In this article, we investigate the jointly optimized resource allocation with hybrid multiple access in energy-efficient industrial Internet of Things (IIoT), where some devices (e.g., those for critical control devices) have higher transmission priority and stable energy supply while some devices (e.g., those for comprehensive sensors) may not. We consider a system model supporting wireless powered IIoT devices, with certain user terminal as a potential relay for the transmission between a hybrid access point and another user terminal. Constrained by the limited energy storage, the user needs to harvest energy before relaying and only the harvested energy is utilized for the following transmission. We propose a collaborative orthogonal and nonorthogonal multiple access protocol where two cooperation schemes with and without decoding the relay message are applied. Jointly considering time sharing in the transmission process, power splitting for simultaneous wireless information and power transfer, and transmit power allocation at the cooperative user, the achievable rate regions under the Rayleigh fading channel model are derived. Based on which, an optimization problem on resource allocation strategies is formulated and discussed. Both analytical and numerical results are provided, illustrating the impact of user geometry on the achievable rates as well as the optimal resource allocation with different cooperative strategies applied in different use cases. Aiming to enhance resource utilization, energy-efficient cooperation enables the combination of various transmission modes and networking classes in large scale networks, as well as a better use of ambient radio frequency signals for wireless powered transmissions.

Hidden Markov model (HMM) has been successfully used for sequential data modeling problems. In this work, we propose to power the modeling capacity of HMM by bringing in neural network based generative models. The proposed model is termed as GenHMM. In the proposed GenHMM, each HMM hidden state is associated with a neural network based generative model that has tractability of exact likelihood and provides efficient likelihood computation. A generative model in GenHMM consists of mixture of generators that are realized by flow models. A learning algorithm for GenHMM is proposed in expectation-maximization framework. The convergence of the learning GenHMM is analyzed. We demonstrate the efficiency of GenHMM by classification tasks on practical sequential data. Code available at this https URL.

We propose two neural network based mixture models in this work. The proposed mixture models are explicit. The explicit models have analytical forms with the advantages of computing likelihood and efficiency of generating samples. Expectation-maximization based algorithms are developed for learning parameters of the proposed models. We provide sufficient conditions to realize the expectation-maximization based learning. The main requirements are invertibility of neural networks that are used as generators and Jacobian computation of functional form of the neural networks. The requirements are practically realized using a flow-based neural network. In our first mixture model, we use multiple flow-based neural networks as generators. Naturally the model is complex. A single latent variable is used as the common input to all the neural networks. The second mixture model uses a single flow-based neural network as a generator to reduce complexity. The single generator has a latent variable input that follows a Gaussian mixture distribution. The proposed models are verified via training with expectation-maximization based algorithms on practical datasets. We demonstrate efficiency of proposed mixture models through extensive experiments for generating samples and maximum likelihood based classification.

We investigate the use of entropy-regularized optimal transport (EOT) cost in developing generative models to learn implicit distributions. Two generative models are proposed. One uses EOT cost directly in an one-shot optimization problem and the other uses EOT cost iteratively in an adversarial game. The proposed generative models show improved performance over contemporary models on scores of sample based test.

In this paper, we study the characteristics of dominant interference power with directional reception in a random network modelled by a Poisson Point Process. Additionally, the Laplace functional of cumulative interference excluding the n dominant interferers is also derived, which turns out to be a generalization of omni-directional reception and complete accumulative interference. As an application of these results, we study the impact of directional receivers in random networks in terms of outage probability and error probability with queue length constraint.

In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm.

We consider cooperation in downlink non-orthogonal multiple access (NOMA) in a network supporting diverse communication modes. One user (UE2) exists as a potential relay between a base station (BS) and another user (UE1). With relaying the signal for UE1, UE2 obtains the opportunity for its own transmission to UE3 in D2D mode, meanwhile maintaining the transmission efficiency for UE1. On the basis of supporting different communication modes, we propose a NOMA-based cooperation scheme at UE2 to combine the relay message with its own. We derive achievable rate regions for two cases depending on the status of the Rayleigh fading channel of the UE2. We find solutions based on experiments through the transmit power allocation strategy at the UE2 and(/or) the BS. We show the impacts of our cooperative scheme and the corresponding user geometry on the achievable rates and the resource sharing strategies.

