal codes. Their error probabilities can be intrinsically improved by a small integer non-norm element. This paper proves the insufficiency of existing encoding methods for obtaining the non-norm element 1+i over QAM and the numbers of transmit antennas: {n:8|n}. An improved method is then presented to overcome this difficulty by number theory. As a by-product, we show that 1+i is one of the smallest integer non-norm elements over QAM and n≥5.

As field trials and initial deployments of Vectored DSL systems materialize in the next few years, Vectored DSL systems will often co-exist with non-vectored DSL systems sharing the same cable. For such mixed-binder scenarios with vectored and non-vectored lines, this paper presents an optimal Dynamic Spectrum Management (DSM) technique referred to as Mixed-binder Optimum Spectrum Balancing (MixOSB) to find the optimal transmit PSD spectra. When the mixed-binders have short vectored lines and long non-vectored lines, simulations show that MixOSB has substantial performance gains over applying existing DSM techniques independently to the vectored DSL systems and non-vectored DSL systems because it reduces the interference induced by the vectored lines on the non-vectored lines. The high computational complexity of MixOSB prohibits its practical implementation. So, a low-complexity practically-implementable mixed-binder multi-level water-filling (MixMLWF) algorithm is proposed and simulations show its performance is close to the solution given by MixOSB.

Orthogonal frequency division multiplexing (OFDM) is a prevalent telecommunication technology to mitigate multipath distortion with high-order modulations such as quadrature amplitude modulation (QAM). However, uncoded OFDM systems also have a serious drawback of high peak-to-mean envelope power ratio (PMEPR). On the other hand, coded OFDM systems can reduce the PMEPR problem but often lead to low code rates. There is thus a tradeoff between PMEPR and code rate in the design of OFDM systems. In this paper, PMEPR reduction for OFDM 64- and 256-QAM sequences is comprehensively studied. Four new families of 64-QAM sequences and seven new families of 256-QAM sequences are proposed to achieve the lowest PMEPR, the highest code rate, or the tradeoffs between these two metrics. Through the comparison with all other OFDM 16- or 64-QAM sequences, these new families of OFDM sequences can facilitate higher code rates. Furthermore, many of these new sequences have lower PMEPR than other OFDM sequences. Adjustment of the tradeoff between PMEPR and code rate can be made to meet the stringent demand in low PMEPR or the need for high code rate subject to various system requirements. Moreover, the construction method of the proposed new sequences is quite simple.

Multi-user buffer control is a closed-loop transmission strategy to ensure users buffers do not underflow or overflow. The dynamic scheme requires buffer state information and cooperation among transmitters. By altering the average arrival rate to users, the transmitters cause users' buffer levels to drift away from underflow and overflow conditions. The paper presents three schemes that suggest coordination among transmitters significantly reduces the resource requirement to ensure multi-user buffer stability.

We present a scheme to ensure Quality of Service for buffered variable rate applications. The scheme does not require knowledge of the channel distributions, indeed will track changing statistics, and is effectively spectrum optimal. The scheme employs stochastic approximation where the optimal solution is learned through updates of the Lagrange multiplier. The convergence speed and nearness to optimality are found, and the buffer stability probabilities are met. Analysis and simulations are provided to validate the scheme's performance.

When an approximately universal code is designed with cyclic division algebras, the normalized diversity product can be intrinsically increased by a small integer non-norm element. While 2 + i has been the smallest integer non-norm element in all known 8 × 8 designs over QAM, this paper presents another new 8 × 8 code with the smaller non-norm element 1 + i over QAM.

Multi-user rate region maximization for the interference channel has attracted great attention recently. However, close to optimal performance algorithms have high complexity, while the fast and distributed algorithms such as the iterative waterfilling algorithm suffer from poor performances, especially when the interferences are severe. Moreover, a lot of works deal with the case when the number of sub-channels L is equal to one, or perform well with a large number L (i.e. asymptotic case). Few works investigate the optimality under the small and finite L. For networks like cognitive radios, the secondary users can only sense a limited number of available sub-channels. As a result, rate region maximization for finite number of sub-channels becomes an issue of vital importance. In this paper, we propose a heuristic solution for the rate region maximization with low complexity and high performance. The basic idea is to select a limited set of combinations of subchannel assignments which most likely achieve the boundary of the rate region, and then construct the convex hull based on the iterative distributed solution. The complexity of the proposed algorithm is O(N2L2 log L) (without multilevel searches in the Optimal Spectrum Balancing (OSB) algorithm), where N is the number of users. Simulation results show that the proposed scheme can achieve performances comparable to those of a full search solution and OSB solution, and significantly better than the iterative waterfilling scheme in the high interference case.

This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution using iterative Jacobian method instead of using centralized schemes. Numerical results show that this distributed algorithm for power allocation is converged to a fixed point and the solution achieves almost the same performance of the exhaustive search.

This paper presents a new quadratic-time algorithm for joint Tx and Rx antenna selection (AS). The proposed approximate optimum executes much faster than the semidefinite-relaxation method, and hence becomes more robust in preserving full AS diversity for space-time coded systems over Rayleigh fading channels. Numerical results confirm the achieved approximation ratios of maximum mutual information and Frobenius norm of channel close to one.

This letter considers a sum-rate-maximizing power allocation problem under the Gaussian cognitive multiple-access channel (MAC), where primary users and secondary users may communicate under mutual interference. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple method to find a solution using semidefinite relaxation (SDR). Simulation results show that the solution achieves almost the same performance of the exhaustive search, within polynomial time.

With the advent of new applications, one of the primary applications supported in downlink cellular systems is streaming video. QoS for streaming video entails data transmission to the mobile stations with limited latency and limited jitter. This requirement on latency and jitter can be mapped to the number of yet-to-be-played packets in a mobile station's buffer, to always be above a certain minimum. Additionally, there should be no overflow of finite-size user buffers. This paper solves the problem of optimal resource allocation in a downlink OFDMA system with buffer constraints for all downlink users. The optimal strategy is shown to be a generalized version of water-filling and channel-inversion. Specifically, with infinite buffer size and no minimum constraint on buffer, it reduces to water-filling; and to channel-inversion in the absence of a buffer. It is shown that scheduling gains from the derived optimal strategy, in terms of number of users that the system can support, can be an order-of-magnitude higher than that of heuristic scheduling schemes.

The capacity of today's cellular mobile communications systems is mainly limited by inter-cell interference. Multi-cell joint transmission or joint detection schemes are means to overcome this limitation and to actively exploit signal propagation across cell borders rather than treating it as noise. In the cellular uplink, messages of multiple terminals can be detected jointly by cooperating base stations, a concept which has shown to significantly increase the efficiency of spectrum usage. Particularly, the performance of cell-edge users and thus system fairness is improved. A major drawback of multi-cell signal processing is the additional backhaul data rate that is required to exchange information among cooperating base stations. In this paper, we examine the performance of different base station cooperation schemes from an information theoretic point of view. The main contribution is the examination of a novel cooperation scheme that is based on the exchange of compressed transmit signals that are known at a base station after the decoding of a message in a very general system model.

This paper addresses the power allocation problem on relaying channels with user-cooperation for multi-user orthogonal frequency division multiplexing (OFDM) systems. The proposed problem is based on dual-mode mobile stations (MSs), where one interface is used to receive signals from a base station (BS) and the other is used to forward the signals to nearby MSs through out-of-band relaying. This dual-mode operation enables MSs to cooperate with one another without consuming the capacity of a broadcast channel. Theoretically, the cooperation among MSs over orthogonal relaying channels has already been defined as conferencing. The proposed scheme uses conferencing to consider a broadcast channel with user-cooperation, where mobile power is distributed among subcarriers. Simulation results demonstrate that the proposed scheme achieves improved performance over the equal-power-allocation scheme on relay channels and the conventional broadcast scheme. These results are shown by considering the average throughput and the outage throughput.

This paper presents a cooperative relay strategy with a game-theoretic perspective. In multi-hop networks, each node needs to send traffic via relay nodes, which behave independently while staying aware of energy constraints. To encourage a relay to forward the packets, the proposed scheme formulates a Stackelberg game where two nodes sequentially bid their willingness weights to cooperate for their own benefits. Accordingly, all the nodes are encouraged to be cooperative only if a sender is cooperative and alternatively to be non-cooperative only if a sender is non-cooperative. This selective strategy changes the reputations of nodes depending on the amount of their bidding at each game and motivates them to maintain a good reputation so that all their respective packets can be treated well by other relays. This paper analyzes a Nash equilibrium from the proposed scheme and validates a sequential-move game by Stackelberg competition as opposed to a simultaneous-move game by Cournot competition. Simulation results demonstrate that the proposed scheme turns non-cooperative nodes into cooperative nodes and increases the cooperative relaying stimulus all over the nodes. Thus, every node forwards other packets with higher probability, thereby achieving a higher overall payoff.

When transmitting at a fixed-rate to a wireless mobile terminal with strict latency requirements channel inversion is often used but at the cost of a significant loss in efficiency. Further, many such systems utilize limited packet buffering at the mobile terminal. In this paper we propose a method to recapture the lost spectral efficiency by exploiting the local buffer. Specifically, in severe channel conditions, latency and buffer state information (BSI) affords the transmitter to wait for good channel conditions rather than attempt to waste power through channel inversion. We propose a scheme that has nearly the spectral efficiency of optimal water-filling in time, yet is able to guarantee Quality of Service by ensuring a probabilistic buffer stability criterion. The solution is a cross-layer approach that utilizes event triggered BSI.

This paper studies the design of a decentralized multiuser MIMO system for spectrum sharing over a fixed bandwidth, where the coexisting users independently update their transmit covariance matrices for individual rate maximization via an iterative manner. This design problem was usually investigated in the literature by assuming that each user treats the co-channel interference from all the other users as additional noise at its receiver, i.e., the conventional single-user decoding (SUD) for the MIMO channel is applied. In this paper, we propose a new decoding method for the decentralized multiuser MIMO system, whereby each user opportunistically cancels the co-channel interference from some or all of the other users via applying multiuser detection techniques, thus named opportunistic multiuser detection (OMD). This paper studies the optimal transmit covariance matrix for each user to iteratively maximize transmit rate with the proposed OMD, and shows the resultant capacity gains over the conventional SUD.

Treating the interference as noise in the n-user interference channel, the paper describes a novel approach to the rates region, composed by the time-sharing convex hull of 2n-1 corner points achieved through On/Off binary power control. The resulting rates region is denoted crystallized rates region. By treating the interference as noise, the n-user rates region frontiers has been found in the literature to be the convex hull of n hyper-surfaces. The rates region bounded by these hyper- surfaces is not necessarily convex, and thereby a convex hull operation is imposed through the strategy of time-sharing. This paper simplifies this rates region in the n-dimensional space by having only an On/Off binary power control. This consequently leads to 2n- 1 corner points situated within the rates region. A time-sharing convex hull is imposed onto those corner points, forming the crystallized rates region. The paper focuses on game theoretic concepts to achieve that crystallized convex hull via correlated equilibrium. In game theory, the correlated equilibrium set is convex, and it consists of the time-sharing mixed strategies of the Nash equilibriums. In addition, the paper considers a mechanism design approach to carefully design a utility function, particularly the Vickrey-Clarke-Groves auction utility, where the solution point is situated on the correlated equilibrium set. Finally, the paper proposes a self learning algorithm, namely the regret- matching algorithm, that converges to the solution point on the correlated equilibrium set in a distributed fashion.

This paper presents a new set of quasi-orthogonal space-time block codes (QOSTBCs) with symbol-by-symbol maximum likelihood (ML) detections for four transmit antennas over quasi-static Rayleigh fading channels. Each of them is analytically proved to achieve full diversity and the same coding gains as the coordinate-interleaved orthogonal design by individually using their optimal constellation rotations over arbitrary QAM or 4M-PSK constellations. Previous designs are included in our systematic formulation as well. Together with the simulation results, the coding loss paying for simplifying the optimal decoders from complex symbol pairwise to symbol-by-symbol ML detections is found asymptotically equal to 0.21 dB, for the QOSTBCs achieving full diversity and the optimal coding gains over general QAM constellations.

In typical home power-line communication (PLC) networks using contention-based access methods, providing quality-of-service (QoS) to high-priority users often comes at the expense of reducing the throughput of low-priority users. This paper proposes a cross-layer protocol which involves interaction between the physical (PHY) and the medium-access-control (MAC) layers, for ensuring politeness of the high-priority users toward the low-priority users for uplink transmission in home PLC networks. This protocol modifies the contention-based CSMA protocol of the MAC layer to exploit the cyclostationarity of the noise in home PLC networks. The PLC noise spectrum has been shown in literature to be periodic with the period of AC line cycle. Using this periodicity, the proposed protocol allows longer medium-access times for low-priority users in every AC line cycle, while meeting the high throughput requirements of the high-priority users. The proposed cross-layer protocol, termed opportunistic CSMA, improves the throughput of the low-priority users by as much as 300% compared to the current CSMA protocols in home PLC networks.

This paper studies linear transmit filter design for weighted sum-rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose a low complexity algorithm for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithm achieves high performance with few iterations.

This paper develops a optimal power-allocation strategy for the general multi-hop cooperative relay systems. The systems allow a different number of hops for different paths and different destinations for different paths. When the orthogonality of channels is guaranteed for each hop, and when the systems want to minimize the total system power to transmit the data to the destinations, it is shown that the optimal power-allocation satisfies the following condition: the summation of all water-levels of a path should be the same as those of others.

In the OFDMA downlink, obtaining channel state information (CSI) from users is necessary for the base station (BS) to optimize network performance by intelligently allocating resources and scheduling mobile stations (MS). However, the overhead of obtaining CSI is a large burden and therefore, schemes to reduce CSI are necessary for a realizable system. By considering a MS's coherence time Deltatcohand coherence bandwidth Bcoh, and exploiting this redundancy in the MS's CSI, the amount of feedback can be tailored to the specific user's profile and greatly decreased. Typically, reducing feedback results in more uncertainty in CSIT and performance degradation. However, in the proposed scheme, the CSIT's deviation from the true channel state is bounded, and thus can provide robust scheduling. Specifically, two BS schemes are suggested that either fix the average BER or the average outage probability regardless of user mobility or delay spread.

This paper investigates orthogonal frequency-division multiple-access (OFDMA) resource-allocation schemes for two-hop relays in a home powerline communication (PLC) network. Unlike wireless channels, which can have noticeable path loss and shadow effects to bring a substantial relay gain, the powerline channel usually observes a quality of the relay channel on par with the direct link so that simple fixed relay configurations often lose performance instead of gaining any. Besides, the quasi-cyclostationary powerline channel benefits little from diversity combining, a scheme often found in cooperative wireless relay protocols to obtain performance improvements on fast fading channels. To address these special and challenging features of the powerline channel, home-PLC relay protocols that jointly allocate subchannels and power to the source and relay nodes are proposed. Simulation results show that significant improvements of data rates can be achieved by jointly optimizing the subchannel and power allocation of home-PLC relay networks.

This paper studies a new decentralized resource allocation strategy, named iterative spectrum shaping (ISS), for a multi-carrier-based spectrum sharing system, where two co-existing users independently and sequentially update transmit power allocation over parallel subcarriers to maximize their individual transmit rates. Unlike the conventional iterative water-filling (IWF) algorithm that applies the single-user detection (SD) at each user receiver by treating the interference from the other user as additional noise, the proposed ISS algorithm opportunistically applies multiuser detection techniques to decode both the desired user and interference user messages, thus termed as opportunistic multiuser detection (OMD). For OMD, this paper derives the optimal user power and rate allocation strategy at each iteration of transmit adaptation. Numerical examples show that the proposed ISS deploying OMD is able to achieve substantial throughput gains over the conventional IWF deploying SD in decentralized spectrum sharing systems.

This paper presents a user-cooperation scheme with limited feedback in a broadcast channel. The proposed scheme allows mobile stations to forward received messages over finite-capacity orthogonal channels, known as conferencing. In addition, the proposed scheme jointly uses the feedback from mobile stations to mitigate multi-user interference by choosing the best beamforming vectors from a finite-sized codebook. As a result, a multi-user broadcast channel is located between a point-to-point multiple-input multiple-output channel and a multi-user multiple-input single-output channel. The former is where full coherent cooperation among receiver antennas is allowed, and the latter is where no cooperation among mobile stations is assumed. Then, this paper analyzes the relation between the amounts of user-cooperation and limited feedback, and shows a trade-off between the relative use of each. Simulation results verify the advantage of cooperation and feedback as complementary technologies in wireless cellular networks.

This paper proposes a novel bit-level combining scheme based on Dempster-Shafer (D-S) evidence theory, termed DS combining, for multiple-input multiple-output (MIMO) systems with hybrid-automatic-retransmission-request (HARQ) mechanism. The DS combining is assisted by the proposed DS detection for performance improvement. The focal-element-set (FES) characterizes the uncertainty contained in the decision statistics, and the corresponding basic-probability-assignment (BPA) of FES is the likelihood measure. The uncertainty can be counteracted by DS detection and further counteracted by DS combining, so more reliable decisions are achieved. Simulation results verify that the proposed combining scheme significantly outperforms its log-likelihood-ratio (LLR) combining counterpart with only moderate complexity increases.

Abstract-This article describes a minimax regret approach to robust beamforming with an ellipsoidal uncertainty model for a steering vector, in which the objective is to minimize the worstcase regret over the uncertainty set, where 'worst' means largest. This problem can be solved efficiently by using an iterative method which uses an alternating sequence of optimization and worst-case analysis steps. Each of the two steps amounts to solving a convex optimization problem. The method typically converges to a solution within 5 iterations. The minimax regret beamforming is illustrated with numerical examples in planar random array antennas. The numerical results show that the minimax regret approach is less pessimistic (less conservative) and provides more robust performance than the worst-case SINR maximization (maximin) approach, where 'worst' means smallest.

It has recently been reported that the unconditional maximum likelihood (UML) symbol-timing estimation is asymptotically equivalent to the square-law nonlinearity (SLN) on an additive white Gaussian noise (AWGN) channel. By introducing a whitened matched filter (WMF), we propose an extended SLN and prove the asymptotical equivalence between the UML and the extended SLN on an additive colored Gaussian noise. Simulation results show the same behavior asymptotically when a mixture of an AWGN and a flicker noise is adopted as a noise source.

This paper presents the use of the common-mode signal in digital-subscriber-line (DSL) transmission. The DSL binder's metallic sheath is used as a common reference to obtain reliable channels for the common-mode signals. The direct and crosstalk channels for the common-mode signal are obtained using multi-conductor transmission line theory, and the data-rate improvement by exploiting these extra dimensions is presented. The lines in the binder are coordinated to cancel differential-mode crosstalk and also to avoid interference caused by radiation from the common-mode within the binder. The high level of common-mode noise is countered by exploiting the correlation between the differential- and common-mode noises. Numerical results based on the derived models show data-rate improvements of up to 100% compared to using only differential-mode transmission.

The throughput of an IEEE 802.11 network decreases as the number of users increases because of the increased collision probability. To improve the throughput in the presence of a large population, this paper presents an opportunistic carrier-sense multiple-acces/collision-avoidance (CSMA/CA) scheme that exploits multi-user diversity while minimally modifying the IEEE 802.11 medium-access control. This method prioritizes those users having high signal-to-noise-ratio by granting earlier access to these users, thus improving the throughput. This prioritization, however, can cause repeated collisions of same users, which is similar to so-called head-of-line (HOL) blocking. To reduce the probability of the occurrence of the HOL blocking, a simple randomization is proposed. A probabilistic analysis shows that this scheme significantly reduces the HOL blocking probability. The simulation results show that the proposed method improves the throughput by as much as 100%, while achieving long-term fairness among users with different channel conditions.

This paper proposes a method that reduces transmit-power consumption of carrier-sense multiple-access (CSMA) networks by utilizing multiuser diversity and power control. Using this method, a terminal sends a packet at a slot if the terminal's signal-to-noise ratio (SNR) is above the threshold associated with the slot. Since the threshold value decreases as time advances, this method will make the user with the largest SNR access the shared channel; thus, a packet can be transmitted with less transmit power. The analysis under the infinite-user model shows that, as traffic load grows, the expected sum-power of the conventional CSMA network increases whereas that of the proposed method decreases.

Multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ) promises high throughput with high reliability. However, combining-scheme design for such systems faces challenges, the presence of interference and the existence of multiple signal-to-interference-and-noise power ratios (SINRs). To overcome these challenges, this paper suggests to design combining schemes with the objective of directly optimizing the log-likelihood ratio (LLR) values. Using this approach, this paper proposes several combining schemes and then analyzes them based on three key design factors: decoding performance, scalability, and memory requirement. Computer simulations under the IEEE 802.16e standard settings show the performances of the proposed combining schemes, which align well with the analysis. Based on the analyses and the simulation results, this paper suggests preferable combining schemes respectively for MIMO systems with HARQ-chase combining (HARQ-CC) and HARQ-incremental redundancy (HARQ-IR).

This paper proposes a new combining scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). The proposed combining scheme is proved to have the optimal decoding performance. Furthermore, the proposed combining scheme is shown to have low memory requirement and reduced complexity compared to other optimal combining schemes. Simulation results under IEEE 802.16e setting with UMTS channel models verify that the proposed combining scheme achieves the optimal decoding performance and performs much better than other suboptimal combining schemes.