We consider optimized cooperation in joint orthogonal multiple access and nonorthogonal multiple access in industrial cognitive networks, in which lots of devices may have to share spectrum and some devices (e.g., those for critical control devices) have higher transmission priority, known as primary users. We consider one secondary transmitter (less important devices) as a potential relay between a primary transmitter and receiver pair. The choice of cooperation scheme differs in terms of use cases. With decode-and-forward relaying, the channel between the primary and secondary users limits the achievable rates especially when it experiences poor channel conditions. To alleviate this problem, we apply analog network coding to directly combine the received primary message for relaying with the secondary message. We find achievable rate regions for these two schemes over Rayleigh fading channels. We then investigate an optimization problem jointly considering orthogonal multiple access and nonorthogonal multiple access, where the secondary rate is maximized under the constraint of maintaining the primary rate. We find both analytical solutions as well as solutions based on experiments through the time sharing strategy between the primary and secondary system and the transmit power allocation strategy at the secondary transmitter. We show the performance improvements of exploiting analog network coding and the impacts of cooperative schemes and user geometry on achievable rates and resource sharing strategies.

A generalization of the ensemble of non-terminated systematic LDPC convolutional codes developed in our previous work is proposed that allows us to design codes with lower rates than the original structure. We show that over the BEC, the modified codes have improved asymptotic and finite-length behavior and we determine the operational anytime exponent. Having shown the advantages of lowering the rate of the code, we propose a feedback protocol that permits encoder and decoder to operate at a variable rate. The rate is set on-the-fly and depends on the decoding success of the decoder. We describe the construction of the variable rate code structure and demonstrate by simulations the superiority of the variable rate scheme as compared to a scheme using a fixed rate.

We consider the effective capacity performance measure of persistent- and truncated-retransmission schemes that can involve any combination of multiple transmissions per packet, multiple communication modes, or multiple packet communication. We present a structured unified analytical approach, based on a random walk model and recurrence relation formulation, and give exact effective capacity expressions for persistent hybrid automatic repeat request (HARQ) and for truncated-retransmission schemes. For the latter, effective capacity expressions are given for systems with finite (infinite) time horizon on an algebraic (spectral radius-based) form of a special block companion matrix. In contrast to prior HARQ models, assuming infinite time horizon, the proposed method does not involve a non-trivial per case modeling step. We give effective capacity expressions for several important cases that have not been addressed before, e.g., persistent-HARQ, truncated-HARQ, network-coded ARQ, two-mode-ARQ, and multilayer-ARQ. We propose an alternative quality-of-service-parameter (instead of the commonly used moment generating function parameter) that represents explicitly the target delay and the delay violation probability. This also enables the closed-form expressions for many of the studied systems. Moreover, we use the recently proposed matrix-exponential distributed modeling of wireless fading channels to provide the basis for numerous new effective capacity results for HARQ.

We propose a novel performance analysis framework for lossless- and truncated-hybrid automatic repeat request (HARQ) that enables neat, general, closed-form throughput expressions in a matrix exponential (ME) distribution form. This approach is applicable to all HARQ schemes for which the probability density function of the effective channel can be characterized by a rational Laplace transform, or equivalently, an ME-distribution. This includes, for example, repetition redundancy HARQ in ME distributed channels. Throughput expressions are also given for the K-truncated-HARQ N-fold diversity, ARQ N-fold diversity, and lossless-HARQ 2-fold diversity cases in the ME distributed channel. Schemes with effective channels of non-rational Laplace transforms, such as IR-HARQ, are explored using truncated continued fractions. A novel integration trick is developed for the integration of ME distributions with singular matrices and yields the simple throughput expression of lossless-HARQ. We also give general analytical expressions for the optimal throughput and optimal rate point that benefit from the compact ME-distribution form proposed.