A group random access-based feedback scheme is proposed for multiuser diversity systems, where users are divided into several feedback groups according to their measured channel states. Different random access probabilities and number of feedback minislots are assigned to each feedback group. Each user competes to send a feedback message through random access if its scheduling metric exceeds a threshold. The base station jointly controls the random access probabilities, the thresholds, and the number of feedback minislots to adjust the feedback load. The proposed feedback scheme shows a good system capacity with limited feedback resources regardless of the number of users.

Power-saving benefits of Dynamic Spectrum Management (DSM) result from its increased robustness to channel and noise changes, as in this paper. A proposed intermittent noise model enables evaluation of the performance of DSM algorithms. Polite Level-1 DSM algorithm consumes much less power than non-polite DSL management algorithms in the presence of intermittent noise. Secondly, a proposed robust level- 2 DSM algorithm compares favorably with methods that change the PSDMASK only upon modem initialization or retraining. The proposed robust level-2 DSM algorithm significantly reduces power consumption. This DSM reduction of DSL transmit power can be even more significant when considering the additional loss of robustness and stability of non-DSM methods.

This paper defines a new metric: a relay gain that measures the performance gain of users using relaying channels at distance s from a base station. The paper derives the closed form of the relay gain for urban macro-cells and rural areas, and shows that the closed form provides much information about how to maximize the performance gain of relay systems. Further, this paper investigates the fairness improvement of relay systems based on the relay gain, and confirms the superiority of relay systems over systems without relaying. Simulation results confirm that the relay gain metric predicts the performance of real relay systems accurately.

This paper reformulates the multi-user OFDMA resource allocation problems in broadcast and multiple-access channels by defining an equivalent interference channel. The resulting problems are then solved by employing low-complexity algorithms for spectrum optimization in the interference channel. The re-formulation averts the high-complexity integer programming problem that otherwise results from an OFDMA system that allocates each user to separate subchannels. Simulation results indicate that the proposed algorithm achieves near-optimal performance and is suitable for PLC resource allocation applications.

This paper investigates the unequal allocation of margin across tones in a multicarrier communication system. Using empirical statistics of the channel signal-to-noise-ratio variation, an algorithm is developed for modems to optimally distribute the available margin across tones instead of allocating equal per-tone margins. Such unequal per-tone margin allocation results in better stability of the line in terms of the outage probability especially when bit and energy adaptation mechanisms are not available or respond slowly to changes in the channel or noise spectrum.

This paper presents a discrete bit-loading algorithm for multi-user multicarrier systems with application to spectrum balancing in digital-subscriber-lines. The algorithm can be implemented in a distributed manner using limited information that is sent to modems by a spectrum management center (SMC). The SMC first classifies users as strong and weak. Strong users then form a rate-penalty table that is used along with the Levin-Campello bit-loading algorithm to limit the interference to weak users. Simulation results show that the proposed algorithm can achieve near-optimal performance. Moreover, the structure of the algorithm enables easy implementation of polite bit and gain adaptation procedures without the need for executing the entire bit-loading algorithm again.

This paper investigates the optimization of margins in digital subscriber lines employing level-2 dynamic spectrum management, where lines are jointly optimized with an emphasis on their stability, throughput-guarantee, and politeness. A new definition of noise margin and the concept of probability of outage are introduced, which allow for an easier formulation of the problems of joint margin and spectra optimization of the lines taking into account their stabilities. The solutions to the highly-coupled optimization problems are simplified using noise margins instead of signal-to-interference-and-noise-ratio margins. The presented algorithms provide up to 100% improvements in the data-rates or a reduction in the probability of outage by an order of magnitude, thus improving the stability of the lines at high data rates.

This paper investigates the optimization of margins in a digital-subscriber-line (DSL) system employing level-1 dynamic spectrum management. A central spectrum management center determines the empirical statistics of the noise variance of each DSL line using long-term observations and optimizes the margin allocation using the statistics. Compared to current systems that allocate ad-hoc margin values, the presented algorithms improve the line's stability, throughput-guarantee, and politeness to other lines in the binder.

This paper proposes to use flexible adaptive- modulation-and-coding (AMC) tables in a wireless network. To support the flexibility of AMC tables, a low-complexity AMC table optimization algorithm is also proposed. The proposed algorithm iteratively optimizes the switching levels of an AMC table according to channel environments, and has fast convergence speed. Computer simulation results show that the proposed algorithm optimizes AMC tables according to different cell characteristics, and that using flexible AMC tables for a wireless network achieves near-optimal average spectral efficiency even with a small feedback load.

This paper studies the downlink Orthogonal Frequency Division Multiplexing (OFDM) setup with a single Base Station (BS) serving many users. The BS is assumed to have limited Channel State Information (CSI) obtained by explicit feedback from the downlink users. Given that the feedback rate and the coherence time of the channel are fixed, the question asked in this paper is: how to allocate the feedback resources optimally? Specifically, what is the optimal number of tones grouped as a subchannel, the number of users that feedback for any subchannel and the number of bits used for quantization of CSI? Analytical expressions are derived for the i.i.d. Rayleigh fading case and it is shown that there is a definite hierarchy in the importance of the three design variables. Feedback resources are first allocated to create the maximum number of subchannels possible, then to allow for more users to feedback for any subchannel and lastly to increase the precision of the channel value. Monte-Carlo simulations are performed to verify the accuracy of the derived analytical expressions.

The high peak-to-average-power ratio (PAR) of orthogonal frequency division multiplexing (OFDM) transmission systems significantly reduces the power efficiency or performance of such systems, and many techniques have been proposed to deal with this problem. Recently, the active constellation extension (ACE) algorithm has received much attention, where the main idea is to reduce the PAR by introducing a perturbation of the transmit constellation that does not reduce the constellationpsilas minimum-distance. In this paper, a different approach is taken where the constellationpsilas minimum-distance is reduced to lower the PAR but the constellation perturbation is done in an optimal way to improve the system performance. The problem of optimally trading off PAR reduction and constellation distortion is shown to be a convex optimization problem that could be solved very efficiently. The proposed idea has no data-rate loss and does not require the transmission of side-information.

This paper considers a sum-rate-maximizing power allocation for the Gaussian cognitive multiple-access channel (MAC), where primary users and secondary users may communicate under mutual interference. Formulation of the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple method to find a solution using semidefinite relaxation (SDR). Numerical examples for the comparison illustrate a tradeoff between the maximum sum-rate and computational complexity.

This paper considers the subchannel-allocation problem to maximize the sum-rate in orthogonal frequency- division multiple-access (OFDMA) regenerative relaying downlink systems with a total power constraint. Based on the Lagrange dual decomposition and the optimal condition of the problem, this paper proposes three heuristic algorithms: an extended modified inverse subchannel signal-to-noise ratio algorithm, a bit accumulation algorithm, and a bit ratio algorithm. Simulation results show that relaying systems with proposed algorithms outperform optimally resource-allocated OFDMA systems without relay stations by almost 100% ~ 270% depending on the system power, which confirms that subchannel-allocation is a key factor in obtaining a huge performance gain.

In a wireless multi-user system using multiple antennas, full multiplexing gain can be achieved through perfect channel state information (CSI) at the base station (BS). However, because of the limitations on the feedback rate and of standard requirements, such as the 3GPP, it is difficult to obtain perfect CSI, or even partial CSI with the extremely large number of feedback bits needed at the region of high signal-to-noise ratios (SNR) in practical systems. Instead of a feedback channel resource, this paper considers another resource for the system, a cooperation channel, which can be used by users to participate in cooperation in a broadcast fading channel. The cooperation among users in a multi-user system has the effect of transforming it into a cooperative point-to-point MIMO system. This paper analyzes the cooperation channel gain and the mobile power used in a cooperation channel to maintain a constant rate gap against the zero-forcing beamforming scheme with full CSI at the BS. In addition, the performance results of this proposed cooperation strategy are provided by computer simulations.

Multicarrier modulation partitions an inter-symbol interference channel into multiple narrowband channels if the length of the cyclic prefix is longer than the channel impulse response. Otherwise, interference from the current and previous multicarrier symbols causes significant distortion at the receiver. This paper expands on the approach introduced in (K.-W. Cheong et al., 1998), where a transmitter based precoder suppresses insufficient-cyclic-prefix distortion. In this paper, the problem of finding an approximate optimal linear precoder to maximize the data-rate in the presence of inter-carrier interference (ICI) due to insufficient-cyclic-prefix distortion is formulated and shown to be a convex optimization problem. The paper further explores low-complexity transmitter equalization and joint transmitter-receiver processing schemes. The proposed methods result in a novel low-complexity insufficient-cyclic-prefix distortion reduction algorithms to maximize the data-rate.

Optimal tone allocation in downlink OFDMA networks is a non-convex NP-hard problem that requires extensive feedback for channel information. In this paper, two constant complexity limited-feedback algorithms are proposed to achieve near-optimal performance. First, using opportunistic feedback, the proposed schemes are shown to reduce feedback overhead by requiring only users likely to be allocated resources to feedback. There are differences between the two proposed schemes for implementation of the feedback protocol. One scheme requires less feedback but is contention-based, while the other scheme is sequential and thus avoids possible collisions leading to slightly higher performance, but needs more feedback. Second, complexity is reduced for resource allocation by solving the optimization problem in a distributed manner, rather than centrally at the base station. As shown both analytically and through numerical results, these distributed algorithms reduce the required feedback overhead significantly, and achieve constant computational complexity with little performance loss compared to the optimal solution.

This paper presents the multiple-input multiple-output (MIMO) channel capacity over the Nakagami-m fading channel. The joint eigenvalue density function of W = HH' where H is the channel matrix, is derived in closed form for H (2 times 2) and any integer values of m, as well as for H (2 times 3) with to = 2 and to = 3. The marginal eigenvalue distribution of W is also derived in a closed-form expression. All the results are validated by numerical Monte Carlo simulations and are in excellent agreement.

This paper investigates the effect of inaccurate SINR estimation on the performance of multi-user scheduling in downlink orthogonal frequency division multiplexing (OFDM) systems. Considering path loss, time and frequency selectivity of the channel, the error statistics of SINR estimation is analyzed. Then, the effect of SINR inaccuracy is evaluated in respect to system throughput and fairness when each user has different error statistics according to channel environments.

This paper studies linear transmit filter design for Weighted Sum-Rate (WSR) maximization in the Multiple Input Multiple Output Broadcast Channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose two low complexity algorithms for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithms achieve high performance with few iterations.

One of the main drawbacks of orthogonal frequency division multiplexing (OFDM) is the high peak-to-average power ratio (PAPR) of the OFDM signal. In this paper, we propose the use of hexagonal constellation for PAPR reduction of an OFDM signal. Because hexagonal constellation is the densest packing of regularly spaced points in two dimensions, we can have more signal points in a given area with hexagonal constellation than with quadrature amplitude modulation (QAM) constellation. We can exploit these extra degrees of freedom provided by the hexagonal constellation for PAPR reduction of an OFDM signal. We will apply the proposed technique to eliminate data rate loss due to the side information in partial transmit sequence (PTS) technique and selected mapping (SLM) technique.

A user-identity feedback method is proposed to achieve multi-user diversity in broadcast channels. This method associates the feedback slots with pre-determined thresholds that diminish with time, and allows feedback from those users whose channel states exceed the threshold assigned to the current slot. Since the threshold can approximate the channel state, this method requires only user-identity feedback. In Rayleigh fading channels, this method is mathematically shown to achieve the sum-rate capacity asymptotically with a large number of users, while requiring only a few feedback slots and little transmission power.

In slow-fading uplink channels, carrier-sense multiple-access (CSMA) has been a popular random-access method, although it can have increased the throughput by using channel state information (CSI) acquired from a downlink training signal and electromagnetic reciprocity. To improve the throughput by using the CSI, this paper presents a random- access scheme that achieves multi-user diversity, called opportunistic p-persistent CSMA (OpCSMA). A user using OpCSMA sends a packet in a slot if the user's CSI exceeds the threshold assigned to the slot. The thresholds diminish with time to prioritize users having good CSI, while being designed to maintain the same persistency as the conventional CSMA, thus enabling backward compatibility. OpCSMA is mathematically shown to significantly increase the throughput compared with conventional CSMA, when the infinite-user model is used to model the variation of the number of users. As the expected number of users increases, the expected sum-rate of the OpCSMA approaches that using a centralized scheduler, which is the theoretical upper bound.

To maximize the spectral efficiency for a time- varying downlink channel with multiple users, the scheduling order of the users needs to be optimized. The scheduling problem naturally is a combinatorial optimization problem with high complexity, which exponentially increases with the number of users. This paper proposes several low-complexity scheduling algorithms. Computer simulation results show that the proposed algorithms approach optimal performance.

This paper presents an opportunistic feedback (OF) protocol that reduces the amount of channel-state-information (CSI) feedback for the OFDMA downlink system. The OF protocol associates a channel value instead of a user to each feedback slot. The users access the slots opportunistically based on their channel state measurement for each tone. This allows the base station (BS) to deduce the channel state from the slot index without explicit channel-state feedback, and also solve the resource allocation problem on the fly. The OF protocol is designed to support heterogeneous traffic, where users with deadline-sensitive (DS) applications are prioritized over best- effort (BE) users. The proposed OF protocol (a) requires finite number of feedback slots upper bounded by a small number, (b) is fully distributed, and (c) provides QoS to the DS applications.

We consider optimal allocation of resources to users in a downlink OFDMA system to support heterogeneous applications consisting of both deadline-sensitive (DS) and best-effort (BE) data in a cross-layer manner. Given the user queue-states and long-term channel statistics, the proposed persistent scheduling algorithm allocates the minimum resources to 'just' meet the deadlines for DS packets (QoS guarantee). The remaining resources are optimally split between the users for their BE data to maximize sum-rate, minimize buffer holding cost or any general utility function. We formulate the resource allocation problem as a single geometric program (GP) that can be solved using standard convex optimization software tools. Simulation results are presented to compare the performance of different objectives for the BE applications in presence of DS traffic.

This paper presents a practical algorithm for antenna selection in multiple-input multiple-output wireless communication systems employing space-time block codes (STBC). It first shows that maximizing the channel Frobenius norm helps maximize the mutual information for both orthogonal STBC and quasi-orthogonal STBC. However, the computational complexity for finding the optimal antenna subset grows exponentially with the number of antennas. This paper identifies that the channel Frobenius norm maximization problem can be formulated as a quadratically constrained quadratic programming (QCQP) problem. Then, despite the fact that the problem is non-convex, a semidefinite relaxation of QCQP enables the problem to be solved approximately by semidefinite programming in polynomial time. Simulation results indicate that the loss of semidefinite relaxation is negligible. It is also shown that although the combination of STBC and antenna selection is not always beneficial, it is a robust transmission strategy in the high SNR regime when only imperfect channel information is available.

This paper proposes a resource-allocation technique for Gaussian multiple-input multiple-output, orthogonal- frequency-division-multiplexing (MIMO-OFDM) multiple-access channel (MAC). Zero-forcing generalized decision-feedback equalizers (ZF-GDFE) are employed at the receiver to cancel completely the interferences produced by all the other users, while a novel matrix decomposition method based on the generalized channel singular-value-decomposition (SVD) is used to find the precoding matrices at each user's transmitter. The achievable rate region is obtained by solving a series of weighted sum-rate maximization problems, and the associated users' power distributions are efficiently found by a Lagrange dual- decomposition method along with a per-tone-based exhaustive search of decoding orders among users. The complexity can be further reduced by replacing the exhaustive search with a greedy algorithm. Simulation results show that the achievable rate region obtained by the greedy algorithm is very close to that achieved by the exhaustive search. Therefore, with a significant computational complexity reduction over the canonical minimum-mean- squared-error (MMSE) -based GDFE, the proposed algorithm provides an ideal scheme for practical systems such as uplink wireless MIMO-OFDM systems and upstream vectored digital subscriber lines (DSL).

This paper presents the MIMO channel capacity over the Nakagami-m fading channel. The joint eigenvalue density function of W = HHdagger, where H is the channel matrix, is derived in a closed form in the 2 times 2 case and for integer values of m, as well as for m rarr infin. The marginal eigenvalue distribution of W is also derived in closed form solution. For the more general r times t case, an asymptotic formulation is presented and is shown to be close to simulations, even for a small number of antennas. All the results are validated by numerical Monte Carlo simulations and are in excellent agreement.

The throughput of an IEEE 802.11 network decreases as the number of users increases because of the increased collision probability. To improve the throughput with a large population, this paper presents an opportunistic CSMA/CA scheme that exploits multi-user diversity, while maintaining backward compatibility with the IEEE 802.11 medium access control. This method prioritizes those users having high signal-to-noise-ratio by granting earlier access to these users. A simple randomization is proposed to prevent the repeated collisions of same users caused by this prioritization. The simulation results show that the proposed method improves the throughput by as much as 100% with a large population.

This paper proposes a new receiver scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). The proposed scheme is proved to have the optimal decoding performance in a sense that all the relevant information is fully used for decoding. Furthermore, it is shown that the proposed scheme has reduced complexity compared to the other optimal receiver scheme. Simulation results under IEEE 802.16e setting with UMTS channel model verify that the proposed receiver scheme achieves the same decoding performance with the other optimal receiver scheme and performs better than other suboptimal receiver schemes.

This paper proposes resource-allocation algorithms to maximize the sum-rate in orthogonal frequency-division multiple-access multi-hop relaying downlink systems. With advance subchannel allocation to users and relay stations, Lagrange dual-decomposition solves the power-allocation problem. This paper shows the optimal solution to be a modified water-filling algorithm, where an inner-outer bisection method determines the optimal water-levels. Further, proposed heuristic resource- allocation algorithms rely on the Karush-Kuhn-Tucker conditions. Simulation results show that the multi-hop OFDMA relaying systems outperform the conventional OFDMA systems by more than 30% with use of the proposed resource-allocation algorithms.

This paper considers energy minimization for a fast-fading random-access network, where each user sends a single fixed-length packet by selecting a single time-slot within a strict delay-limit. The proposed algorithms assume that each user causally knows its channel state information from electromagnetic reciprocity. With the channel distribution known to all users, the proposed dynamic-programming solution provides an optimal scheduler that minimizes the sum of energy used to transmit a packet and outage cost incurred by a packet drop. Without the knowledge of the channel distribution, a heuristic scheduler is additionally proposed, which learns channel statistics by observing initial time slots.

This paper characterizes the delay region that is quite useful for multi-user packet scheduling. In a quasi-static channel, the optimal delay region is defined as every set of total delay vectors achieved by some scheduling policies when there are no further packet arrivals. Each user's total delay is equivalent to the amount of time until that user's queue backlog is cleared. The optimal delay region shows the fundamental limit on each user's achievable queueing delay and describes the trade-off among the users in terms of queueing delay when different scheduling policies are applied. In addition, the concept of the delay region is shown to be extendable to each packet's average delay as well as total delay.

Multicarrier modulation partitions an inter-symbol interference channel into multiple narrowband channels if the length of a cyclic prefix is longer than the channel impulse response. Otherwise, interference from the current and previous symbols cause significant distortion at the receiver. This paper proposes a low complexity approach to efficiently suppress this distortion by reserving a few tones. While the interference from the previous symbol is canceled by the receiver using the already detected symbol, the interference from the current symbol is suppressed at the transmitter by appropriately correlating transmit data tones and the reserved tones. This correlation and tone reservation cause a small data-rate loss depending on the severity of the channel conditions but overall the proposed scheme will lead to an improved performance.

In a slowly time-varying fading broadcast channel, a proposed randomized scheduler achieves multi-user diversity gain while reducing the amount of feedback. The scheduler requests feedback of signal-to-noise ratios (SNR) from a random subset of users in conjunction with the previously scheduled user, and then selects the user with the largest SNR. With temporal correlation, this scheduler achieves near optimal sum-rate even with feedback from a small subset of users, which considerably reduces the amount of feedback.

This paper proposes the opportunistic power allocation (OPA) scheme for random beamforming with a limited feedback rate. Without the channel state information, the proposed scheme allocates different amounts of power to different beams. Various low-complexity search algorithms for the proposed OPA scheme are also proposed to find the optimal power allocation that maximizes the sum rate. Computer simulations show that the proposed OPA scheme significantly improves the sum rate, and the optimal power allocation is found with low complexity. In addition, it is shown that the number of beams should increase as the SNR increases in order to maximize the sum rate.

To increase the achievable sum rate of downlink MIMO (Multiple Input Multiple Output) systems, the cooperation among Base Stations (BS) is investigated in a slow fading channel. Three levels of BS coordination are considered: full coordination, partial coordination, and no coordination. This paper assumes that the downlink MIMO channel state information (CSI) is sent to the corresponding BS through a feedback link with some delay. In a fully coordinated system, the CSI at each BS needs to be collected at the central coordinator, and this process may result in significant additional delay. In this paper, the achievable throughput of each coordination level is evaluated and compared including the effects of the delay in CSI. A quasi-static fading is considered where the channel is static within one codeword, but it gradually changes over time based on the well-known Jake's model. Also, dirty paper coding (DPC) is applied, which is a transmission method shown to achieve the sum capacity of MIMO broadcast channels (BC). The results show that under certain delay conditions, the partially-coordinated system outperforms the fully-coordinated system. In addition, this paper presents a new partial-coordination method that provides higher throughput than the conventional partial-coordinated system.

This paper proposes an efficient algorithm that produces near-optimal discrete bit-loading for a Gaussian interference channel that models a DSL network. It first takes a continuous bit-loading initialization, and then rounds one user's bits in each tone independently, with rounding direction determined by evaluating a weighted sum rate objective function. After adjusting all the tones of a user, that user's power constraint is met by a power tightening procedure; then, the algorithm moves to the next user. Convergence of the proposed algorithm is proved. This algorithm can be made distributed by only allowing rounding DOWN the bits, and it can be also applied to Gaussian Multiple Access Channel (MAC) and Gaussian Broadcast Channel (BC) with slight modifications.

This paper considers a multiple-access channel with two state components, where the first sender knows only the first state component, the second sender knows only the second component, and the receiver knows both components. The notion of adaptive-rate capacity is introduced to characterize the set of achievable rates when the state is fixed in each transmission block but can vary between blocks. Single-letter characterizations of the adaptive-rate capacity region for the discrete-memoryless and the Gaussian models are established. The expected adaptive sum-rate capacity is compared to the ergodic sum-rate capacities when the senders have complete and partial state information, and to the sum-rate capacity of the compound MAC. This comparison shows that the adaptive sum-rate capacity can be close to the ergodic capacity and much higher than the sum-rate capacity of the compound MAC.

To maximize spectral efficiency for multiple users with time-varying broadcast channel, the scheduling order of the users needs to be optimized. The scheduling problem naturally is a combinatorial optimization problem with high complexity, which exponentially increases with the number of users. In this paper, several scheduling algorithms that have small complexities are proposed. Computer simulation results show that the proposed algorithms achieve performance close to the optimal one.

This paper proposes and analyzes receiver schemes for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). It is shown by means of analysis as well as computer simulations that the proposed receiver schemes have optimal decoding performance in the sense that all the relevant information is fully used. Also complexity-wise, the proposed receiver schemes are found beneficial when designing MIMO systems, because the same decoding architecture can be re-used regardless of the number of retransmissions.

This paper establishes necessary and sufficient conditions for reliable transmission of a source over a relay channel when source side information is available non-causally (a) only at the receiver, (b) only at the relay, or (c) at both the relay and the receiver. For the cases of side information only at the receiver and at both the relay and the receiver, we establish tight necessary and sufficient conditions that apply to any relay channel and show that source-channel separation is optimal. When side information is available only at the relay, we establish a necessary condition for reliable transmission and show that it is tight for the class of degraded relay channels and that source-channel separation is optimal in this case.

This paper addresses cross-layer resource allocation in quasi-static fading multiple access channels (MAC) with no channel state information at the transmitters (CSIT). Under the cross-layer approach without CSIT, the power and rate are determined based on an outage rate region as well as the current queue state information (QSI). For heterogeneous quality-of- service (QoS) requirements, an individual outage rate region results in better performance compared to the common outage rate region that is widely considered in the literature. This paper first reviews the recent notion of an individual outage rate region for the quasi-static fading MAC without CSIT. Individual outage rate regions are then used in two major types of scheduling policies: maximum weight matching scheduling (MWMS) and queue proportional scheduling (QPS). It is shown that MWMS and similar techniques based on weighted-sum-rate maximization require exponential complexity in the number of users because of the non-convex nature of the relevant optimization problems. By contrast, QPS can be very efficiently solved by using a successive feasibility check. Stochastic simulations show that compared to MWMS and the common outage rate region, significant throughput increase and delay reduction are possible by using the QPS scheduling policy with the individual outage rate region.

This paper considers a wireless uplink, where some users have deadline-sensitive (DS) traffic and others have best- effort (BE) traffic. The objective is to meet the deadlines for DS packets a fixed percent of time (QoS guarantee), at the same time minimizing the sum-power used for transmission in a distributed manner without feedback fromallusers to the base station (BS). Given each user's channel state and rate requirement, the optimal user ordering that minimizes sum-power is shown to be independent of the rate requirements and depends solely on the channel conditions. Based on this, using a limited amount of feedback, the proposed opportunistic feedback (OF) protocol guarantees QoS to DS data and minimizes sum-power. Numerical results show that (i) the OF protocol provides deadline-meeting guarantees and (ii) minimizes sum-power with a greatly reduced feedback overhead as compared to that of a central scheduler.

We consider a MIMO broadcast channel (BC) with large M and K, where M is the number of transmit antennas and K is the number of single-antenna users; and propose a scalable feedback protocol that achieves the sum-capacity with limited feedback of channel state information (CSI). In our earlier work, we showed that if feedback time slots correspond to channel gains and not to users, the sum-capacity M log log K can be achieved with feedback resources growing only as M log K, unlike linearly as M K for conventional schemes. In this work, we show that feedback requirement can further be reduced by half or more, while still achieving the sum-capacity. A scalable feedback (SF) protocol using random beamforming (RBF) is proposed, which a) requires finite number of feedback slots upper bounded by a constant, b) is fully distributed, c) needs finite transmission energy during feedback and d) achieves the sum-capacity. Numerical results show that feedback load is substantially reduced as compared to conventional schemes, as well as our own previously proposed SF scheme.

This paper presents an opportunistic feedback (OF) protocol that achieves the asymptotic sum-capacity of the fading broadcast channel (BC) with a limited amount of feedback. The OF protocol associates a channel value instead of a user to each feedback slot. The users access the slots opportunistically based on their channel state measurement. This allows the base-station to deduce the channel state from the slot index without explicit channel-state feedback. This protocol is then extended to the MIMO BC by using zero-forcing beamforming and random beamforming. The OF protocol is analytically shown to (a) require finite number of feedback slots upper bounded by a small number, (b) be fully distributed, (c) need minimal transmission energy during feedback and (d) asymptotically achieve the sum-capacity of the MIMO BC. Comparison with other opportunistic feedback schemes shows that the proposed scheme has substantially larger sum-rate with a lower feedback overhead.

This paper studies optimal allocation of resources to users in a fading broadcast channel (BC) to support heterogeneous traffic. Resource allocation is done in a cross-layer manner for both deadline-sensitive (DS) and best-effort (BE) data to provide users guaranteed Quality of Service (QoS). Given the user queue-states, the proposed algorithm allocates the minimum resource to 'just' meet the deadlines for DS packets a fixed % of time. The remaining resources are then optimally split between the users for their BE data to maximize sum-rate, minimize buffer holding cost or any general utility function. The resource allocation problem is formulated as a linear program (LP) followed by a geometric program (GP) which can be solved very efficiently. Simulation results are presented for Poisson packet arrivals and exponentially distributed packet lengths on a Rayleigh fading channel for both the DS and BE traffic.

This paper presents power-efficient transmission schemes for the multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) block-fading channel under the assumption that the channel during each fading block is known perfectly at the receiver, but is unavailable at the transmitter. Based on the well-known vertical Bell Labs layered space-time (V-BLAST) architecture that employs independent encoding for each transmit antenna and successive decoding at the receiver, this paper presents a per-antenna-based power and rate feedback scheme, termed the "closed-loop" V- BLAST, for which the receiver jointly optimizes the power and rate assignments for all transmit antennas, and then returns them to the transmitter via a low-rate feedback channel. The power and rate optimization minimizes the total transmit power for support of an aggregate transmission rate during each fading block. Convex optimization techniques are used to design efficient algorithms for optimal power and rate allocation. The proposed algorithms are also modified to incorporate practical system constraints on feedback complexity and on modulation and coding. Furthermore, this paper shows that the per-antenna-based power and rate control can be readily modified to combine with the conventional linear MIMO transmit preceding technique as an efficient and capacity-approaching partial-channel-feedback scheme. Simulation results show that the closed-loop V-BLAST is able to approach closely the MIMO-OFDM channel capacity assuming availability of perfect channel knowledge at both the transmitter and the receiver.

This paper presents the capacity region of frequency-selective Gaussian interference channels under the condition of strong interference, assuming an average power constraint per user. First, a frequency-selective Gaussian interference channel is modeled as a set of independent parallel memoryless Gaussian interference channels. Using nonfrequency selective results, the capacity region of frequency-selective Gaussian interference channels under strong interference is expressed mathematically. Exploiting structures inherent in the problem, a dual problem is constructed for each independent memoryless channel, in which both mathematical and numerical analysis are performed. Furthermore, three suboptimal methods are compared to the capacity-achieving coding and power allocation scheme. Iterative waterfilling, a suboptimal scheme, provides close-to-optimum performance and has a distributed coding and power allocation scheme, which are attractive in practice.

This paper applies multiple-input multiple-output (MIMO) transmission methods to multiwire communication systems. Using channel matrices generated from a binder MIMO channel model, a performance assessment of digital subscriber line (DSL) technology based on MIMO transmission methods finds that symmetric data rates of more than 1 Gbps are achievable over four twisted pairs (category 3) for a 300 m range. Similar results are also obtained for a ldquoquadrdquo cable. To achieve this data rate, this paper proposes that the source and load be excited using common mode.

This paper introduces a multiple-input multiple-output channel model for the characterization of a binder of telephone lines. This model is based on multiconductor transmission line theory, and uses parameters that can be obtained from electromagnetic theory or measured data. The model generates frequency-dependent channel/binder transfer function matrices as a function of cable type, geometric line-spacing and twist-length parameters, and source--load configurations. The model allows the extraction of the magnitude and the phase of individual near end crosstalk, far end crosstalk, split-pair, and phantom transfer functions from the transfer function matrix of the binder. These individual crosstalk transfer functions are often found to be very sensitive to small imperfections in the binder. Examples of category 3 twisted pair American telephone lines and ldquoquadrdquo telephone cables are also presented.

In upstream vectored DSL transmission, the far-end crosstalk (FEXT) can be completely cancelled by using zero- forcing generalized decision-feedback equalizers (ZF-GDFE). When the spatially correlated alien crosstalk is present, the achievable data rates of DSL lines with ZF-GDFE depend on their decoding orders at each DMT tone. Given a weighted sum-rate maximization problem, the optimal orderings for all DMT tones can be found by the Lagrange dual decomposition method. However, the computational complexity of such approach grows with the factorial of the number of users, which makes the optimal search infeasible with a large number of vectored lines. This paper presents a modified greedy algorithm (MGA) that performs close to the optimal search of decoding orders. The complexity of MGA is only proportional to the cube of the number of users, which is the same as it of QR decomposition. With a significant reduction of complexity, MGA is a promising technique for practical DSL systems.

This paper investigates the effect of non-zero SNR margin and coding gap on the maximum sum rate and achievable rate region of the Gaussian multiple-access channel (MAC). Frequency-division multiple-access (FDMA) is shown to be the only sum-rate-maximizing scheme for a scalar Gaussian MAC when the margin/gap is not zero. Furthermore, successive decoding is shown to be strictly sub-optimal from a sum rate perspective. With fixed probability-of-error, single-user codes with finite gap are sufficient to achieve the maximum sum rate. The achievable rate region of the scalar Gaussian MAC with non-zero margin/gap is also characterized. Unlike the capacity region of a scalar MAC, the optimal achievable rate region with non-zero margin/gap is not a pentagon. Finally it is shown that when there is non-zero margin/gap, the optimality of the FDMA scheme can be generalized to a Gaussian MAC with inter-symbol interference (ISI).

In this paper, we consider single user throughput optimization problem for continuous flat fading channels of multiple-input multiple-output (MIMO) system. It is known that channel state information (CSI) at the transmitter enables significantly higher data rate for MIMO system compared to single-input single-output (SISO) system case. One of the widely used methods to obtain CSI is training based scheme. Putting more resource on training will give more accurate CSI, thus enabling higher data rate, but might decrease throughput because less resource is left for data transmission. The proposed mathematical framework enables us to find the optimal resource allocation between training period and data transmission period to achieve the highest throughput possible as a function of the number of antennas, Doppler spread, signal-to-noise ratio and computational complexity.

This paper introduces an algorithm for spectrum management for digital subscriber line (DSL) systems based on band preference. The proposed method influences the usage of spectrum through band preference factors that subtly modify the loading algorithm of DSL modems. Ad-hoc algorithms for computing such band preference factors are discussed. Simulation results in a practical ADSL environment show that the performance of the proposed method is better than that of Iterative Water-filling (IWF) [1] and is close to that of Optimal Spectrum Balancing (OSB) [2], even with a small number of control parameters.

For multi-user orthogonal frequency division multiplexing (OFDM) systems, efficient optimal rate and power allocation algorithms are presented via geometric programming (GP), a special form of convex optimization problem for which very efficient interior point methods exist. Both multiple access channel (MAC) and broadcast channel (BC) are considered and the following two resource allocation problems are of main interest: weighted sum-rate maximization (WSRmax) and weighted sum-power minimization (WSPmin). Utilizing degradedness of BC on each tone, WSRmax and WSPmin in the BC can be all formulated as GP. By using the duality relation between MAC and BC, it is shown that the above resource allocation problems in the MAC can be converted into GP problems as well. This GP perspective of multi-user OFDM resource allocation problems provides numerical efficiency as well as strong scalability for any additional constraints of GP form.

A class of optimal resource allocation problems in linear Gaussian multiple-access and broadcast channels (MAC and BC) can be summarized as weighted sum power minimization problem. In this paper an iterative water-filling algorithm is proposed to solve this problem efficiently. It is shown that by formulating an explicit rate expression for MAC, though non-convex of power spectral densities, the optimality conditions demonstrate a strong water-filling flavor. By iteratively solving the optimality conditions, whereas in each iteration a slightly modified single-user margin adaptive water-filling(MAWF) algorithm is applied to update the dual variable in a greedy manner, the power spectral density of each user converges to the optimal solution very fast. Simulations verify convergence and optimality. The problem in BC can be solved in its dual MAC.

In this paper, power-efficient transmission schemes are studied for MIMO-OFDM block-fading channels under the assumption that the channel is perfectly known at the receiver but unknown at the transmitter. Based on the well-known V-BLAST architecture that employs the horizontal encoding and the interference-nulling based successive decoding, this paper presents a closed-loop V-BLAST extension for MIMO-OFDM whereby the transmit rate and power as well as the assigned transmit antenna for each data stream at different OFDM tones are jointly optimized at the receiver and then fed back to the transmitter. Simulation results have confirmed that the closed- loop V-BLAST architecture is able to approach closely the MIMO-OFDM channel capacity attained through the eigenmode transmission that requires the complete channel feedback from the receiver to the transmitter.

In a Gaussian MIMO broadcast channel, serving more than one user at a time is generally more beneficial in terms of average sum-rate. Under partial channel state information (CSI) feedback constraints, however, serving only one user at a time can be a better multiple access method when the number of active users in the system is smaller than a certain threshold. This paper uses single user beam-forming (SUBF) to refer to the transmitting scheme that serves only one user at a time and multi-user beam-forming (MUBF) to refer to the scheme without such a constraint, i.e., a scheme that is allowed to serve more than one user at a time. It turns out that the aforementioned user threshold varies with other system parameters, especially, it increases as the number of transmit antennas increases. Monte Carlo simulations and a statistical analysis are provided to verify the results

For block fading channls, the delay-limited capacity measures the maximum constant-rate achievable over all fading blocks under the availability of complete channel knowledge at both the transmitter and the receiver. In this paper, we consider constant-rate transmissions over MIMO-OFDM block fading channels, under the condition that the channel is known at the receiver but unknown at the transmitter. We consider the well-known V-BLAST architecture that employs independently encoded data for each transmit antenna and present a closedloop extension of V-BLAST whereby the receiver jointly optimizes the rate and power assignments for each transmit antenna and then informs them to the transmitter via a low-rate feedback channel. Simulation results have confirmed that the closed-loop V-BLAST architecture can approach closely the channel delaylimited capacity if a capacity-achieving scalar code is used at each transmit antenna.

In this paper, Opportunistic p-persistent Carrier Sense Multiple Access (OpCSMA) is proposed to incorporate multiuser diversity into p-persistent CSMA. In the OpCSMA, each mobile terminal (MT) is assumed to have the knowledge of its channel state information (CSI). At each idle time slot, an MT sends a packet if the corresponding channel gain is above the threshold, which is determined such that the probability of accessing the medium is maintained to be p for any idle slots. Using the infinite user model, it is proved that the OpCSMA provides significant increase in the expected capacity compared to p-persistent CSMA. In addition, the expected capacity of the OpCSMA is shown to be proportional to ln G at low SNR where G is the offered load. Simulation results corroborate the above findings in slow fading channels.

This paper proposes a power efficient p-persistent Carrier Sense Multiple Access (CSMA) employing multiuser diversity, called Opportunistic p-persistent CSMA (OpCSMA). At each idle time slot, an MT sends a packet if the corresponding channel gain is above the threshold which is determined such that the probability of accessing the medium is p for any idle slots. Also, the transmit power is controlled to maintain the constant signal-to-noise-ratio when the channel gain exceeds the cut-off fade depth. The analysis under the infinite user model shows that as traffic load grows, the transmit power consumption of the conventional p-persistent CSMA increases, whereas that of the OpCSMA decreases owing to multiuser diversity effect. Simulation results corroborate these findings in slow fading channels.

This paper proposes to use candidate symbol table for the decoding of the first few substreams for spatially multiplexed system. In the new decoding algorithm, we generate candidate symbol table (CST) and do ordered successive interference cancellation (OSIC) for each candidates. At the end, Maximum Likelihood (ML) criteria is used to determine the optimum transmit symbol vector among the estimated candidates. Simulation result shows that the size of CST can be maintained to be small, even if the number of bits per symbol increases. Simulation results show that this algorithm gives us performance close to ML decoder, and outperforms maximum likelihood decision feedback equalizer (ML-DFE) and channel-based adaptive group detection based OSIC (AGD-OSIC).

Queue Proportional Scheduling (QPS) assigns each user a data rate proportional to the number of packets (or bits) in that user's queue. This paper analyzes stability, delay and fairness properties of QPS in a Gaussian broadcast channel (BC). QPS is shown to achieve throughput optimality, and guarantee fairness as well as different priorities among users in terms of average queuing delay. One well known throughput optimal policy for broadcast channels is Maximum Weight Matching Scheduling (MWMS) that maximizes the inner product of the queue state vector and the achievable rate vector. Simulation results with Poisson packet arrivals and exponentially distributed packet lengths demonstrate that QPS provides a significant decrease in average queuing delay compared to MWMS in a Gaussian BC.

This paper studies the fading multiple-access channel (MAC) with additive Gaussian noise and multiple transmit and receive antennas. It is assumed that the receiver has the perfect channel state information (CSI) while the mobile transmitters have no such knowledge. This paper presents a transmission scheme where the receiver jointly optimizes the signal covariance matrices for all transmitters, based on the channel distribution information (CDI) and the rate demand of each individual user, and then feeds them back to all transmitters. Under this scheme the achievable multi-user power region that is composed of all transmit power-tuples with which a given set of "ergodic" rates is achievable for all transmitters, is characterized by using convex optimization techniques. It is observed from simulation results that the transmit optimization based on the CDI can provide substantial power savings in the fading MAC

The paper provides a proof of the converse for the capacity region of the Gaussian MIMO broadcast channel under total average transmit power constraint. The proof uses several ideas from earlier works on the problem including the recent converse proof by Weingarten, Steinberg and Shamai. First the duality between Gaussian multiple access and broadcast channels is employed to show that every point on the boundary of the dirty paper coding region can be represented as the optimal solution to a convex optimization problem. Using the optimality conditions for this convex problem, a degraded broadcast channel is constructed for each point. It is then shown that the capacity region for this degraded broadcast channel contains the capacity region of the original channel. Moreover, the same point lies on the boundary of the dirty paper coding region for this degraded channel. Finally, the standard entropy power inequality is used to show that this point lies on the boundary of the capacity region of the degraded channel as well and consequently it is on the boundary of the capacity region of the original channel

This paper proposes efficient rate and power allocation algorithms for OFDMA downlink systems where each tone is taken by at most one user. Weighted sum rate maximization (WSRmax) and weighted sum power minimization (WSPmin) problems are considered. Since these resource allocation problems are non-convex, complexity of finding the optimal solutions is prohibitively high. This paper employs the Lagrange dual decomposition method to efficiently solve both optimization problems. Because of their non-convex nature, there is no guarantee for the solution obtained by the dual decomposition method to be optimal. However, it is shown that with practical number of tones, the duality gap is virtually zero and the optimal solutions can be efficiently obtained

In a fading broadcast channel (BC), Queue Proportional Scheduling (QPS) is presented via geometric programming (GP). Given the current queue state, QPS allocates a data rate vector such that the expected rate vector averaged over all fading states is proportional to the current queue state vector as well as on the boundary of the ergodic BC capacity region. One well known throughput optimal policy for a fading BC is Maximum Weight Matching Scheduling (MWMS), which maximizes the inner product of the queue state vector and achievable rate vector. Simulation results for Poisson packet arrivals and exponentially distributed packet lengths demonstrate that QPS provides a significant decrease in average queuing delay compared to MWMS. In addition, QPS is shown to guarantee fairness among users in terms of average queuing delay.

In mobile wireless networks, dynamic allocation of resources such as transmit powers, bit-rates, and antenna beams based on the channel state information of mobile users is known to be the general strategy to explore the time-varying nature of the mobile environment. This paper looks at the problem of optimal resource allocation in wireless networks from different information-theoretic points of view and under the assumption that the channel state is completely known at the transmitter and the receiver. In particular, the fading multiple-access channel (MAC) and the fading broadcast channel (BC) with additive Gaussian noise and multiple transmit and receive antennas are focused. The fading MAC is considered first and a complete characterization of its capacity region and power region are provided under various power and rate constraints. The derived results can be considered as nontrivial extensions of the work done by Tse and Hanly from the case of single transmit and receive antenna to the more general scenario with multiple transmit and receive antennas. Efficient numerical algorithms are proposed, which demonstrate the usefulness of the convex optimization techniques in characterizing the capacity and power regions. Analogous results are also obtained for the fading BC thanks to the duality theory between the Gaussian MAC and the Gaussian BC.