This paper studies the asymptotic performance of multi-hop amplify-and-forward relay multiple-antenna communication channels. Each multi-antenna relay terminal in the considered network amplifies the received signal, sent by a source, and retransmits it upstream toward a destination. Achievable ergodic rates of the relay channel with both jointly optimal detection and decoding and practical separate-decoding receiver architectures for arbitrary signaling schemes, along with average bit error rates for various types of detectors are derived in the regime where the number of antennas at each terminal grows large without a bound. To overcome the difficulty of averaging over channel realizations, we apply a large-system analysis based on the replica method from statistical physics. The validity of the large-system analysis is further verified through Monte Carlo simulations of realistic finite-sized systems.

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a `binoisy' multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations.

We propose a rate-adaptive error-correction coding framework for transmission over finite-length block-fading channels, with causal channel state information at the transmitter. A dynamic programming optimization approach can be use to obtain the optimal rate adaptation strategy. A suboptimal rate adaptation strategy is developed for sequential random codes. Numerical results show that significant performance gains are achievable with the proposed adaptation scheme.

We consider an interference network with independent links, whose multi-antenna transmitters have access to an imperfect analog estimate of their local channels. Assuming that the receivers treat the interference as noise, we define the outage rate region as the set of rate-tuples that are achievable with a given probability and we characterize the boundary of the region for transmit beamforming. Our study shows that the Pareto-optimal beamforming vectors judiciously balance the desired signal power and the interference power based on the quality of the estimated channel state. Our analysis further reveals that, in contrast to the well-known results by Jorswieck, for the perfect channel side-information case, transmission at full power is not necessarily Pareto-optimal.

We investigate the erasure floor performance of distributed Luby transform (DLT) codes for transmission within a multi-source, single-relay, and single-destination erasure-link network. In general, Luby transform (LT) codes exhibit a high erasure floor due to poor minimum-distance properties, which can be improved by maximizing the minimum variable-node degree. The same behavior is observed for DLT codes, and therefore a new combining scheme at the relay is proposed to maximize the minimum variable-node degree in the decoding graph. Furthermore, the encoding process at the sources and the combining scheme at the relay are coordinated to improve the transmission overhead. To characterize the asymptotic performance of the proposed DLT codes, we derive closed-form density-evolution expressions, considering both lossless and lossy source-relay channels, respectively. To support the asymptotic analysis, we evaluate the performance of the proposed DLT codes by numerical examples and demonstrate that the numerical results correspond closely to the analysis. Significant improvements in both the erasure floor and transmission overhead are obtained for the proposed DLT codes, as compared to conventional DLT codes.

We study a multinode network, where a multi-antenna transmitter Tx communicates with its desired receiver Rx, whereas a cluster P ≡̂ {Px,n, n = 1, . .. ,N} of unintended nodes is disturbed by the Tx-Rx (TR) communication. To prevent severe performance degradation, we impose a constraint on the total interference that is inflicted at the nodes of P. The TR link contains a line-of-sight component, whereas the propagation environment for each Tx-Px,n link is shadowed. The Tx node is preprocessing the information sequence by means of a precoding matrix that is optimized to achieve the ergodic capacity under a constraint on the maximum admissible ergodic interference power, arriving on P. In this paper, we show that the optimum precoding strategy involves the transmission of a single stream over the precoding direction, i.e., the eigenvector of the precoding matrix, which corresponds to beamforming along the instantaneous direction of the TR-link channel. The solution of the remaining power allocation problem yields the optimal precoding matrix. For this setup, we provide an efficient stochastic characterization of the network, which allows us to obtain an analytical expression for the TR-link ergodic capacity; this problem has been previously open, even for the case of a single-antenna node Tx and a single-element set P. We complement the analysis by deriving the TR-link signal-to-noise ratio and the average bit error rate, which are associated with our transmission scheme. Numerical results corroborate the theoretical analysis and reveal an interplay between the network parameters and their impact on the TR-link performance.

Hardware impairments in radio-frequency components of a wireless system cause unavoidable distortions to transmission that are not captured by the conventional linear channel model. In this paper, a “binoisy” single-user multiple-input multiple-output (SU-MIMO) relation is considered where the additional distortions are modeled via an additive noise term at the transmit side. Through this extended SU-MIMO channel model, the effects of transceiver hardware impairments on the achievable rate of multi-antenna point-to-point systems are studied. Channel input distributions encompassing practical discrete modulation schemes, such as, QAM and PSK, as well as Gaussian signaling are covered. In addition, the impact of mismatched detection and decoding when the receiver has insufficient information about the non-idealities is investigated. The numerical results show that for realistic system parameters, the effects of transmit-side noise and mismatched decoding become significant only at high modulation orders.