For fading broadcast channels (BC), a throughput optimal scheduling policy called queue proportional scheduling (QPS) is presented via geometric programming (GP). QPS finds a data rate vector such that the expected rate vector over all fading states is proportional to the current queue state vector and is on the boundary of the ergodic capacity region of a fading BC. Utilizing the degradedness of BC for each fading state, QPS is formulated as a geometric program that can be solved with efficient algorithms. The GP formulation of QPS is also extended to orthogonal frequency-division multiplexing (OFDM) systems in a fading BC. The throughput optimality of QPS is proved, and it is shown that QPS can arbitrarily scale the ratio of each user's average queueing delay. Throughput, delay, and fairness properties of QPS are numerically evaluated in a fading BC and compared with other scheduling policies such as the well-known maximum weight matching scheduling (MWMS). Simulation results for Poisson packet arrivals and exponentially distributed packet lengths demonstrate that compared with MWMS, QPS provides a significant decrease in average queueing delay and has more desirable fairness properties.

This letter examines a discrete bit-loading problem of upstream and downstream for discrete multitone digital subscriber lines with echo cancellation. Both far-end crosstalk and near-end crosstalk are taken into account. An optimal discrete bit-loading algorithm is developed when the loop lengths of all same-service users in a common binder are the same. Simulation results show that the optimal algorithm achieves a substantially higher data rate than existing suboptimal schemes.

A multiuser bit-loading problem is investigated in multicarrier communication systems. Assuming knowledge of all the channel gains, we propose a multiuser bit-loading algorithm that attempts to minimize the total power to transmit a target rate-sum of all users. It is shown that this algorithm is optimal when the interference among users is nonexistent or strong. The simulation results show that the proposed algorithm finds a near-optimal solution for very-high-speed digital subscriber line systems.

In this paper, capacity limits and power-control schemes are assessed for the block-fading (BF) additive white Gaussian noise (AWGN) channels under the assumption that the channel state information (CSI) is known at both the transmitter and the receiver sides. Two notions of channel capacity limits are considered in this paper, including the ergodic capacity for transmission without delay constraint, and the delay-limited capacity for transmission under a strict delay constraint. With the full availability of CSI, a BF channel can be decomposed into multiple space-time-frequency subchannels, and is, therefore, considered in this paper as a vector BF channel. We propose a class of multitarget (MT) power-control schemes, which we show to be computationally implementable and able to perform well in approaching the capacity limits of vector BF channels. These power-control schemes are based on a subchannel grouping technique, which can be used to further divide subchannels in a vector BF channel into multiple grouped channels, each exhibiting different fading statistics. Each MT scheme then assigns a particular set of power "targets" into these grouped channels, and maximizes the transmission rate via various statistical waterfilling solutions. Numerical results are presented to evaluate and compare the achievable transmission rates associated with these proposed schemes for some example vector BF channels.

In this letter, we investigate the performance of constant-power waterfilling algorithms for the intersymbol interference channel and for the independent identically distributed fading channel where a constant power level is used across a properly chosen subset of subchannels. A rigorous performance analysis that upper bounds the maximum difference between the achievable rate under constant-power waterfilling and that under true waterfilling is given. In particular, it is shown that for the Rayleigh fading channel, the spectral efficiency loss due to constant-power waterfilling is at most 0.266 b/s/Hz. Furthermore, the performance bound allows a very-low-complexity, logarithm-free, power-adaptation algorithm to be developed. Theoretical worst-case analysis and simulation show that the approximate waterfilling scheme is very close to the optimum.

This correspondence studies the statistical distribution of the signal-to-interference-plus-noise ratio (SINR) for the minimum mean-square error (MMSE) receiver in multiple-input multiple-output (MIMO) wireless communications. The channel model is assumed to be (transmit) correlated Rayleigh flat-fading with unequal powers. The SINR can be decomposed into two independent random variables: SINR=SINR/sup ZF/+T, where SINR/sup ZF/ corresponds to the SINR for a zero-forcing (ZF) receiver and has an exact Gamma distribution. This correspondence focuses on characterizing the statistical properties of T using the results from random matrix theory. First three asymptotic moments of T are derived for uncorrelated channels and channels with equicorrelations. For general correlated channels, some limiting upper bounds for the first three moments are also provided. For uncorrelated channels and correlated channels satisfying certain conditions, it is proved that T converges to a Normal random variable. A Gamma distribution and a generalized Gamma distribution are proposed as approximations to the finite sample distribution of T. Simulations suggest that these approximate distributions can be used to estimate accurately the probability of errors even for very small dimensions (e.g., two transmit antennas).

This letter analyzes the effect of the carrier frequency offset on orthogonal frequency division multiplexing (OFDM) systems for multipath fading channels. A simple approximate expression for the average signal-to-noise ratio (SNR) is derived. This approximate expression is shown to be an upper bound of the average SNR for flat fading channels and an exact expression for the AWGN channel. The approximate average SNR expression is validated using Monte Carlo simulation for both flat fading channels and frequency-selective fading channels

This paper proposes adaptive modulation and coding (AMC) as a method for the bit-interleaved coded OFDM (BIC-OFDM) packet transmission. Following a pair-wise error probability (PEP) analysis of AMC-BIC-OFDM in a slowly fading frequency selective channel, AMC scheme maximizes the total rate by optimally selecting the code and efficiently allocating rate and power over the frequency band. The proposed method improves upon the performance of uniform rate and power allocation scheme by 6.5 to 10 dB

It has been shown that the quasi-orthogonal space-time block codes (QOSTBCs) can achieve full diversity by rotating the constellations of half the transmitted symbols. Although the rotation angle has been analytically derived for QAM constellations, for arbitrary M-PSK, the coding gain maximizing rotation angle can be found only by computer search. In this paper, a set of QOSTBCs for four transmit antennas that achieves full diversity for M-PSK modulations is presented. The orthogonal designs for real constellations and several QOSTBCs are also included in our formulation. With the same maximum-likelihood decoding complexity, the new codes have BER performance identical to the QOSTBC with constellation rotations. Without any constellation expansion, our scheme is superior to the QOSTBC with constellation rotations in implementations.

This paper studies the system throughput limits of the MIMO broadcast channel for wireless downlink transmission. More specifically, the expected throughput for no-delay-constrained (NDC) traffic and the delay-limited throughput for delay-constrained (DC) traffic are characterized and compared. The multiuser-diversity effect on the delay-limited throughput for DC traffic is discussed for the first time. A novel transmission scheme that can simultaneously support both NDC and DC traffics is proposed. Computer simulation shows that the proposed scheme can approach the system throughput limit effectively provided that it is designed for the correct traffic ratio between NDC and DC services.

This paper considers wireless downlink transmission when multiple antennas are employed at both the base station (BS) and the mobile terminals. Assorted dynamic transmission schemes based on TDMA and SDMA are described and their associated system throughput limits are compared, under different assumptions on the availability of channel side information (CSI) at the BS. The trade-off between scheme complexity and system throughout is discussed.

It has been shown that a complex orthogonal design that provides full diversity and full transmission rate is not possible for more than two transmit antennas. The paper presents a new class of quasi-orthogonal space-time block codes using a group-theoretic method. The new designs can achieve full diversity for quadrature phase-shift-keying modulation, like the system using rotated constellations. Based upon the analysis of the new codes, a relaxed designing viewpoint for full diversity is proposed for arbitrary signal constellations.

Time variation of wireless channels can have a serious effect on the quality of service (QoS) experienced by the data streams. However, these channel processes cannot be easily characterized within a queueing theory framework. In this work, the burstiness properties of the wireless channel process are captured using its peakedness function. The channel process is then replaced by a renewal process with the same peakedness function to enable analysis based on queueing theory results. Simulations show that the approximate queue formed using peakedness matching is a very good predictor of the QoS behavior of the original queue.

This paper considers a scenario where multiple antenna base stations use transmit beamforming to communicate with single antenna mobiles with minimum receive signal-to-interference ratio (SIR) constraints. In this system, minimizing the total power expenditure requires solving a non-convex optimization problem. A semi-definite program (SDP) relaxation can be used to convert the non-convex problem to a centralized SDP that can be solved efficiently and optimally with convex optimization techniques. Using the properties of the dual of this SDP relaxation, a two-stage iterative algorithm is proposed to solve the decentralized version of the problem. In the first stage, limited amount of centralized feedback is used to find the optimum beamforming directions through distributed eigenvalue computations. The second stage uses the distributed autonomous power control technique proposed by Foschini and Miljanic for single antenna systems.

This paper proposes a new transmitting scheme for a multi-antenna (MIMO) Gaussian broadcast channel. The transmitter exploits multiuser diversity using a small amount of feedback information from the receivers. The feedback information consists of the maximum achievable rate for each user and the necessary power distribution profile across the spatial dimensions that the transmitter should use to achieve that rate. The receivers use the iterative water-filling algorithm to maximize the achievable rate. The new scheme serves a single user at each transmission, hence the name single user random beamforming (SUBF) scheme. The proposed scheme maximizes the average sum rate under a TDMA environment (i.e., supporting a single user at a time) with the partial channel state information (CSI) feedback constraint.

This paper considers two sub-optimal transmission schemes for a family of parallel Gaussian vector broadcast channels. One of the schemes is based on the QR precoding of Ginis et al. (2000). In QR precoding, the maximum achievable throughput depends on the order in which users are encoded. This scheme is a new algorithm for obtaining the best user ordering and channel-input covariance matrix that maximizes the total channel throughput. The proposed algorithm has linear complexity in the number of multi-carrier frequencies. The simplicity of a linear transmitter-and-receiver architecture is attractive for a transmission scheme. The design of a linear transmitter and multiple linear receivers that maximize the total throughput is studied. It is shown that under discrete bit loading assumption for each user, this problem reduces to solving a series of second order cone programming problems.

A novel framework is presented to characterize the tradeoff between diversity and multiplexing of space-time codes at finite signal-to-noise ratios (SNR). The diversity gain of a space-time code is defined by the slope at a particular SNR of the outage probability versus SNR curve for a multiplexing gain defined by the ratio of the system spectral efficiency to the capacity of an additive white Gaussian noise (AWGN) channel. The finite-SNR diversity-multiplexing tradeoff is evaluated for orthogonal space-time block codes and spatial multiplexing with horizontal encoding. The tradeoff curves provide a characterization of achievable diversity and multiplexing gains for a given space-time code at SNR encountered in practice. It is seen that the achievable diversity gains at finite SNR are significantly lower than the asymptotic values given in the literature.

This paper proposes a transmit power optimization algorithm for a Gaussian vector broadcast channel. The optimal power allocation minimizes the sum trace of input covariance matrices of all the users in the Gaussian vector broadcast channel. By duality the transmit power optimization can be transformed into an equivalent convex optimization in a multiple access channel. Recursive equations are derived as sufficient conditions for the minimum transmit power and an iterative algorithm is proposed to solve the equations. Numerical examples show that the iterative algorithm converges very fast and efficiently determines the input covariance matrices for the optimum power allocation.

This paper studies the combination of practical trellis and convolution codes with Tomlinson-Harashima precoding (THP) for the presubtraction of multiuser interference that is known at the transmitter but not known at the receiver. It is well known that a straightforward application of THP suffers power, modulo, and shaping losses. This paper proposes generalizations of THP that recover some of these losses. At a high signal-to-noise ratio (SNR), the precoding loss is dominated by the shaping loss, which is about 1.53 dB. To recover shaping loss, a trellis-shaping technique is developed that takes into account the knowledge of a noncausal interfering sequence, rather than just the instantaneous interference. At rates of 2 and 3 bits per transmission, trellis shaping is shown to be able to recover almost all of the 1.53-dB shaping loss. At a low SNR, the precoding loss is dominated by power and modulo losses, which can be as large as 3-4 dB. To recover these losses, a technique that incorporates partial interference presubtraction (PIP) within convolutional decoding is developed. At rates of 0.5 and 0.25 bits per transmission, PIP is able to recover 1-1.5 dB of the power loss. For intermediate SNR channels, a combination of the two schemes is shown to recover both power and shaping losses.

Successive interference cancellation (SIC) is a technique for increasing the capacity of cellular code-division multiple-access (CDMA) systems. To be successful, SIC systems require a specific distribution of the users' received powers, especially in the inevitable event of imperfect interference cancellation. This apparent complication of standard CDMA power control has been frequently cited as a major drawback of SIC. In this paper, it is shown that surprisingly, these "complications" come with no additional complexity. It is shown that 1-bit UP/DOWN power control-like that used in commercial systems-monotonically converges to the optimal power distribution for SIC with cancellation error. The convergence is proven to within a discrete step-size in both signal-to-noise plus interference ratio and power. Additionally, the algorithm is applicable to multipath and fading channels and can overcome channel estimation error with a standard outer power control loop.

The paper presents an exact analysis of the effect of the carrier frequency offset on orthogonal frequency division multiplexing (OFDM) systems for a general multipath fading channel. As is well known, the carrier frequency offset attenuates the desired signal and causes intercarrier interference, thus reducing the signal-to-noise ratio (SNR). The SNR degradation due to the carrier frequency offset is evaluated by deriving the exact SNR expression in the presence of the carrier frequency offset. The SNR analysis can be used for the design of a practical OFDM system in determining how small the frequency offset should be in order to maintain the SNR degradation to negligible levels.

In order to obtain high transmission rates DSL systems have to cope with stationary and non-stationary disturbances, as well as the non-ideal characteristic of the twisted pair channel. To mitigate non-stationary interference, a forward error correction (FEC) scheme is employed that consists of a Reed-Solomon outer code and interleaving. By augmenting the interleaving delay, protection against increasingly long noise bursts can he achieved. however, when radio frequency ingress (RFI) also affects the subscriber loops, the required interleaving delay may potentially increase to undesired levels. The additional delay that is required for combined impulse noise and RFI protection can be lowered by using more redundant RS codes, or by employing RFI cancellation techniques. In the latter case, additional digital cancellation is also necessary in order to mitigate the effect of RFI on the transmitted data. This paper proposes a digital RFI cancellation scheme for DMT-DSL systems that is based on information exchange between the DSL demodulator and the RS decoder at the receiver. It is shown that the technique can be seamlessly incorporated in current DMT-DSL systems, since no changes are required at the transmitter. The method can partly cancel the effect of RFI, and can help bridge the gap between the required interleaving delay when only impulse noise is present and the increased delay when RFI also affects transmission.

This paper studies the capacities of block-fading (BF) additive white Gaussian noise (AWGN) channels with multiple transmit and receive antennas, under the assumption that perfect channel state information is available at both the transmitter (CSIT) and the receiver (CSIR). We study both ergodic capacity under no transmission delay constraint and delay-limited capacity for delay-constrained case, and consider the tradeoff between capacity and complexity. Optimal power allocation schemes to achieve ergodic and delay-limited capacities are known as variants of standard water-filling algorithms, which usually requires large computational complexity at the transmitter side. In this paper, we propose a new sub-optimal power allocation scheme, so-called multi-target channel inversion (MT-CI), which can be easily implemented at the transmitter and still asymptotically achieve the performance of optimal schemes. Furthermore, MT-CI transforms the original fading channel into parallel AWGN channels and hence greatly reduces the receiver complexity. In addition, the proposed scheme is shown to be also suitable for simultaneous transmission of multimedia services which may require different levels of quality of service (QOS).

In next generation data networks, joint optimization of physical layer parameters and scheduling layer parameters will be necessary to meet the demands of quality of service (QoS)-constrained traffic like video traffic. Until now, such optimization problems considered only simple and non-realistic Markov chain models to represent physical layer channel dynamics. In this paper, we consider the incorporation of realistic channel models in a Markov decision process (MDP) formulation for the QoS-constrained optimization of the physical layer. The channel random process is transformed into an extended Markovian setup through hidden Markov models (HMM) and the solution of the resulting optimization problem is shown to be a partially observable Markov decision process (POMDP). The optimal scheduling agent bases its decision on a parameter that summarizes complete system history until the decision instant. This parameter can he computed at each decision instant based only on newly available information, avoiding the need to record all the past states.

Adaptive modulation and coding (AMC) is receiving increasing attention as an effective method to enhance the performance of wireless systems. This paper proposes AMC as a method for the bit-interleaved coded OFDM (BIC-OFDM) packet transmission. We provide a pair-wise error probability (PEP) analysis of AMC-BIC-OFDM in a slowly fading frequency selective channel. We maximize the total rate by optimally selecting the code and efficiently allocating rate and power over the frequency band. The proposed method improves the performance of uniform rate and power allocation scheme by 8 to 19 dB.

This paper proposes a low-complexity space-frequency bit-interleaved coded modulation (SF-BICM) transceiver with successive interference cancelling (SIC) processing for multiinput multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two schemes are presented in order to improve the detection performance of SF-BICM perturbated by the error propagation at SIC receiver. First, the bit stream to each transmit antenna is distributed via the rate-compatible puncturing (RCP) such that the SIC process is "code-assisted". Second, a simple heuristic soft bit-metric computation is proposed to compensate for the incorrect soft information caused by the error propagation. Simulation results in the indoor wireless local area network (WLAN) channels show that the proposed RCPC SF-BICM with the new soft bit-metric has significant power gains up to 6dB over the conventional SIC receiver.

The paper studies power control schemes for achieving the ergodic capacity of vector block-fading (BF) channels when the channel state information (CSI) is available to both transmitter and receiver sides. The optimal water-filling solution achieves the maximum ergodic capacity, but requires complicated calculations and frequent adjustment of the transmission powers. On the other hand, a single-target constant power (ST-CP) policy is easier to implement, but experiences large capacity loss compared to the optimal solution. A suboptimal policy is proposed which first groups the sub-channels within the frame of interest into multiple grouped channels, then allocates different constant powers to each grouped channel using a statistical water-filling (SWF) policy. The new scheme asymptotically achieves the maximum ergodic capacity. Simulations are given to evaluate the performance of the new scheme, and to compare it with the optimal power allocation scheme and the single-target constant power policy.

In certain communication channels, such as short copper twisted pairs, it is theoretically possible to perform transmission with very high spectral efficiency using a very wide bandwidth. However, current analog-to-digital converter (ADC) technology limits the allowable sampling rate and resolution, thus severely constraining the transmission speeds. This paper proposes the partitioning of the available bandwidth into multiple bands, each employing an independent ADC. The benefit of such a scheme is the reduction of the sampling rates of the ADCs. An increase in the dynamic range is allowed, thus offering the potential to realize very high spectral efficiencies. An analysis of transmission under ADC constraints is performed, where an expression for the achievable data rate is derived, based on an empirical rule for the tradeoff between the ADC sampling rate and resolution. A bandwidth-partitioning problem is formulated, where the objective is the maximization of the data rate, and the optimization parameters are the frequency-band assignments. Then, a practical example of transmission over category (CAT)-5 cable is considered. The possible impairment factors are outlined, and the essential system elements are described. Using the previously given algorithm, the optimum solution and the corresponding performance are given for two distinct scenarios. These scenarios serve to illustrate the bandwidth-partitioning procedure, and provide useful intuition regarding the application of the proposed method. In particular, it is deduced that it is best to have narrower bands in frequencies where the signal-to-noise ratio (SNR) is relatively high, and wider bands in frequencies where the SNR is relatively low.

We derive optimal and suboptimal multiuser transmit-optimization methods for a multicarrier broadcast channel with intersymbol interference under the frequency-division multiple-access (FDMA) restriction. The general FDMA-based multicarrier broadcast problem is formulated as a maximum weighted rate-sum problem. Given each user's subchannel assignment, the optimal transmit strategy is achieved by multilevel waterfilling. Unfortunately, the problem of finding the optimal subchannel assignments is combinatorial. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution, and therefore, a characterization of the FDMA capacity region for a broadcast channel. If all users share the same transmission medium, we prove that the optimal frequency partitioning among the users has an ordered structure that can be exploited to significantly reduce the computational complexity. To make multiuser transmit-optimization schemes practical for applications with relatively fast time-varying user data-rate requirements or priorities, further reduction in computational complexity is necessary. This is achieved by restricting the energy distribution to be constant across the used subchannels. Simulations indicate the low-complexity constant-energy methods presented are very robust, and suffer from negligible performance loss.

In addition to being designed to successfully cope with stationary noise, crosstalk, and intersymbol interference, digital subscriber loop (DSL) systems need to be shielded from nonstationary disturbances, such as impulse noise and RF interference. Currently, deployed DSL systems achieve protection against nonstationary interference using a combination of Reed-Solomon (RS) codes and interleaving. However, interleaving results in delay. Long delays are undesirable in high-rate systems that support interactive applications. In this study, it is shown that the interleaving delay of DSL systems can be significantly reduced by performing erasure decoding of the RS codewords at the receiver. Three different techniques for determining the erasures are proposed. Use of the techniques results in a reduction of the interleaving delay that is required to mitigate worst-case impulse noise by up to a factor of 2, which is verified by simulation. Moreover, the techniques do not require any changes at the transmitter and therefore guarantee compatibility with currently deployed systems.

This paper characterizes the sum capacity of a class of potentially nondegraded Gaussian vector broadcast channels where a single transmitter with multiple transmit terminals sends independent information to multiple receivers. Coordination is allowed among the transmit terminals, but not among the receive terminals. The sum capacity is shown to be a saddle-point of a Gaussian mutual information game, where a signal player chooses a transmit covariance matrix to maximize the mutual information and a fictitious noise player chooses a noise correlation to minimize the mutual information. The sum capacity is achieved using a precoding strategy for Gaussian channels with additive side information noncausally known at the transmitter. The optimal precoding structure is shown to correspond to a decision-feedback equalizer that decomposes the broadcast channel into a series of single-user channels with interference pre-subtracted at the transmitter.

This paper proposes an efficient numerical algorithm to compute the optimal input distribution that maximizes the sum capacity of a Gaussian multiple-access channel with vector inputs and a vector output. The numerical algorithm has an iterative water-filling interpretation. The algorithm converges from any starting point, and it reaches within 1/2 nats per user per output dimension from the sum capacity after just one iteration. The characterization of sum capacity also allows an upper bound and a lower bound for the entire capacity region to be derived.

This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error.

IEEE 802.11a wireless local area network (WLAN) system which employs bit-interleaved coded orthogonal frequency division multiplexing (OFDM) is one of the most important applications of bit-interleaved coded modulation (BICM). The capacity and cutoff rate of BICM have been well studied in flat-fading channels assuming infinite-length ideal interleaving. This assumption is practically justifiable only in fast-fading channels. WLAN channel environment is, however, highly frequency selective while slowly varying in time. In this work, we obtain outage capacity and outage cutoff rate expressions for BICM in such quasistatic frequency selective fades, under a uniform ideal interleaving assumption. These results are also extended to the general case of space-frequency BICM (SF-BICM) which is the multiinput multioutput (MIMO) extension of BICM.

Impulse noise is a potential impairment of very-high speed digital subscriber line (VDSL) services. VDSL systems are protected from impulse noise using a combination of Reed-Solomon coding and interleaving. Since there are two competing proposals for VDSL, the first one based on the use of QAM line code and the second one using DMT modulation, it is interesting to compare their performance in terms of immunity to impulse noise. The paper presents a comparison of the behavior of QAM-VDSL and DMT-VDSL in the presence of impulse noise in real configurations. The required interleaving delay to correct all the generated errors for both systems is investigated. It is shown that when no notches are used in the radio-amateur bands, QAM and DMT systems require similar delays in order to achieve the same level of protection against impulse noise. However, when notches are implemented, DMT-VDSL achieves higher rates than QAM-VDSL. Therefore, larger error-correcting code redundancy can be used, which results in lower end-to-end delays for DMT-VDSL systems.

DSL systems achieve high rate transmission through copper pairs traditionally used for voiceband communication. In order to attain high rates, sophisticated system designs are employed to cope with both stationary and non-stationary disturbers. In current DSL systems, protection against nonstationary interference, comprising impulse noise and radio frequency ingress (RFI), is achieved using a forward error correction (FEC) scheme consisting of a Reed-Solomon (RS) code and interleaving. However, interleaving results in increased end-to-end delay. The end-to-end delay can be reduced by taking advantage of the erasure decoding property of RS codes. The paper presents a byte-erasure technique that allows erasure decoding to be employed. The method locates the possibly erroneous bytes in each RS codeword by comparing the square distance between each received carrier symbol of the interleaved stream and the closest point of the constellation to which the symbol belongs. Thus, the interleaving delay can be reduced by a factor up to 2 when impulse noise impairs transmission. The method can also be applied to systems affected by both impulse noise and RFI, since it can distinguish between the two sources of non-stationary interference. Finally, no change is required at the transmitter, and hence compatibility with currently deployed systems is guaranteed. A DMT-VDSL system is used as a particular example of the achieved reduction of the interleaving delay.

This paper presents a low-complexity iterative receiver for coded OFDM systems. We present an EM-based iterative algorithm for combined channel estimation and decoding that makes collective use of the available data and system constraints. Minimum numbers of pilots are sent only in the first symbol of the packet to acquire the channel; then the iterative algorithm is used to track the channel time variation, which is assumed to follow a state-space model, using an EM-based Kalman filter. Data recovery can be achieved within a single OFEM symbol. We also propose the use of an optional outer LDPC code in serial concatenation to offer a trade-off between latency and performance, especially for multi-amplitude modulations, without affecting the complexity of the core iterative algorithm.

This paper presents the capacity region of frequency-selective Gaussian interference channels under the condition of strong interference, assuming an average power constraint per user. First, a frequency-selective Gaussian interference channel is modeled as a set of independent parallel memoryless Gaussian interference channels. Using non-frequency selective results, the capacity region of frequency-selective Gaussian interference channels under strong interference is expressed mathematically. Exploiting structures inherent in the problem, a dual problem is constructed for each independent memoryless channel, and solved. Furthermore, three suboptimal methods are compared with the capacity-achieving coding and power allocation scheme. Iterative waterfilling, a suboptimal scheme, provides close-to-optimum performance and has a distributed coding and power allocation scheme, which are attractive in practice.

This paper investigates the power allocation for upstream and downstream signals in twisted-pair channels in order to maximize data rate. The channels interfere with each other in two forms: the near-end crosstalk and far-end crosstalk. These interferences can be mitigated by the joint optimization of upstream and downstream power spectral density (PSD). We derive the condition under which a subchannel is shared by both streams of monopolized by only one direction stream. In addition, the optimal power-allocation algorithm based on the greedy approach is developed under the discrete-rate constraint. Numerical results show that the optimal power-allocation achieves substantially more data rate than suboptimal schemes: the equal PSD scheme and frequency division duplexing (FDD) scheme.

This paper addresses the joint design of transmit and receive beamvectors for a multicarrier MIMO channel within the general and powerful framework of convex optimization theory. From this perspective, a great span of design criteria can be easily accommodated and efficiently solved even though closed-form expressions may not be available. Among other criteria, we consider the minimization of the average bit error rate (BER) and also of the maximum BER among all carriers for a given signal constellation. We show how to include additional constraints to control the peak-to-average ratio (PAR) in the system design.

The data that is transmitted in DSL system is subject to corruption by impulse noise, i.e., noise bursts of high energy that interfere with the transmitted symbols. As DSL data rates increase the crosstalk mitigation techniques become more sophisticated, impulse noise limits service in terms of rate or delay. Because of the highly non-stationary nature of impulse noise, a combination of interleaving and Reed-Solomon coding is currently used to shield systems from noise burst. This paper presents a modified impulse noise protection algorithm that takes advantage of the improved performance of Reed-Solomon codes when the location of the impaired bytes is known. Without changing the structure of the encoder or the interleaver, it is shown that the delay, or equivalently the overhead due to forward error correction coding, can be reduced without compromising the immunity of the system to impulses. A DMT-VDSL system is used as a particular example of the improvement achieved using byte-erasure.

A significant portion of the end-to-end delay in high-rate DSL systems is due to the impulse noise protection scheme employed in order to shield those systems against random, non-stationary noise bursts of high energy that appear on the copper lines. Systems are protected from impulse noise using a combination of interleaving and Reed-Solomon codes. In order to lower the end-to-end delay without reducing the data rate that is available to the user, one needs to decrease the interleaver depth. This paper presents a way to achieve this reduction without compromising neither the robustness to noise bursts nor the data rate of the system. The proposed algorithm relies on the inner code used by many DSL systems and uses the metric provided by the inner code decoder at the receiver. A DMT-VDSL system is used as a particular example of the achieved reduction of the end-to-end delay.

Multipath fading and inter-symbol interference (ISI) are two fundamental impairments limiting the transmission quality of broadband wireless communications. In this paper we consider multiple-input single-output ISI channels and propose an ISI minimizing method implemented at the base station (BS) side using space time block coding (STBC) and statistical pre-filtering (SPF), which combines transmit beamforming (TB) with signal pre-alignment (PAL) based on the statistical knowledge of downlink channel state information (CSI). The proposed method transforms a time-dispersive channel into multiple flat fading channels, thus not only the ISI is minimized through SPF, but also the path diversity is maintained through STBC. With the delay spread reduction capability, the SPF method is further applied to multicarrier systems to reduce the cyclic prefix length, thus to increase the system throughput. Computer simulations have evaluated the effectiveness of the proposed method.

Maximizing the total rate with no coordination is an attractive option to increase the throughput of existing multiuser communication systems. The paper compares a suboptimal method for rate and power allocation in a two-user multicarrier channel with the optimal method, subject to individual power constraints. The suboptimal method, iterative waterfilling (IW), closely approximates the performance of the optimal method when interference power is small. Moreover, IW is easy to deploy in existing systems in which different transmission paths may not be coordinated.

This paper proposes a new method for decoding multicarrier symbols with severe nonlinear distortion. The first part evaluates mutual information expressions for practical nonlinear models and shows the performance bounds for commonly used receiver structures. Then, we derive the maximum-likelihood (ML) sequence estimator, which unfortunately has an exponential complexity due to the nonlinear distortion. This extremely large complexity can be reduced with a simple algorithm that iteratively estimates the nonlinear distortion, thereby reducing the exponential ML to the standard ML without nonlinear distortion. The proposed method can be used to reduce the peak-to-average power ratio of multicarrier signals by clipping the transmit sequence. It can also be used to correct any nonlinear distortion present in transmitter/receiver amplifiers that are operating close to saturation.

The paper presents a numerical study of the impact of impulse noise on asymmetric digital subscriber lines (ADSL). Methods for simulating the effect of impulse disturbances on a discrete multitone system are first presented, and actual measured noise bursts are then used for the simulations as if they were deterministic signals, in order to characterize their effects on ADSL systems. It is shown that, while a combination of coding, interleaving, and 6-dB margin is adequate in protecting ADSL systems from isolated impulses, an impulse train with long duration can cause a significant number of error bits in the system. In this case, a tradeoff among the number of error seconds, the maximum reach, and the coding delay must be made.

When transmitting over multiple-input-multiple-output (MIMO) channels, there are additional degrees of freedom with respect to single-input-single-output (SISO) channels: the distribution of the available power over the transmit dimensions. If channel state information (CSI) is available, the optimum solution is well known and is based on diagonalizing the channel matrix and then distributing the power over the channel eigenmodes in a "water-filling" fashion. When CSI is not available at the transmitter, but the channel statistics are a priori known, an optimal fixed power allocation can be precomputed. This paper considers the case in which not even the channel statistics are available, obtaining a robust solution under channel uncertainty by formulating the problem within a game-theoretic framework. The payoff function of the game is the mutual information and the players are the transmitter and a malicious nature. The problem turns out to be the characterization of the capacity of a compound channel which is mathematically formulated as a maximin problem. The uniform power allocation is obtained as a robust solution (under a mild isotropy condition). The loss incurred by the uniform distribution is assessed using the duality gap concept from convex optimization theory. Interestingly, the robustness of the uniform power allocation also holds for the more general case of the multiple-access channel.

The advantages of multiuser communication, where many users are allowed to simultaneously transmit or receive in a common bandwidth, are considered for multiple-antenna systems in a high signal-to-noise ratio (SNR) regime. Assuming channel state information at receiver (CSIR) to be available, the ergodic capacity is characterized for both unbiased and biased channels, and the quantitative capacity gain of a multiple-antenna multiuser system is analyzed for multiple-access channels. For highly biased (correlated) channels, a multiuser system is shown to be inherently superior to a single-user system (a time- or frequency-division multiple-access (TDMA or FDMA) based system) due to the underlying multiuser diversity, and the sum capacity is shown to scale linearly with the number of antennas. For unbiased channels, the characteristics of ergodic capacity are shown to transfer to outage capacity when a large degree of space diversity exists, and to deterministic capacity when the number of receive antennas is large. Also, a brief discussion on the multiuser multiple-antenna communication in broadcast channel is provided.

OFDM systems typically use coding and interleaving across subchannels to exploit frequency diversity on frequency-selective channels. This paper presents a low-complexity iterative algorithm for combined blind and semi-blind channel estimation and soft decoding in coded OFDM systems. Channel estimation is performed in the time domain using the expectation maximization (EM) algorithm to take advantage of the channel-length constraint and the extra observation offered by the cyclic-prefix. The proposed technique converges within a single OFDM symbol and, therefore, has a minimum latency and is suitable for fast time-varying channels.

This paper investigates the multiuser bit and power allocation problem in discrete multi-tone digital subscriber line modems. A spectrum-management center with knowledge of direct and crosstalk-coupled channel gains allocates the bits and the available power to the subchannels for all users in a common binder. The center uses a multiuser discrete bit-loading algorithm that attempts to minimize the total transmit power given a target sum-rate. This algorithm extends the greedy algorithm for the single-user channel to the multi-user channel. Simulation results for the upstream transmission in very high-speed digital subscriber line show that the total power can be reduced using the multi-user discrete bit-loading algorithm instead of applying. the single-user greedy algorithm iteratively.

This paper investigates the rate and power control problem in a frequency-selective interference channel. The objective of the rate and power control is to maximize the achievable rate region, given an average power constraint for each user. We then propose a centralized algorithm with which a spectrum-management center determines the data rate and power of each user. The proposed algorithm is based on the multi-user discrete bit-loading algorithm that considers the bit and power allocation over frequency and users simultaneously. Simulation results for the upstream transmission in very high-speed digital subscriber line systems show that the proposed rate and power control algorithm enlarges the rate region achieved by the existing distributed algorithms.

Multiuser detection in DSL systems has recently gained some attention. Several methods have been proposed and they provide a significantly increased data rate. However, there are several issues that must be resolved in order to realize the asserted improvements. These issues include the frame synchronization of the different users. We analyze the issue of frame synchronization in a multiuser DSL environment. We propose a novel method to solve this issue that utilizes DSL specific characteristics to overcome obstacles that make the general problems difficult or intractable. Then, the performances of the proposed scheme are analyzed.

This paper proposes and analyzes an iterative power control scheme for use with successive interference cancellation (SIC) in the presence of cancellation errors. SIC is shown by Andrews and Meng (see IEEE Transactions On Wireless Communications, Oct. 2001), to increase the capacity of cellular CDMA systems significantly, even if the signal cancellation is imperfect due to estimation errors. However, an important complication of SIC relative to conventional CDMA receivers is that a specific non-uniform distribution of powers must be assigned to the users in order for the system to function robustly. This paper proposes a simple up/down distributed iterative power control scheme for DS-CDMA systems employing SIC. We analyze its feasibility region and prove that it converges to close to the optimum solution even in the presence of estimation errors. The total received power is shown to be a reliable metric for admission control. This analysis considers both multi-rate CDMA where each user has a different target signal-to-interference-and-noise ratio (SINR), and asynchronous power control where user power updates occur asynchronously.

Space-time block codes from orthogonal designs were proposed in Tarokh et al. (1999) for communication over fading channels with multiple transmit and receive antennas. These codes require no knowledge of the channel at the transmitter, and linear processing at the receiver achieves maximum-likelihood decoding. This paper presents an alternative approach to code design, where the code criterion is such that the transmitter and receiver operations essentially "diagonalize" any arbitrary matrix channel. Such diagonalization greatly simplifies decoding. The transmitter is assumed to have no knowledge of the channel. The desired properties of such a code are derived. It is shown that with some additional constraints, the resulting class of codes is identical to the codes introduced in Tarokh et al. Hence, an alternative interpretation of space-time block codes from orthogonal designs is given. The alternative code construction criteria that are derived may facilitate the design of more general classes of codes.

An adaptive method is proposed for multiple-input-multiple-output (MIMO) decision feedback equalization (DFE) in the absence of channel knowledge at the receiver and without requiring a training sequence. The zero-forcing (ZF) DFE is shown to consist of an orthogonal matrix (feedforward section) and an upper triangular matrix (feedback section). The feedforward matrix is expressed as the multiplication of Givens rotations terms, where each term is characterized by a rotation angle. An adaptive algorithm is presented for the blind determination of the unknown angles and of the elements of the feedback matrix. The adaptation criteria are decorrelation conditions. Simulation results are included demonstrating the performance of the method.

Bit loading algorithms use M-ary quadrature amplitude modulation (M-QAM) of the OFDM sub-carriers, where the number of bits modulating each of them is obtained so that either energy is minimized, rate or margin are maximized. Many of them use the SNR gap approximation for M-QAM signaling, making the algorithm simpler to implement. In some circumstances it may be interesting to use M-ary phase shift keying (M-PSK) instead of M-QAM, e.g. when Golay complementary sequences are used to reduce the PAR (peak-to-average ratio) in OFDM. An approximation is derived for M-PSK similar to the SNR gap of M-QAM, a constant-energy bit loading algorithm is described and its performance is compared to a previously reported algorithm using M-QAM.

This paper presents a method to mitigate interference on a transmission system by another system with an overlapping frequency band. The systems are uncoordinated so that they cannot be made to transmit in orthogonal coding space. The transmission environment is an interference channel rather than the multiaccess channel often considered in other multiuser detection problems, for instance at the base station of a code division multiple access wireless system. Using the fact that the inputs are all from discrete constellations, it is possible to use a multiuser maximum-likelihood (ML) detector to decode the signals from the system of interest with low probability of error. However, the ML detector often requires impractical computation. A soft linear canceler is instead used to reduce the interference with a small loss of bandwidth in the system of interest. The method has a much lower complexity than a full-blown ML detector, and the soft canceler performance is close to an ML detector. The method is demonstrated on a very-high-speed digital subscriber lines system with a home local area network interference. The system of interest is using a multicarrier modulation transmission scheme such as discrete multitone, while the interfering system transmits using quadrature amplitude modulation.

This paper describes the "vectored" transmission technique for digital subscriber line (DSL) systems, which utilizes user coordination at the central office or optical network unit. This method exploits the colocation of the downstream transmitters and of the upstream receivers, in order to achieve far-end crosstalk (FEXT) cancellation and perform multiuser transmission optimization. The performance improvements are particularly pronounced in environments with strong FEXT such as in very high-speed DSL. Discrete multitone is employed for each user with additional constraints on the cyclic prefix length and with the assumption of block-synchronized transmission and reception for downstream and upstream transmission correspondingly. Within each tone, upstream crosstalk is removed by multiple-input-multiple-output decision feedback at the receiving side, while downstream crosstalk is eliminated by analogous preprocessing at the transmitting side. Additionally, the issue of transmission energy allocation in frequency and among users is addressed. Assuming frequency-division duplexing, the corresponding optimization problem is formulated and solved via convex programming both for a fixed upstream-downstream band plan and for a dynamically programmable band plan. The case of power backoff as a means to reduce the impact of crosstalk on alien systems is also treated. Interestingly, the performance of the proposed methods is shown to be very close to known information theory bounds.

We present an algorithm that autonomously synchronizes all DMT-Zipper based VDSL modems in an unbundled access network, solving the problem with nonorthogonal NEXT that appears in systems with unsynchronized modems. The algorithm we present runs autonomously in each VDSL modem in the central office or in the street cabinet. We determine the other modems' relative frame offsets by exploiting their NEXT signal using the inherent cyclic redundancy found in DMT signals. By estimating the relative frame offsets of the other users, we can adjust a given user's own frame-timing relative to the mean of the others. With our method all modems in the network will be synchronized to within a small fraction of the total DMT frame-length, suppressing the nonorthogonal NEXT to a level far below the background noise-floor. This means that we can achieve the same performance in an unbundled access network without any master clock reference as in a system where all modems are perfectly synchronized using a master clock.

Multiuser transmission methods for digital subscriber line (DSL) systems have become of interest with the potential for increased data rate and loop reach. These methods often assume that the set of crosstalk interferers, called the crosstalk profile, and their associated channel responses are known. For DSL systems, the interferers are often uncoordinated, so that in a dynamic environment where DSL transmitters can energize and deenergize, the crosstalk profile cannot be transmitted to the user of interest. While the crosstalk channel estimation problem in a dynamic environment can be intractable for general transmission systems, channel and crosstalk analysis can make use of the specific DSL environment. Namely, the physical channels in a DSL system do not change rapidly, and hence estimates of the crosstalk channel can be saved for future reference. For this reason, we introduce the concept of a channel profile. We develop several algorithms to detect the crosstalk profile and investigate the asymptotic behavior of the new algorithms. Simulations show that for typical crosstalk interference scenarios, the observation time to determine the correct crosstalk profile at probability of error less than 10/sup -3/ can be less than 2 ms.

This paper considers the multiuser power control problem in a frequency-selective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a two-player version of the game. An iterative water-filling algorithm is proposed to efficiently reach the Nash equilibrium. The iterative water-filling algorithm can be implemented distributively without the need for centralized control. It implicitly takes into account the loop transfer functions and cross couplings, and it reaches a competitively optimal power allocation by offering an opportunity for loops to negotiate the best use of power and frequency with each other. When applied to the upstream power backoff problem in very-high bit-rate digital subscriber lines and the downstream spectral compatibility problem in asymmetric digital subscriber lines, the new power control algorithm is found to give a significant performance improvement when compared with existing methods.