In this paper, we consider throughput and rate optimized throughput for large-scale MIMO-(H)ARQ systems in i.i.d. complex Gaussian block fading channels. Exact analysis of large-scale MIMO is generally intractable, yet the field of random matrix theory has provided asymptotic expressions for the instantaneous channel capacity, which we propose for studying MIMO-(H)ARQ systems. Even with those expressions, closed-form results for the maximum throughput and optimal rate are not known. We therefore provide i) tight asymptotic lower and upper bounds, with a diminishing gap, for the optimal rate that is useful for the design of practical link adaptation algorithms, and ii) a tight asymptotic lower bound for the maximized throughput, suggesting the practical sufficiency of MIMO-ARQ, without any packet combining, over more complex MIMO-HARQ methods.

We consider the throughput performance of ARQ in interfering channels, where the signal of interest as well as the interferers are subject to independent distributed Nakagami-m block fading. The key contribution is the derivation of closed-form expressions for the rate-maximized throughput. For this purpose, we employ the powerful parameterization approach from [1], allowing the problem to be solved exactly in a closed-form. We also consider the scaled-power, and the interference-limited, case.

A cognitive radio network with a multiple-input single-output secondary link and a multi-antenna primary receiver is considered. The secondary transmitter steers its transmission into the direction of its intended destination in order to maximize the received signal-to-noise ratio. Under this beam-forming strategy, the power allocation is optimized to achieve the ergodic capacity under the constraint that the long-term interference, caused at the primary receiver, will not exceed a predefined threshold. Assuming line-of-sight communication (Rician fading) for the secondary link and Rayleigh fading for the secondary-to-primary link channel, we derive the exact closed-form expression for the ergodic capacity. Numerical results corroborate theoretical findings and illustrate the manifold impact of the system parameters into its performance.

The present paper studies the asymptotic performance of dual-hop amplify-and-forward multiple-input multiple-output relay communication systems. In the corresponding setup, a relay amplifies the signal received from a source, retransmitting it towards a destination, while the direct source-destination link is absent. Ergodic achievable rates under separate decoding, along with the average bit error rate under various detection schemes are derived in the regime where the number of antennas at each terminal grows without bound. To overcome the mathematical difficulty of averaging over both channel realizations and input signals we apply large-system analysis based on the replica method from statistical physics. The validity of the large-system analysis is further verified through Monte Carlo simulations, providing particularly good accuracy at low SNR.

Luby transform (LT) codes are a class of rateless codes that automatically adapt their rate to the quality of the communication channel. In the original LT codes, fixed check-node degree distributions are used to combine variable nodes uniformly at random to extend the code graph and produce code bits. Here we propose a different approach: we design a sequence of rate-compatible degree distributions, and develop an algorithm that produces code bits in a manner such that the resulting degree distributions follow the designed sequence. Using this new design framework, we develop low-complexity LT codes suitable for time-varying noisy channels. Performance and complexity of the proposed LT codes are measured in terms of bit error rate and average number of edges per information and coded bit, respectively. Numerical examples illustrate the resulting trade-off between performance and complexity of the designed LT codes.

We consider a scenario consisting of a primary and a secondary system, each represented by a pair of a transmitter and a receiver. The secondary transmitter assists in the retransmission of the primary message, which prevents the primary performance from being degraded by allowing the secondary system to access the transmission resources. Two network coding schemes applied in retransmission phase are investigated, the stationary network coding (SNC) scheme and the adaptive network coding (ANC) scheme. For each scheme we derive analytical results on packet throughput and infer that the ANC scheme outperforms the SNC scheme. We then provide a numerical performance comparison and a numerical optimization of the secondary packet throughput. Our main result shows cooperation can provide a significant performance improvement through effective network coding.