Near-end crosstalk (NEXT) is one of the major impairments to the current asymmetric digital subscriber line (ADSL) downstream transmission. This paper presents two methods for an ADSL receiver to cancel one (dominant) NEXT signal from other types of services (such as HDSL (high-bit-rate DSL), SDSL (single-pair, symmetric DSL), T1, etc.). The methods exploit the fact that the crosstalk signal has a large excess bandwidth and its spectra in the main lobe and in the excess band are strongly correlated. The principal idea is then to estimate the crosstalk in some frequency bands (e.g., excess band) and cancel it in other frequency bands (e.g., main lobe). The frequency-domain analysis in this paper provides an intuitive explanation of the crosstalk estimation and cancellation, as well as a guidance to select the right frequency bands to observe the crosstalk signal. Moreover, a fast algorithm is proposed for practical implementation. This algorithm avoids matrix inversion and large matrix multiplication in every transmission block. Simulation results show that one of the proposed methods, minimum mean-squares error estimation and cancellation, is very effective to cancel one (dominant) NEXT and the improvement is significant in terms of the data rate and the line reach for the ADSL service. For example, using a real measured NEXT transfer function, the proposed method can increase the ADSL downstream data rate by 200% for some loops. The methods are extended to estimate and cancel two or more crosstalkers. The amount of improvement depends on the crosstalkers' characteristics and it is generally less than that of a single crosstalker case.

We present a new algorithm for blind symbol synchronization in orthogonal frequency division multiplexing (OFDM) systems. The new algorithm declares symbol synchronization when a certain autocorrelation matrix, constructed from the received signal, achieves minimum rank. Unlike previously proposed blind algorithms, the new rank method guarantees correct symbol synchronization, even in the presence of intersymbol interference. Also, it does not assume that the OFDM time samples are i.i.d. In particular, the rank method works even with OFDM systems that employ pulse shaping. The increased complexity of the algorithm would be acceptable for systems, such as fixed-receiver broadcast systems, that require guaranteed synchronization under all conditions.

Space-time codes have been introduced to improve mobile system performance in a multipath fading environment. We consider a multiple-input multiple-output (MIMO) system with m mobile antennas and n base station antennas, in which there are L multipaths at the base station at distinct angles of arrival. We show that when the channel has no intersymbol interference (ISI), then adaptive antennas in the form of beamforming, can be combined with space-time coding, to achieve a diversity gain of mL and a large signal-to-noise ratio (SNR) gain whenever n/spl ges/L. When the channel has ISI, beamforming can be used by the MIMO systems to achieve an SNR gain over a single-input multiple-output system, although both systems have the same diversity gain.

This paper proposes a numerical method for characterizing the rate region achievable with frequency-division multiple access (FDMA) for a Gaussian multiple-access channel with intersymbol interference. The frequency spectrum is divided into discrete frequency bins and the discrete bin-assignment problem is shown to have a convex relaxation, making it tractable to numerical optimization algorithms. A practical low-complexity algorithm for the two-user case is also proposed. The algorithm is based on the observation that the optimal frequency partition has a two-band structure when the two channels are identical or when the signal-to-noise ratio is high. The simulation result shows that the algorithm performs well in other cases as well. The FDMA-capacity algorithm is used to devise the optimal frequency-division duplex plan for very-high-speed digital subscriber lines.

A block-fading channel model is considered, and a K-block delay constraint is imposed on data transmission. The key consideration is that the channel state information is fed back to the transmitter in a causal manner. A general cost function /spl mu/(x) is considered in solving the delay-constrained transmission problem, under the short-term and the long-term power constraints. A causal power adaptation strategy is needed to maximize the cost function, hence dynamic programming is found to give the optimum solution. The general cost function is then specialized to the cases of expected and outage capacities. In the case of expected capacity, it is observed that optimizing the transmitted power does not give much benefit at high signal-to-noise ratio (SNR), but provides a substantial gain at low SNR. At low SNR, it is proved that the capacity increases by a factor of approximately log K/m, due to power adaptation, when the channel fades according to the /spl chi//sub 2m//sup 2/ statistics. In the case of outage capacity, it is shown that the optimum power adaptation solution to the long-term constraint problem provides a substantial SNR gain at both low and high values of SNR. Random coding bounds are derived for the outage capacity algorithms.

This paper investigates the problem of minimizing the latency of iterative decoding of low-density parity check codes using the sum-product algorithm on a proposed low-complexity programmable pipelined parallel architecture. We present heuristic techniques for solving the NP-hard combinatorial optimization problems of mapping and scheduling the processing tasks of decoding an arbitrary LDPC code on n parallel pipelined processing units so as to minimize the total number of clock cycles required to complete a single decoding iteration. We compare the quality of result and running time of the proposed techniques to those of simple randomized techniques. We also investigate the effect of using local buffering at the pipelined processing units. In the case of zero local buffering, the proposed mapping and ordering techniques offer an improvement of 75.1% over randomized alternatives for the case of n=16. The proposed mapping technique always leads to an improvement of at least 11% over randomized mapping even if infinite local buffering is used. It is shown that a speedup factor of 1.12n-0.024n/sup 2/ can be achieved using a local buffer size of only 32 words.

This paper shows that under certain conditions the generalized decision feedback equalizer (GDFE) asymptotically converges to the infinite length minimum-mean-square-error decision feedback equalizer (MMSE-DFE), in the sense that both structures perform essentially the same signal processing operations at both the transmitter and the receiver. The GDFE (developed by Cioffi and Forney (1997)) is a multiple-input-multiple-output (MIMO) generalization of the well-known DFE structure, whose special cases include various transmission schemes such as discrete multi-tone (DMT). The proofs are based on a fundamental equivalence theorem holding between the Cholesky factorization of a doubly infinite Toeplitz covariance matrix and the spectral factorization of a stationary sequence. The results extend to the case where the optimum spectrum consists of several disjoint bands (which implies the operation of multiple corresponding independent MMSE-DFEs). The convergence of GDFE to the potentially many MMSE-DFEs requires performing a "generalized resampling" operation, which is equivalent to partitioning the available bandwidth into disjoint bands and eliminating the unused regions.

In this paper, transmit schemes for multi-antenna Gaussian multiple access channels are considered. For the case of a large number of users, a short term power constraint, and slowly fading channels, asymptotic optimality of beamforming is shown under the sum rate maximization criterion. This is an interesting result because the optimal transmit scheme for each user is to beamform to one direction even if each user is equipped with a large number of transmit antennas. Also, this result extends to ISI channels assuming OFDM modulation. A suboptimal transmit scheme based on this result follows for a system with partial channel side information.

This paper considers the vector Gaussian broadcast channel where a single transmitter with multiple antennas sends independent information to multiple receivers. An achievable rate region is derived by decomposing the broadcast channel into a series of single-user channels with non-causal side information. The side information may be completely pre-subtracted using precoding techniques. A practical trellis precoding method is presented. Trellis precoding can be viewed as a generalization of the Tomlinson-Harashima(1971, 1969) precoder. By taking into account the entire non-causal side-information sequence, a trellis precoder gives an additional shaping gain up to 1.53 dB compared to a Tomlinson precoder.

This paper investigates optimal power control in a frequency selective multiuser interference network. The power control problem is modeled as a non-cooperative game. The existence and uniqueness of a Nash equilibrium in the game is established, and an iterative water-filling algorithm is proposed to reach the Nash equilibrium efficiently. It is shown that the Nash equilibrium point corresponds to a competitively optimal power allocation in the interference network. Based on this result, an adaptive power control algorithm for upstream VDSL power back-off is developed. The power control algorithm takes into account the loop transfer functions and cross-couplings, and allows the loops to negotiate the best use of power and frequency. This new algorithm is found to have a substantial performance improvement when compared to current methods.

Near-end crosstalk (NEXT) is one of the major impairments to current ADSL downstream transmission. This paper presents two methods for an ADSL receiver to cancel one (dominant) NEXT signal from other types of services (such as HDSL, SDSL, T1 etc). The methods exploit the fact that the crosstalk signal has a large excess bandwidth and its spectra in the main lobe and in the excess band are strongly correlated. The principal idea is then to estimate the crosstalk in some frequency bands (e.g., excess band) and cancel it in other frequency bands (e.g., main lobe). Simulation results show that one of the proposed methods, MMSE estimation and cancellation, is very effective to cancel one (dominant) NEXT and the improvement is significant in terms of the data rate and the line reach for the ADSL service. For example, using a real measured NEXT transfer function, the proposed method can increase the ADSL downstream data rate by 200% for some loops.

This paper investigates the problem of blindly acquiring the channel gains for a synchronized multiuser system using the expectation maximization (EM) algorithm. The EM algorithm takes advantage of the finite alphabet property of the transmitted signal. It also provides MMSE estimates of the transmitted data that can be used by the receiver for decoding purposes. The algorithm has been applied to a multicarrier system and results show that the application of EM in the high SNR case provides significant improvement over traditional channel estimation techniques.

This paper describes a modulation scheme achieving far-end crosstalk (FEXT) cancellation, assuming that joint signal processing among the users can be performed at either the receiver or at the transmitter side. The multi-user channel is modeled as a multiple-input-multiple-output (MIMO) system, and the development starts with the zero-forcing generalized decision feedback equalizer (GDFE). Structures are derived, which combine the discrete multi-tone (DMT) transmission technique with either successive cancellation at the receiver or precoding at the transmitter. A promising application of the proposed scheme is in FEXT-limited digital subscriber line (DSL) systems. Computer simulations demonstrate that significant performance improvements can be realized in such scenarios.

We consider the problem of optimal power allocation for a broadcast channel with ISI under the FDMA restriction. Due to the FDMA restriction, the resulting problem is combinatorial in nature and hard to solve. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution and therefore, a characterization of the capacity region. It is also shown that under certain conditions on the channel responses, the optimal frequency partition has an ordered structure that can be exploited to further reduce the computational complexity.

We improve the bit error rate (BER) performance of block coded modulation (BCM) by simply introducing single parity check codes (SPCC). Two types of parity check operations are investigated. The proposed scheme is suited to parallel processing and only hard decision is needed in the decoding procedure. Computer simulation results are given to show the coding gains.

We present an algorithm for self-synchronizing all modems in a discrete multitone (DMT)-based very high-speed digital subscriber line (VDSL) system using the Zipper duplex method. This solves the problem with non-orthogonal near-end crosstalk (NEXT) that appears in systems with unsynchronized modems. The algorithm we present runs autonomously in each VDSL-modem. It uses the auto-correlation of the DMT-signal to determine the frame-offset of other users, and adjusts the own frame-timing to be better aligned with the other users. With our method all modems will be self-synchronized to within a small fraction of the total DMT frame-length. This self-synchronization suppresses the NEXT to a level far below the background noise-floor. This means that our self-synchronized system has the same performance as a system where all modems are perfectly synchronized to a master clock.

Accurate identification of crosstalk interferers can increase throughput by proper loading or multiuser detection. In some systems, such as cable based delivery systems, crosstalk channel characteristics are finite and static. Furthermore, the type of service on each line does not change. The combination of the type of service and the channel characteristic is known as a crosstalk profile. Specific methods are introduced that allow for the detection of a crosstalk profile and further minimize the probability of error in selecting from the set of possible crosstalk interference scenarios.

This paper investigates peak-to-average power ratio (PAR) reduction in block transmission systems when the effects of transmit filters are included. Two new algorithms are presented that reduce the PAR more than conventional PAR methods. These algorithms are shown to be effective in multicarrier modulation. An improvement of over 2 dB is shown for block lengths of size 256.

This paper derives a rigorous performance bound for the constant-power water-filling algorithm for ISI channels with multicarrier modulation and for i.i.d. fading channels with adaptive modulation. Based on the performance bound, a very-low complexity logarithm-free power allocation algorithm is proposed. Theoretical worst-case analysis and simulation show that the approximate water-filling scheme is close to optimal.

This paper characterizes the optimal power control method for maximum sum capacity in a multiple access fading channel with multiple transmitter and receiver antennas when perfect channel side information is available at both the transmitters and the receiver. The profound benefit of multi-antenna diversity is demonstrated by a dimension counting argument. The optimal power allocation strategy in a system with n transmit antennas for each user and m receive antennas is a combination of successive cancellation and a TDMA-like scheme where in each time slot the rank of the transmit signals r/sub k/ for all users must satisfy /spl Sigma//sub k/r/sub k/(r/sub k/+1)/spl les/m(m+1). Thus, the total number of users that are allowed to transmit simultaneously is constrained by the number of receiver antennas. Receiver diversity increases the total number of dimensions thus allowing more users to transmit at the same time. By contrast, transmitter diversity allows a single user to occupy multiple dimensions as to benefit its own transmission, thus having the effect of precluding simultaneous transmission by other users.

This paper presents two novel and efficient water-filling algorithms for a two-user Gaussian multiaccess channel with intersymbol interference. These algorithms efficiently compute the optimal transmit power spectral density (PSD) for each user and obtain the capacity region of the channel. One algorithm is developed for the special case where two users have the same priorities and is more efficient than prior work. Another algorithm is designed for the first time to compute the general case where two users have different priorities. Both algorithms use a binary search technique and each has a computational complexity of O(NlogN) where N is the number of subcarriers.

Turbo codes are applied to magnetic recoding channels by treating the channel as a rate-one convolutional code that requires a soft a posteriori probability (APP) detector for channel inputs. The complexity of conventional APP detectors, such as the BCJR algorithm or the soft-output Viterbi algorithm (SOVA), grows exponentially with the channel memory length. This paper derives a new APP module for binary intersymbol interference (ISI) channels based on minimum mean squared error (MMSE) decision-aided equalization (DAE), whose complexity grows linearly with the channel memory length, and it shows that the MMSE DAE is also optimal by the maximum a posteriori probability (MAP) criterion. The performance of the DAE is analyzed, and an implementable turbo-DAE structure is proposed. The reduction of channel APP detection complexity reaches 95% for a five-tap ISI channel when the DAE is applied. Simulations performed on partial response channels show close to optimum performance for this turbo-DAE structure. Error propagation of the DAE is also studied, and two fixed-delay solutions are proposed based on combining the DAE with the BCJR algorithm.

Crosstalk among telephone lines in the same or neighboring bundles is a major impairment in current xDSL systems. This paper proposes a novel idea of an impartial third party that identifies the crosstalk coupling functions among the twisted pairs in these xDSL systems. The crosstalk identification technique includes the following four major procedures: (1) the transmitted and received signals from each DSL modem for a predefined time period are collected and sent to the third party; (2) the signals are resampled according to the clock rate of the receiver of interest; (3) the signals' timing differences are estimated by cross correlation; and (4) the crosstalk coupling functions are estimated using the least-squares method. The performance of the cross correlation and least-squares methods is analyzed to determine the amount of data needed for identification. Simulation results show that the proposed methods can identify the crosstalk functions accurately and are consistent with theoretical analysis. These identified crosstalk functions can be used to significantly improve the data rate (e.g., multiuser detection) and to facilitate provisioning, maintenance, and diagnosis of the xDSL systems.

This paper investigates optimal constellation labeling in the context of the edge profile. A constellation's edge profile lists the minimum-distance edge for each binary symbol error. The paper introduces the symmetric-ultracomposite (SU) labeling structure and shows that this structure provides undominated edge profiles for 2/sup n/-PSK, 2/sup n/-PAM, and 2/sup 2n/-point square QAM. The SU structure is a generalization of the commonly used reflected binary Gray code. With the proper choice of basis vectors, SU labeling can support either set-partition or Gray-code labeling of 2/sup n/-PSK, 2/sup n/-PAM, and 2/sup 2n/-point square QAM. Notably, there are Gray-code and set-partition labelings that do not have the SU structure. These labelings yield inferior edge profiles. The SU structure does not apply to cross constellations. However, for any standard cross constellation with 32 or more points, a quasi-SU labeling structure can approximate the SU structure. With the correct choice of basis, quasi-SU labelings produce quasi-Gray labelings. However, the quasi-SU structure cannot support set-partition labeling. In fact, the quasi-SU structure provides a better edge profile than standard set-partition labeling. Thus, for cross constellations there is a choice between edge profile optimality and the group structure provided by set-partitioning. Here, the correct choice depends on whether the encoder trellis has parallel branches.

Certain blind channel estimation techniques allow the identification of the channel up to a scale or phase factor. This results in singularity of the Fisher information matrix (FIM). The Cramer-Rao bound, which is the inverse of the FIM, is then not defined. To regularize the estimation problem, one can impose constraints on the parameters. In general, many sets of constraints are possible but are not always relevant. We propose a constrained CRB, the pseudo-inverse of the FIM, which gives, for a minimum number of constraints, the lowest bound on the mean squared estimation error.

In this paper, a frequency selective NEXT cancellation algorithm for xDSL transmission is proposed. NEXT is cancelled by subtracting estimated noise from the received signal. An adaptive filter is used to estimate the band limited interference noise from the interference data. This algorithm is applied for a DSL application where asymmetric and symmetric services coexist. It showed about 40% improvement of transmission speed.

This paper presents a real-valued discrete multicarrier modulation approach that is based on the use of the discrete Hartley transform (DHT) and its inverse (IDHT) to perform the modulation and demodulation operations. Since the DHT and IDHT definitions are identical, we can use the same hardware or program to implement the modulator and demodulator of the proposed multicarrier method. As compared to the complex-valued discrete Fourier transform based multicarrier modulation method, the proposed one achieves the same transmission performance with reduced computational complexity and implementation cost.

This paper proposes to combine maximum-likelihood (ML) decoding and decision feedback equalization (DFE) for the Vertical Bell Laboratories Layered Space-Time (V-BLAST) system. In the new decoding algorithm, we perform ML decoding for the first p subchannels, and use the DFE procedure for the remaining subchannels. We mathematically show that the new decoding scheme increases the diversity order for the worst subchannel from 1 to p, and verify it by computer simulation. Also, we propose an ordering scheme which gives the best performance for the worst subchannel, and show that an SNR gain equal to the number of transmit antennas can be achieved by the suggested ordering.

This paper formulates the problem of embedded modulation applied to a multiuser multicarrier system. These embedded multiuser optimization problems are shown to be convex, for which globally optimal solutions can be computed efficiently. We also show that these embedded problems are convex relaxations of the combinatorial FDMA multiuser problems and thus provide performance bounds to the optimal and asymptotically optimal solutions proposed by Hoo, Tellado and Cioffi (see IEEE Global Telecommunications Conf. (Globecom), p.25-30, 1998 and IEEE PIMRC, p.278-82, 1998).

Through the use of the spatial diversity, wireless transmission system capacity can increase dramatically. However, in the multiple-user environment, the system performance is limited by co-channel interference. Beamforming is typically used to suppress the interference, but it is not always able to process a multipath signal optimally, especially when the paths from each user arrive in an alternating fashion. This paper describes a spatial multi-user detection scheme using singular value decomposition that can outperform beamforming and space-time equalization. This spatial detection scheme is compatible with TDMA, FDMA or CDMA and greatly enhances performance.

The paper proposes and investigates a new approach to adaptive spatio-temporal equalization for MIMO (multiple-input multiple-output) channels. A system with n transmit and m (m/spl ges/n) receiver antennas is assumed. A decision feedback equalizer is considered. A least squares solution is first formulated, based on which a recursive solution using Riccati recursions is proposed. The proposed solution is tested by simulating the MIMO system. It is shown that the adaptive solution achieves the same performance as the optimum least squares solution. The effect of the nondiagonal channel elements (acting as interference) on the system performance is also studied. It has been shown that in order to achieve better performance, the interference from nondiagonal channel elements needs to be minimized. This can be done by using orthogonal transmission. Moreover the proposed solution do not require channel identification and will also enable equalizer adaptation to channel changes.

We consider a block flat fading channel, where both the transmitter and receiver have perfect knowledge of the channel gain of the current block, but have no knowledge of future blocks. For a delay constraint of K blocks, and a target rate R/sub 0/, we derive the optimum power adaptation strategy that would minimize the probability of outage, which is equivalent to finding the outage capacity. Both, short term and long term power constraints are considered. Significant power gains are afforded by the strategy for all SNRs, even for small K.

This paper proposes a numerical method for characterizing the achievable rate region for a Gaussian multiple access channel with ISI under the frequency division multiple access restriction. The frequency spectrum is divided into discrete frequency bins and the discrete bin assignment problem is shown to have a convex programming relaxation, making it tractable to numerical algorithms. The run-time complexity may be further reduced in the two-user case if the two channels are identical, or if the signal-to-noise ratio is high.

This paper proposes an iterative soft interference cancellation scheme for a multiple antenna system. The proposed scheme is derived from the maximum a posteriori (MAP) criterion. At each iteration, the a posteriori probability is obtained by cancelling out the previous soft symbols, new soft symbols are calculated based on the a posteriori probability, and the total interference-plus-noise power is dynamically updated to account for the uncertainty in the soft symbols. The computational cost of the proposed algorithm grows linearly with the number of antennas while that of the optimum MAP detector grows exponentially. Simulations results show that an SNR gain of about 3 to 5 dB can be obtained by the proposed soft cancellation scheme.

We analyze the general problem of multiuser transmit optimization for a Gaussian broadcast channel with ISI under the FDMA restriction. Due to the FDMA restriction, the resulting problem is combinatorial in nature and hard to solve. However, by relaxing the FDMA restriction, we obtain a convex reformulation that allows for efficient computation of the optimal solution. By enforcing a constant-energy restriction, further reduction in computational complexity is achieved. We present the optimal and one suboptimal constant-energy method with bandwidth optimization. Simulation results show that these methods suffer from negligible performance loss even at low SNRs where the constant-energy approximation is not valid.

We investigate receive diversity for OFDM-based broadband communication systems. We consider the use of multiple antennas to combat time-selective fading and OFDM transmission in combination with an appropriate guard interval to suppress intersymbol interference. The receive diversity scheme is located in the frequency-domain and we derive different linear estimators, hereafter referred to as diversity equalizers. We show that the carrier-based solution for the optimum linear MMSE estimator-which is the least complex solution that maximizes the overall SNR is the well known maximum ratio combiner (MRC). Furthermore, we present a performance analysis for the proposed diversity equalizers and compare theoretical results to a simulated system which uses channel state information for MRC.

We discuss multiuser loading algorithms for maximum data rate-sum through a vector multiple access channel (MAC) with additive white Gaussian noise (AWGN). We prove that the maximum rate-sum can be obtained with very limited, if any, sharing of frequency and space dimensions of the channel between users, which significantly simplifies the optimal transmission technique and detection in case of two users. For arbitrarily narrow frequency subchannels, the maximum rate-sum in a two-user problem can always be achieved without having more than one user in each space-frequency channel dimension. The results apply, e.g., to single-input and multi-input multi-output (MIMO) wireless MAC channels with a small spread factor. The transmission efficiency is significantly improved in comparison with frequency-division multiple access (FDMA), the optimal transmission scheme for a scalar MAC.

Previous research has shown that the capacity of a multiple antenna system grows linearly with increasing number of antennas for rich-scattering environments. However, this is not true for wireless channels with a small number of independent paths. To overcome this problem, this paper investigates the possibility of exploiting the multiuser dimension with and without channel side information at the transmitter. First, the single user capacity per antenna is shown to converge to zero with increasing number of antennas for channels with a finite number of independent paths. Then multiuser capacity per antenna at the limit is shown to be positive. Simulation results are presented for a single user system and a multiuser uplink system.

In order to gain insights on equalization design in wireless mobile communication systems, we compare the performance of several multi-channel MLSE equalizers which adaptively track fast-fading channels. Commonly-used channel tracking schemes, decision-directed recursive least square (DD/RLS), per-survivor processing recursive least square (PSP/RLS) and other reduced-complexity MLSE algorithms are considered. Simulation results that illustrate the performance of the equalizers working with various channel tracking schemes are presented.

We derive the optimal bit and energy allocation for a discrete multitone (DMT) modulation system simultaneously providing two services with different quality of services (QoS), and show that it is NP-hard. Thus, we propose three novel, fast, discrete dual loading algorithms. These methods apply Campello's (see IEEE International Symposium on Info. Theory, MIT, p.193, 1998) discrete loading algorithms and are based on a novel tone selection procedure that offers significant reduction in complexity but still achieves near optimal performance. Simulation results support our tone selection procedure by indicating the convergence in performance of these loading algorithms to the optimum with increasing N, N being the number of subchannels or tones.

We show that high rate interleaved parity check (IPC) codes provide significant coding gain on the magnetic recording channel. A reduced complexity detector performing joint channel detection and IPC decoding is introduced. Simulation result shows an SNR gain of 1.6 dB for the E/sup 2/PR4 channel at a bit error rate of 10/sup -5/, using a rate 196/200 4-way interleaved parity check code.

We discuss the usage of space-time coding with multi-antenna transmission for a DS/CDMA system. We have considered an L-multipath, M-mobile antenna system in which the base station has a phased N-antenna array (i.e. fading at the base station antennas is completely correlated). We have shown that for the considered DS/CDMA system, for the channel with no ISI, adaptive antennas, with optimized transmit vector, can be combined with space-time coding (e.g. delay-diversity coding) to achieve a diversity gain of ML and a large coding gain whenever N/spl ges/L.

This paper derives probability density functions (PDFs) to describe the behavior of data demodulated with imperfect channel estimation. The PDFs apply to cases of flat Rayleigh-fading, multiple-diversity reception Rayleigh-fading, and flat Ricean-fading. These PDFs can be used to determine analytically both the symbol error rate and bit error rate for multi-amplitude constellations with in-phase and quadrature components, thus avoiding the need for extensive computer simulation.

Multi-carrier modulation is a modulation technique that enables higher transmission rate than traditional techniques, such as single-carrier quadrature amplitude modulation (QAM) systems. One implementation of multi-carrier modulation technique is discrete multi-tone (DMT). DMT used in asymmetric digital subscriber lines (ADSL) and very high speed DSL (VDSL) systems has a fixed cyclic prefix length. When the impulse response of the channel is longer than the designed prefix length, for instance when the length of the line impulse response is very long, distortion will appear at the channel output in the form of interference between the carriers. This paper describes a method to remove this distortion by introducing a precoder at the transmitter. Although there will be a power increase when the precoder is used, the distortion is significantly reduced, yielding a performance improvement.

A new procedure is proposed for solving the problem of channel shortening (a.k.a. the TEQ problem) for discrete multi tone (DMT) systems. Channel shortening is accomplished by using an multi-input-single-output (MISO) adaptive filter bank at the receiver. Each input represents a "logical path" from the transmitter to the receiver The "paths" are derived either via oversampling, or by using multiple analog to digital converters (A/Ds) with different sampling delays, or from A/Ds connected to different receive antennas (as may be the case in a wireless system). It is shown that for a finite order linear time invariant channel, it is always possible (provided certain conditions are met) to find a FIR filter bank combiner such that the effective length of the channel is no more than the cyclic prefix.

It is well known that the minimum mean square error (MMSE) and minimum peak distortion (MPD) criteria do not minimize bit error rate (MinBER), and for some channels they can have a large degradation compared to the MinBER solution. Based on the strengths and weaknesses of the MMSE and MPD criteria, we have defined two new solutions, which we call minimum noise limited peak distortion (MNLPD) and min-/spl alpha/. The first solution is based on MPD but avoids the problem of noise enhancement. The second solution finds the optimal of a family of equalizers derived from the MMSE and MPD criteria. We have shown by numerical calculation that by using the MNLPD or the min-/spl alpha/ criteria we can achieve almost MinBER performance. The proposed methods have a larger complexity, but can be solved using well known techniques since they can be described as simple convex optimization problems.

We propose a novel loading algorithm for discrete multitone (DMT) modulation or orthogonal frequency division multiplex (OFDM) systems simultaneously providing two constant bit rate (CBR) services. Furthermore, these two services have different quality of services (QoS) characterized respectively by their target bit error rates (BER). We derive the optimal solution and show that it is NP-hard. Thus, we propose a method namely, disjoint bandwidth (DBW) which is O(N log N) that still gives near optimal performance. The reduction in complexity is enabled by the set selection procedure we propose. Simulation results for frequency selective Rayleigh fading channels with additive white Gaussian noise show that the DBW method is within 0.1% of the optimum for a total number of carriers N>12 and that it performs on the average 15% better than any previously reported method in the literature.

Most multicarrier system designs assume perfect knowledge of the transmission channel. However in practice, the accuracy in channel identification is limited either by errors in channel estimation or by variations in the channel once it had been estimated. When not accounted for, these channel mismatch errors degrade the performance of our system and can lead to unacceptably high bit error rates. In this paper, we extend the existing multicarrier design concepts to systems with imperfect channel knowledge. We assume a Rayleigh fading channel, and study the impact of errors due to variations in the transmission channel. We develop a model for these errors, analyze their distribution, and derive analytic expressions for the probability of error of our system in the presence of these errors. We then extend the existing loading algorithms, taking into account the channel mismatch errors, and show the improvement in performance over the conventional multicarrier system designs.

Multipath signal propagation has long been viewed as an impairment to reliable communication in wireless channels. This paper shows that the presence of multipath greatly improves achievable data rate if the appropriate communication structure is employed. A compact model is developed for the multiple-input multiple-output (MIMO) dispersive spatially selective wireless communication channel. The multivariate information capacity is analyzed. For high signal-to-noise ratio (SNR) conditions, the MIMO channel can exhibit a capacity slope in bits per decibel of power increase that is proportional to the minimum of the number multipath components, the number of input antennas, or the number of output antennas. This desirable result is contrasted with the lower capacity slope of the well-studied case with multiple antennas at only one side of the radio link. A spatio-temporal vector-coding (STVC) communication structure is suggested as a means for achieving MIMO channel capacity. The complexity of STVC motivates a more practical reduced-complexity discrete matrix multitone (DMMT) space-frequency coding approach. Both of these structures are shown to be asymptotically optimum. An adaptive-lattice trellis-coding technique is suggested as a method for coding across the space and frequency dimensions that exist in the DMMT channel. Experimental examples that support the theoretical results are presented.

This article examines Tomlinson-Harashima precoding (1971, 1972) on discrete-time channels having intersymbol interference and additive white Gaussian noise. An exact expression for the maximum achievable information rate of zero-forcing (ZF) THP is derived as a function of the channel impulse response, the input power constraint, and the additive white Gaussian noise variance. Information rate bounds are provided for the minimum mean-square error (MMSE) THP. The performance of ZF-THP and MMSE-THP relative to each other and to channel capacity is explored in general and for some example channels. The importance of symbol rate to ZF-THP performance is demonstrated.

The sector error rate (SER) of the decision feedback equalizer (DFE) is analyzed for digital magnetic recording applications. In contrast to the detector bit error rate, the sector error rate is the probability of at least one bit error in a sector of N bits, after application of an error correcting code (ECC). Due to error propagation, the DFE produces long error bursts that exceed the typical correcting capabilities of hard disk drive ECC systems. We characterize this impairment in terms of the loss in recording density. We propose new optimization criteria that limit the energy of the DFE feedback filter, slightly increasing the probability of a burst error but greatly decreasing the probability of an uncorrectable burst. The constrained DFE regains 75% of the density lost to error propagation. Alternatively, the constraint provides up to 5 orders-of-magnitude in SER margin on a Lorentzian channel at a density of PW/sub 50/=3.0 T.

This paper presents the improvement obtained from using a discrete multitone approach for transmitting information over a time-invariant wireless channel. A scalar channel model similar to the well known Jakes model (1974) is assumed. Additive white Gaussian noise is also assumed. Flat energy is put across the entire band and the multitone signal-to-noise ratio and bit rate are computed. These values are compared with those obtained from using a discrete multitone approach and assigning bits only to the "good" portions of the band. Improvements in signal-to-noise ratio and in data rates are obtained using this method. Analytic expressions for the SNR and data rate improvements are also derived.

Advances in VLSI technology permit the use of interpolated timing recovery (ITR) as a replacement for the conventional VCO-based phase lock loop. Fully digital ITR has the advantage of lower cost and higher stability. In this paper, we present an interpolated timing recovery scheme that requires almost no oversampling, which should be suitable for high-speed storage channels.

A bandwidth-optimized and equalized multicarrier transceiver that achieves near-optimum performance at a practical complexity level is described. The equalizer used is a relatively short FIR filter whose taps and delay are set to optimize the performance of the multicarrier transceiver. Simulation results on a set of carrier-serving-area digital subscriber loops are also presented to demonstrate the separate and joint effects of bandwidth optimization and equalization on performance. Finally, the intriguing idea of using a pole-zero equalizer to achieve the high performance of long FIR equalizers at a much lower implementation cost is investigated.

The problem of approximating a long FIR filter by a reduced-parameter stable pole-zero filter is addressed. We derive a computationally efficient order-recursive algorithm that achieves this task with high accuracy. Our main emphasis is on applying this algorithm to reduce the implementation complexity of the decision feedback equalizer's long FIR feedforward and feedback filters encountered in high-speed data transmission on digital subscriber loops.

We simulate the performance of an equalized Gaussian minimum shift keying (GMSK) signal in an indoor radio environment with fading, noise, imperfect carrier recovery, cochannel interference (CCI), and intersymbol interference (ISI). We show that data rates of 20 Mb/s at bit error rates (BER) /spl les/10/sup -4/ are possible with root mean square (RMS) delay spreads up to 25 ns using a simple limiter-discriminator-integrator (LDI) receiver and a (6, 4) decision feedback equalizer (DFE). In environments with larger RMS delay spreads, coherent detection is required for the same performance. We show that using a decision-directed second-order digital carrier synchronizer with time varying loop filters, frequency offsets up to 200 kHz can be corrected with negligible performance degradation. This paper utilizes a DFE structure which compensates for both modulator and channel ISI, and yet requires no power-intensive multiplication operations in the feedback section. A DFE (8, 8) with two-level switched (selection) diversity is shown to allow 20 Mb/s data transfer at a BER/spl les/10/sup -4/ for RMS delay spreads under 150 ns, with CCI. A light BCH (26, 31) code allows error-free reception of over 90% of packets with RMS delay spreads under 150 ns, and up to 70% of packets with RMS delays of 150 ns.

A new criterion for partially-equalizing severe ISI channels to reduce the cyclic prefix overhead of the discrete multitone (DMT) transceiver, assuming a fixed transmission bandwidth, is introduced. The equalized DMT is shown to recover a significant portion of the performance loss incurred because of the use of a moderate-size FFT in the DMT to reduce latency and implementation cost. In particular, equalizers designed using our new criterion result in a higher DMT performance margin than traditional mean-square-error DMT equalizers. Finally, additional promising methods that further enhance the performance of the equalized DMT are investigated.

Multicarrier transmission methods have long been known to optimize the performance of data transceivers on bandlimited communication channels. One form of multicarrier transmission, known as discrete multitone modulation (DMT), is particularly attractive for its ability to be implemented using efficient digital signal processing techniques. Given a basic DMT system, it is possible to increase the aggregate data rate with full-duplex transmission using echo cancelation. However, DMT echo cancelation at first appears difficult because of the computational complexity required in a straightforward implementation to cancel the cross-echoes produced by each carrier into every carrier. This paper presents high-speed echo cancelation techniques for full-duplex data transmission using DMT systems. The techniques estimate the echo with a method of fast convolution that combines a complex multiply per tone with a short convolution in the time domain. In addition, the frequency-domain update of the echo parameters consists of one complex multiply per tap. As a result, these techniques can achieve much lower complexity than that required by traditional single-carrier technique, such as the least mean square (LMS) algorithm. This approach has been implemented for asymmetric digital subscriber line (ADSL) applications.

The transmission of high-speed data over severely band-limited channels may be accomplished through the use of discrete multitone (DMT) modulation, a modulation technique that has been proposed for a number of new applications. While the performance of a DMT system has been analyzed by a number of authors, these analyses ignore the effect of timing jitter on system performance. Timing jitter becomes an increasingly important concern as higher data rates are supported and larger constellations are allowed on the DMT subchannels. Hence, in this paper, we assume that synchronization is maintained by using a digital phase-locked loop to track a pilot carrier, Given this model, we derive error rate expressions for an uncoded DMT system operating in the presence of timing jitter, and we derive an expression for the interchannel distortion that results from a varying timing offset across the DMT symbol. In addition, we investigate the performance of trellis-coded DMT modulation in the presence of timing jitter. Practical examples from the asymmetric digital subscriber line (ADSL) service are used to illustrate various results.

Optimal transmit filters for packet-based data transmission on dispersive Gaussian-noise linear time-invariant channels are derived by maximizing the mutual information, subject to a fixed input power budget. A quasi-stationary approximation to the optimal nonstationary input covariance process is derived and shown to exhibit negligible mutual information loss from the optimal case, for situations of most practical interest. Moreover, this quasi-stationary approximation results in efficiently computed lattice or pole-zero implementations of the transmit filter. By considering the popular finite-impulse-response minimum-mean-square-error decision-feedback equalizer (FIR MMSE-DFE) as a receiver structure, we show that transmitter optimization results in an appreciable improvement in the decision-point signal-to-noise ratio. Finally, we show that, as the output blocklength becomes infinite, the optimum finite-dimensional nonstationary input covariance process converges to a stationary process whose power spectrum obeys the well-known water-pouring distribution.

A unified approach for computing the optimum settings of a length-N/sub f/ input-aided equalizer that minimizes the mean-square error between the equalized channel impulse response and a target impulse response of a given length N/sub b/ is presented. This approach offers more insight into the problem, easily accommodates correlation in the input and noise sequences, leads to significant computational savings, and allows us to analyze a variety of constraints on the target impulse response besides the standard unit-tap constraint. In particular, we show that imposing a unit-energy constraint results in a lower mean-square error at a comparable computational complexity. Furthermore, we show that, under the assumed constraint of finite-length filters, the relative delay between the equalizer and the target impulse response plays a crucial role in optimizing performance. We describe a new characterization of the optimum delay and show how to compute it. Finally, we derive reduced-parameter pole-zero models of the equalizer that achieve the high performance of a long all-zero equalizer at a much lower implementation cost.

In this correspondence we derive the finite-length, minimum mean-squared error decision feedback equalizer (MMSE-DFE). We include decision delay as an explicit parameter. Our derivation yields an algebraic interpretation of the effect of decision delay on DFE performance (measured by mean-squared error). It also allows the fast computation of the MMSE-DFE for several different values of both decision delay and the number of feedback taps. Our approach is especially useful for short filter lengths, when the decision delay can significantly affect DFE performance.

A bandwidth-optimized and equalized multicarrier transceiver that achieves near-optimum performance at a practical complexity level is described. The equalizer used is a relatively short FIR filter whose taps and delay are set to optimize the performance of the multicarrier transceiver. Simulation results on a set of carrier-serving-area subscriber loops are also presented to demonstrate the separate and joint effects of bandwidth optimization and equalization on performance. Finally, the intriguing idea of using a pole-zero equalizer to achieve the high performance of infinite-complexity FIR equalizers at a much lower implementation cost is investigated.

We simulate the performance of an equalized Gaussian minimum shift keying (GMSK) signal in an indoor radio environment with fading, noise, cochannel interference and intersymbol interference (ISI). We show that data rates of 20 Mbps at bit error rates (BER) /spl les/10/sup -4/ are possible with RMS delay spreads up to 25 ns using a simple limiter-discriminator-integrator receiver and a (6,4) decision feedback equalizer (DFE). In environments with larger RMS delay spreads, coherent detection is required for the same performance. We introduce a DFE structure which compensates for both modulator and channel ISI, and yet requires no power-intensive multiplication operations in the feedback section. An (8,8) DFE with 2-level switched (selection) diversity is shown to allow 20 Mbps data transfer at BER /spl les/10/sup -4/ for RMS delay spreads under 150 ns, with cochannel interference. Adding a (26,31) BCH code allows error-free reception of over 90% of packets with RMS delay spreads under 150 ns, and up to 70% of packets with RMS delays of 150 ns.

The discrete multitone (DMT) modulation is considered to be a viable transmission scheme for high-speed subscriber loop. In this paper, the fast algorithm for computing the equalizer settings derived in [1] is extended and applied for the DMT in high-speed subscriber loop. The channel pulse response is assumed to be given by the channel identification method, and then the equalizer filter settings are computed. In simulations, a fast algorithm for the symbol spaced equalizer in a colored noise channel is used. Simulation results performed in various CSA loops indicate that the fast algorithm yields the near-optimum settings for the DMT system

We investigate the use of a run-length-limited (RLL) sliding-block line code to reduce the effects of intersymbol interference in high-speed (multi-Gb/s) data transmission over the direct-detection single-mode optical fiber channel. In addition to their well-known use for synchronization purposes, line codes can be designed to eliminate certain worst-case patterns that would otherwise preclude reliable data transmission at high rates and very long fiber lengths. The code considered here prohibits isolated "one's" (the 010 pattern) from appearing in the transmitted sequence. Simulation results indicate that this code, coupled with a simple compensation scheme at the receiver, can significantly increase dispersion-limited data rates and/or fiber lengths for both externally modulated and directly modulated systems. While our emphasis is on one particular line code, we discuss sliding block coding for the optical fiber channel in a general context.>

In this paper, we present a finite-granularity, loading algorithm for a discrete multitone (DMT) modulation system. The proposed algorithm offers significant implementational advantages over the well-known water-pouring method and the earlier Hughes-Hartogs algorithm, while typically suffering only negligible performance degradation relative to the optimal solution. We also present simulation results of this loading algorithm applied to the newly proposed asymmetric digital subscriber lines (ADSL) service.>

The minimum mean-squared-error decision-feedback equalizer (MMSE-DFE) has properties that suggest that it is a canonical equalization structure for systems that combine equalization with coded modulation. The structure and performance of the MMSE-DFE are succinctly derived using linear-estimation-theoretic principles in this first part of this two-part paper. The front-end of the MMSE-DFE, called the "mean-square whitened matched filter" (MS-WMF), is preferable in some ways to a matched filter or a whitened matched filter as a canonical receiver front end. In a coded system, the feedback filter of the MMSE-DFE may be implemented in the transmitter using precoding. The MMSE-DFE can perform significantly better than a zero-forcing decision-feedback equalizer, particularly at moderate-to-low SNR's and on severe-ISI channels. The MMSE-DFE is biased. The optimum unbiased MMSE-DFE is the MMSE-DFE with the bias removed. Removing bias improves error probability, but reduces the SNR to SNR/sub MMSE-DFE,U/=SNR/sub MMSE-DFE/-1. It is shown that this SNR relationship is a particular case of a very general result and that SNR/sub MMSE-DFE,U/ gives a more realistic estimate of SNR. The results are extended to partial response equalization and to equalization with correlated inputs in an appendix.>

For pt.I see ibid., vol.43, no.10, p.2582 (1995). The minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE) has properties that suggest that it is a canonical equalization structure in systems that combine equalization with coded modulation. With a given symbol rate 1/T and transmit spectrum, the output signal-to-noise ratio SNR/sub MMSE-DFE,U/ of a MMSE-DFE with an unbiased decision rule is a single parameter that characterizes the channel for coding purposes. Indeed, the transmit spectrum that maximizes SNR/sub MMSE-DFE,U/ is the capacity-achieving (water-pouring) spectrum, and the capacity C(T) (in bits per two dimensions) is given by C(T)=log/sub 2/[1+SNR/sub MMSE-DFE,U/] regardless of the channel characteristics. The performance of a coded system with a MMSE-DFE equalization structure may be accurately estimated using the gain of the coding scheme at a given Pr(E). This performance is shown to be approximately the same as that of a multicarrier system using the same transmit spectrum and similar coding; such systems are known to be able to approach capacity arbitrarily closely. The MMSE-DFE can perform significantly better than a zero-forcing decision-feedback equalizer, particularly at moderate-to-low SNR's and on severe-ISI channels. Simulation results indicate that performance of the MMSE-DFE is surprisingly insensitive to transmit spectral shaping, as long as the transmit spectrum exceeds the capacity-achieving band, but that there is an optimal symbol rate that should (approximately) be used.>

A novel fast algorithm for computing the minimum MSE decision feedback equalizer settings is proposed. The equalizer filters are computed indirectly, first by estimating the channel, and then by computing the coefficients in the frequency domain with the discrete Fourier transform (DFT). Approximating the correlation matrices by circulant matrices facilitates the whole computation with very small performance loss. The fractionally spaced equalizer settings are derived. The performance of the fast algorithm is evaluated through simulation. The effects of the channel estimation error and finite precision arithmetic are briefly analyzed. Results of simulation show the superiority of the proposed scheme.

Shows how coding and constellation shaping may provide significant gains to a discrete multitone (DMT) system transmitting over spectrally-shaped channels. First, the authors present and analyze a concatenated coding scheme consisting of an inner trellis code and outer block code when applied to DMT modulation, and address some of the implementation issues associated with this scheme. Some laboratory test results for a DMT prototype employing the coding scheme are presented. Next, they propose a method for applying Forney's trellis shaper across the tones in a DMT system to realize significant shaping gain. To illustrate the coding and shaping gains achieved, they use scenarios indicative of the newly introduced asymmetric digital subscriber line service. By combining a powerful coding scheme, shaping, and DMT modulation, they arrive at an implementable transceiver that can provide very high data rates over spectrally-shaped channels.

This paper extends a number of results on the infinite-length minimum-mean-square-error decision Feedback equalizer (MMSE-DFE) reported by Cioffi, Dudevoir, Eyuboglu and Forney (see IEEE Trans. Commun., 1995) to the finite-length case. Cholesky factorization and displacement structure theory are demonstrated to be two powerful analytical tools for analyzing the finite-length MMSE-DFE. Our objective throughout the paper is to establish finite-length analogs of the well-known infinite-length MMSE-DFE results. Similarities and differences between the two cases are examined and delineated. Finally, convergence of our derived finite-length results to their well-established infinite-length counterparts is shown.>

We introduce a method for tracking a Rayleigh-fading channel with Orthogonal Frequency Division multiplexing (OFDM) so that multi-amplitude bit rate schemes such as 16 QAM may be used in a wireless channel. In addition, we derive a distribution to predict the symbol error rate of the modulation scheme. The modulation scheme is applied to an indoor wireless system operating at a rate of 25 Mb/s. The probability of error derived from simulation shows good agreement with the theoretically predicted probability of error. We keep a fairly large bit rate by using few training symbols; in simulation, the error propagation accounts for a slight increase in symbol error rate, but is not catastrophic due to the use of rotationally-invariant 16 QAM constellations.>

A data-driven echo canceller for full-duplex data transmission with multitone modulation is presented. This multitone echo canceller (MTEC) is not impaired by eigenvalue-spread problems that are inherent in signal-driven echo cancellers-it has numerical performance and cancellation range that equals, and in most cases exceeds, that of data-driven echo cancellers used in data transmission with baseband or quadrature amplitude modulation. The method makes use of frequency-domain updating, but time-domain implementation of the canceller. It introduces no delay into the received signal path and presents no special difficulties for interframe interpolation between near-end echo, far-end echo, or far-end data signal. The authors also investigate the fast initialization and the special case of far-end frequency offset in the echo signal.>

Computationally efficient algorithms are introduced for the real-time calculation of finite impulse response (FIR) equalizers for packet-based data transmission applications. It is found that a minimum mean-square-error decision feedback (MMSE-DFE) with arbitrary (finite) numbers of feedforward and feedback taps can be very efficiently computed from the channel response. The authors combine a recent theory of finite-spectral factorization for the MMSE-DFE with the theory of structured matrices to derive these efficient procedures for computing the equalizer settings. The method introduced is much more computationally efficient than direct computation by matrix inversion or than the use of popular gradient or least-squares algorithms over the duration of the packet.>

Combined equalization and coding approaches which significantly outperform previous techniques are presented for the binary Lorentzian channel with additive Gaussian noise. The authors develop a technique based on the concatenation of standard trellis codes with an equalization code and a block decision feedback equalizer (BDFE). Signal sets for the trellis code are generated by partitioning BDFE output vectors according to four- and eight-dimensional lattices. They also investigate the combination of a decision feedback equalizer (DFE) and a convolutional code (CC) and find that this system provides theoretical coding gains from 1 to 3 dB in the high linear recording density range of 2>

The capacity and cutoff rates for channels with linear intersymbol interference, power dependent crosstalk noise, and additive white noise are examined, focusing on high speed digital subscriber line data transmission. The effects of varying the level of additive white noise, crosstalk coupling gain, sampling rate, and input power levels are studied in detail for a set of simulated two-wire local loops. A closed-form expression for the shell constrained Gaussian cutoff rate on the crosstalk limited channel is developed and related to the capacity, showing that the relationship between these two rates is the same as on a channel without crosstalk noise. The study also projects achievable rates on a digital subscriber line, inside and outside of a carrier serving area, with a sophisticated but realizable receiver.>

The block-gradient (block LMS) algorithm's finite precision performance in the data-driven echo canceller application is analyzed. From both the analysis and simulation results, it was found that the block LMS requires significantly less precision than the standard LMS algorithm. The analysis also shows how higher convergence and tracking speeds may be traded for an improvement in precision requirements. The authors derive formulae that can be used to accurately compute echo rejection levels as a function of precision, signal powers, step-size, block length, and echo canceller length. The utility of the formulae is demonstrated by showing performance levels for a typical V.32bis full-duplex voiceband modem operating at a transmission rate of 14.4 kbit/s (7200 Hz sampling rate), and for a high-speed digital subscriber line echo canceller operating at a sampling rate of 400 kHz.>

The authors derive a procedure to send r bits on M parallel channels. A decomposition of the best constellation in Z/sup M/+(1/2, . . ., 1/2) is given in terms of the cross-products of lower dimensional shells of points. The proposed scheme can be used with good known coset codes to provide an alternate method of coded modulation. The results indicate that one can get good shaping gains for low encoder complexity. The method is also generalized for channels with unequal gains. The authors also find a significant performance advantage at fixed shaping gain, in certain cases, with respect to the recent Voronoi constellations in terms of peak-to-average power and constellation expansion.>

A discrete approach to multiple tone modulation is developed for digital communication channels with arbitrary intersymbol interference (ISI) and additive Gaussian noise. Multiple tone modulation is achieved through the concatenation of a finite block length modulator based on discrete Fourier transform (DFT) code vectors, and high gain coset or trellis codes. Symbol blocks from an inverse DFT (IDFT) are cyclically extended to generate ISI-free channel-output symbols that decompose the channel into a group of orthogonal and independent parallel subchannels. Asymptotic performance of this system is derived, and examples of asymptotic and finite block length coding gain performance for several channels are evaluated at different values of bits per sample. This discrete multiple tone technique is linear in both the modulation and the demodulation, and is free from the effects of error propagation that often afflict systems employing bandwidth-optimized decision feedback plus coset codes.>

A discrete multitone (DMT) transceiver design for high bit rate digital subscriber line (HDSL) access is presented and analyzed. The DMT transmitter and receiver structure and algorithms are detailed, and the computational requirements of DMT for HDSL are estimated. At a sampling rate of 640 kHz, using an appropriate combination of a short finite-impulse-response (FIR) equalizer and a length-512 DMT system, 1.6 Mb/s data transmission is possible within the carrier serving area (CSA) at an error rate of 10/sup -7/ on a single twisted pair. A significant performance margin can be achieved when two coordinated twisted pairs are used to deliver a total data rate of 1.6 Mb/s. In terms of a performance-per-computation figure of merit, the DMT system is an excellent candidate for HDSL implementation.>

The authors study the performance of a multichannel modulation method for asymmetric digital subscriber lines (ADSLs) and very high-speed digital subscriber lines (VHDSLs). In the ADSL case, over all unloaded North American subscriber lines in the test set, a unidirectional 1.536 Mb/s data rate service from the end office to the customer premises is possible on a single twisted pair at an error rate of 10/sup -7/ with at least a 6 dB margin used coded multichannel modulation with sufficient transmit power. In the VHDSL case, data rates in excess of 100 Mb/s can be transmitted reliably, at an error rate of 10/sup -7/, using uncoded multichannel modulation on a single twisted pair over a distance>

A modification of the decision feedback equalizer (DFE), RAM-DFE, is presented and analyzed for use in channels with trailing nonlinear intersymbol interference, especially binary saturation-recording channels. In the RAM-DFE, a look-up table, which can be easily implemented with random access memory, (RAM), replaces the transversal filter feedback section of the DFE. The feedforward section of the equalizer remains linear. A general nonlinear Markov (or finite-state machine) model is used to model the nonlinear intersymbol interference (ISI) channel. With this Markov model, a method is introduced for computing the minimum-mean-squared-error settings of the feedforward filter coefficients and the feedback filter and look-up table contents for the linear DFE and the RAM-DFE, respectively. RAM-DFE with these settings can be significantly better than the linear DFE for channels with trailing nonlinear ISI. Globally convergent gradient-type algorithms for updating the feedforward section coefficients and the contents of the feedback table are introduced and analyzed. Results based on data taken from disk storage units are discussed.>

The design of a high-speed adaptive decision feedback equalizer (DFE) is described for detection of magnetic disk data. A RAM is used in the feedback path instead of the usual transversal filter, and the equalizer is referred to as the RAM-DFE. The RAM compensates for trailing nonlinear distortion in the disk data. However, use of the RAM makes the equalizer more sensitive to latency in the adaptive update and can slow training considerably when using LMS adaptation. A technique is presented for training the RAM which reduces convergence time to near that of a transversal feedback filter. The RAM-DFE design is targeted for a VLSI implementation using BiCMOS technology. Simulation predict clock speeds in excess of 50 MHz, corresponding to data rates in excess of 50 Mb/s. The design also includes circuits to perform digital timing recovery and initial synchronization.>

A fast Householder filter (FHF) QR-RLS algorithm is presented that requires significantly less (by a factor of at least three) computation than previous fast QR-RLS adaptive algorithms. The essential feature of the new method is that it replaces the Givens rotations used in these fast QR algorithms by Householder transformations. A set of filters that characterize the QR factorization of a data matrix is derived, and time updates on this set are determined using a generic Householder updating identity. The FHF requires 7N computations per iteration for the standard prewindowed case, which is the same as the FTF (fast transversal filter) and FAEST fast (non-QR) RLS.>

Design of a high-speed adaptive decision feedback equalizer (DFE) for detection of magnetic disk data is described. A RAM is used in the feedback path instead of the usual transversal filter, and the equalizer is referred to as the RAM-DFE. The RAM compensates for trailing nonlinear intersymbol interference in the disk data. The structure and operation of the RAM-DFE is described, and it is shown that implementation of the RAM-DFT requires circuitry for timing recovery, gain adjustment, synchronization, and training. The overhead of these subsystems coupled with the high-speed requirements of risk drives makes implementational complexity a key design issue. The effects of finite precision, latency, implementation of the feedback path, and training on the performance and complexity of the system are discussed. The RAM-DFE has been designed on a single VLSI chip using BiCMOS technology. Simulations predict clock speeds in excess of 54 MHz, corresponding to data rates in excess of 54 Mbit/s.>

An investigation is conducted of the use of a fast-converging frequency-domain adjustment method for the echo canceller that conforms to the CCITT V.32 standard. The method requires no additional processor cycles (or cost increase) over that already required during steady-state operation of the V.32 modem, and reduces the training period to a maximum of 7.5 s, and nominally about 2.5 s. The presence of intermediate echoes can be detected naturally with the presented methods. Simple modifications of the new method are also introduced to accommodate special situations where intermediate echoes and/or frequency offset are present.>

A linear technique for combining equalization and coset codes on partial response channels with additive white Gaussian noise is developed. The technique, vector coding, uses a set of transmit filters or 'vectors' to partition the channel into an independent set of parallel intersymbol interference (ISI)-free channels for any given finite (or infinite) block length. The optimal transmit vectors for such channel partitioning are shown to be the eigenvectors of the channel covariance matrix for the specified block length, and the gains of the individual channels are the eigenvalues. An optimal bit allocation and energy distribution, are derived for the set of parallel channels, under an accurate extension of the continuous approximation for power in optimal multidimensional signal sets for constellations with unequal signal spacing in different dimensions. Examples are presented that demonstrate performance advantages with respect to zero-forcing decision feedback methods that use the same coset code on the same partial response channel. Only resampling the channel at an optimal rate and assuming no errors in the feedback path will bring the performance of the decision feedback methods up to the level of the vector coded system.>

A rectangular systolic array of processing units is presented for implementation of the QR adaptive filter. This array requires approximately 8N processing units to exactly solve the least-squares adaptive filtering problem using QR factorization. If a processing unit takes 50 ns to perform a task, the array can be implemented at an adaptive-filter input sampling rate of 20 MHz, with no loss in characteristic high performance (of least squares), numerical stability, or accuracy. This improves on widely used gradient methods for adaptive filtering, which must insert increasing amounts of performance-degrading delay into the adaptive updating when either the speed of implementation or number of taps increase. A discussion of the structure and interconnection of the processing units is included, as well as computer simulations that verify the stability and performance of the adaptive processing array.>

There has been considerable recent interest in QR factorization for recursive solution to the least-squares adaptive-filtering problem, mainly because of the good numerical properties of QR factorizations. Early work by Gentleman and Kung (1981) and McWhirter (1983) has produced triangular systolic arrays of N2/2 processors that solve the Recursive Least Squares (RLS) adaptive-filtering problem (where N is the size of the adaptive filter). Here, we introduce a more computationally efficient solution to the QR RLS problem that requires only O(N) computations per time update, when the input has the usual shift-invariant property. Thus, computation and implementation requirements are reduced by an order of magnitude. The new algorithms are based on a structure that is neither a transversal filter nor a lattice, but can be best characterized by a functionally equivalent set of parameters that represent the time-varying "least-squares frequency transforms" of the input sequences. Numerical stability can be insured by implementing computations as 2 × 2 orthogonal (Givens) rotations.

A recursive-least-squares (RLS) adaptive fast transversal filter (FTF) for processing of continuous-time signals is presented. It has the same structure as the discrete-time least-squares FTF, namely, a tapped-delay-line with time-varying gains, which are updated by propagating a set of coupled recursions. However, while the discrete-time scheme involves a fundamental unit of time (i.e., the sampling period of the signal), which determines both the duration of the delay and the rate of gain updating, our continuous-time scheme involves a delay of arbitrary duration and continuously-varying gains. Also, the conceptual and computational complexity of the continuous-time FTF is reduced in comparison to the to that of the discrete-time FTF. The rate of parameter updating in the continuous-time FTF configuration is essentially independent of the bandwidth and center frequency of the processed signal. Consequently, the gain-update module of the proposed algorithm can be implemented with slow devices (or with digital hardware), whereas the signal-path filter must match the frequency characteristics of the processed signal.

The important problem of Adaptive Line Enhancing (ALE) is addressed in this paper. Its solution involves an Adaptive Notch Filter (ANF) proposed in [1],[2] using a minimal parameter constrained infinite impulse response (IIR) model in conjunction with the Recursive Prediction Error Method (RPEM) [3]. A Fast Transversal Filter (FTF) algorithm for the adaptive RLS-type updating of the linear phase filter is presented.

"Covariance" or "unwindowed" Recursive Least Squares (RLS) adaptive algorithms are useful in applications where the input data cannot be assumed to be zero before application of these algorithms. Equivalently, the initial data inside the filter is nonzero before the very first iteration of the covariance RLS algorithm. Several computationally efficient covariance RLS algorithms have appeared in both lattice and transversal-filter form. However, the existing lattice algorithms have two problems that are remedied by the newly presented covariance-lattice RLS algorithm of this paper: First, the new algorithm permits a non-zero initial condition on the filter response (in addition to permitting the non-zero data), which is not permitted by any modification of the previous covariance-lattice RLS algorithms. Second, the new covariance-lattice algorithm can begin processing data at any point in time without the need for "warning" the algorithm (N-1) time samples in advance, as is required in all of the previous covariance-lattice algorithms. The new covariance lattice algorithm has an entirely different set of internal recursions in comparison to the previous algorithms, mainly because the order and number of terms in the sum of squared errors are unrelated during the computations comprising the new algorithm. An added benefit is that the new covariance-lattice RLS algorithm is also slightly more computationally efficient than the previous covariance-lattice RLS algorithms.

A new order-recursive least-squares algorithm for adaptive processing of discontinuous blocks of data is presented. For any one of these data blocks, the new algorithm is significantly more efficient in both total and "per-order" computation than any others that solve this same problem, including those recently introduced by Morf et al (1977), by Marple (1981), and by Kalouptsidis, Carayannis, and Manolakis (1985). In addition, the new numerically stable algorithm permits the recursive incorporation of new blocks of data, unlike those previous algorithms, which cannot be modified for use with more than one data block. The new algorithm does not vary block length with order during the intermediate computations for a particular block and is derived using the geometric Fast Transversal Filters (FTF) concepts that have also been used in time-recursive least-squares algorithms.

Computationally efficient recursive-least-squares (RLS) procedures are presented specifically for the adaptive adjustment of the data-driven echo cancellers (DDEC's) that are used in voiceband fullduplex data transmission. The methods are shown to yield very short learning times for the DDEC, while they also simultaneously reduce computational requirements to below those required for other leastsquare procedures, such as those recently proposed by Salz (1983). The new methods can be used with any training sequence over any number of iterations, unlike any of the previous fast-Converging methods. The methods are based upon the fast transversal filter (FTF) RLS adaptive filtering algorithms that were independently introduced by the authors of this paper; however, several special features of the DDEC are introduced and exploited to further reduce computation to the levels that would be required for slower-converging stochastic-gradient solutions. Several tradeoffs between computation, memory, learning time, and performance are also illuminated for the new initialization methods.

An efficient exact-least-squares procedure is presented specifically for the adaptive adjustment of a fractionally spaced equalizer (FSE). The intersymbol interpolation of the desired training sequence is used by this new procedure to reduce computational requirements and to improve convergence. For aT/pFSE (1/Tbeing the data symbol rate andpthe number of taps that span one symbol period), a factor ofpimprovement in "start-up" time is attained by this new procedure in comparison to the multichannel FSE versions of the "fast-Kalman" leastsquares algorithms of Falconer and Ljung [7] and in comparison to the Ling-Proakis [10] simplification for multichannel versions of the "fastlattice" least-squares algorithms of Satorius and Pack [8 ]Substantial reductions in computational and storage requirements are also achieved by the new procedure through the elimination of the inversion ofp \times pmatrices in these multichannel versions. Additional reductions in computational requirements are achieved by a special exact-least-squares modification for the passband "Nyquist" FSE structure of Mueller and Werner [6]. The procedure is shown to be most efficiently implemented using a transversal-filter realization of the fast exact-least-squares algorithmns. The per-iteration and per-unit-time computational requirements of the new procedure (T/4FSE) are found to be approximately the same as those of the more conventional, but much slower converging, (T/2) tap-leakage stochastic-gradient algorithms of Gitlin, Meadors, and Weinstein [15]. Finally, simulations are conducted to verify the operation of the new procedure for both the training and decision-directed modes of operation.

A unified theory is presented to characterize least-squares adaptive filters, in either lattice or transversal-filter form, for nonstationary processes. The derivations are based upon a geometric formulation of least-squares estimation and on the concept of displacement rank. A few basic geometric relations are shown to underlie the various algorithms. Insights into the fundamental concepts that unify lattice- and transversal-filter approaches to least-squares adaptive filters are also given. The general results are illustrated by applications to the so-called "pre-windowed" and "growing-memory covariance" formulations of the deterministic least-squares problem.

Fast, fixed-order, exact-least-squares algorithms for tapped-delay-line adaptive-filtering applications are presented in this paper. These new recursive algorithms require fewer operations per iteration and exhibit better numerical properties than the so-called Fast-Kalman algorithm of Ljung and Falconer [1978] and the unnormalized, least-squares, joint-process-lattice algorithms of Morf and Lee [1978]. In comparison with the currently used stochastic-gradient or LMS adaptive algorithm of Widrow and Hoff, the new, fixed-order, least-squares algorithms yield substantial improvements in transient behavior at a modest increase in computational complexity. Additionally, over a wide range of practical applications, the new algorithms demonstrate numerical properties comparable to those of the normalized lattice introduced by Lee, Morf, and Friedlander [1981], but at a considerable reduction in complexity.