MOTIVATION: Estimation of bacterial community composition from a high-throughput sequenced sample is an important task in metagenomics applications. As the sample sequence data typically harbors reads of variable lengths and different levels of biological and technical noise, accurate statistical analysis of such data is challenging. Currently popular estimation methods are typically time-consuming in a desktop computing environment. RESULTS: Using sparsity enforcing methods from the general sparse signal processing field (such as compressed sensing), we derive a solution to the community composition estimation problem by a simultaneous assignment of all sample reads to a pre-processed reference database. A general statistical model based on kernel density estimation techniques is introduced for the assignment task, and the model solution is obtained using convex optimization tools. Further, we design a greedy algorithm solution for a fast solution. Our approach offers a reasonably fast community composition estimation method, which is shown to be more robust to input data variation than a recently introduced related method. AVAILABILITY AND IMPLEMENTATION: A platform-independent Matlab implementation of the method is freely available at http://www.ee.kth.se/ctsoftware; source code that does not require access to Matlab is currently being tested and will be made available later through the above Web site.

This paper investigates cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter can help the primary transmission, and it should also ensure that the primary message is not leaked to the secondary user. We consider two cognitive scenarios depending on whether the secondary transmitter knows the primary message or not. In the first case, the secondary transmitter is unaware of the primary transmitter's message and acts as a helping interferer to enhance the secrecy of the primary transmission, whereas in the second case, relaying of the primary message is also within its capabilities. First, we find achievable rate regions for these two scenarios in the case of AWGN channels. We then investigate three different optimization problems: the maximization of the primary rate, the maximization of the secondary rate and the minimization of the secondary transmit power. For these optimization problems, we find closed-form expressions in important special cases. Furthermore, we analyze the cooperation between the primary and secondary transmitters from a game-theoretic perspective. We model their interaction as a Stackelberg game, for which we define and find the Stackelberg equilibrium. Finally, we use numerical examples to illustrate the rate regions, the three optimizations, and the impact of the Stackelberg game on the achievable rates and on the transmission strategies of the secondary transmitter.

Here we propose an ensemble of non-terminated systematic LDPC convolutional codes with increasing memory, and show that, over the binary erasure channel (BEC), these codes achieve anytime reliability asymptotically when decoded with an expanding-window message-passing decoder. The corresponding anytime exponents are determined through protograph-based extrinsic information transfer charts. Fundamental complications arising when transmitting with finite block lengths are identified and a combinatorial performance analysis, when transmitting over a static BEC with a fixed number of erasures per codeword block, is developed. Based on the performance analysis, we explore the use of feedback for achieving anytime behavior with constraints on block length. To meet complexity constraints, with or without feedback, the code memory can be limited at the cost of an error floor emerging with a delay proportional to the memory constraint. Although the analysis is developed for a static BEC we show numerically that we can design efficient low-complexity finite-length codes with anytime properties even for the conventional BEC.

We focus on the design of distributed Luby transform (DLT) codes for erasure networks with multiple sources and multiple relays, communicating to a single destination. The erasure floor performance of DLT codes improves with the maximum degree of the relay-degree distribution. However, for conventional DLT codes, the maximum degree is upper bounded by the number of sources. An additional constraint is that the sources are required to have the same information block length. We introduce a D-bit buffer for each source-relay link, which allows the relay to select multiple encoded bits from the same source for the relay-encoding process; thus, the number of sources no longer limits the maximum degree at the relay. Furthermore, the introduction of buffers facilitates the use of different information block sizes across sources. Based on density evolution, we develop an asymptotic analytical framework for optimization of the relay-degree distribution. We further integrate techniques for unequal erasure protection into the optimization framework. The proposed codes are considered for both lossless and lossy source-relay links. Numerical examples show that there is no loss in erasure rate performance for transmission over lossy source-relay links, as compared with lossless links. Additional delays, however, may occur. The design framework and our contributions are demonstrated by a number of illustrative examples, showing the improvements obtained by the proposed buffer-based DLT codes.

This paper examines throughput performance, and its optimization, for lossless and truncated automatic repeat request (ARQ) schemes in Gaussian block fading channels. Specifically, ARQ, repetition redundancy, and in part also incremental redundancy-hybrid ARQ, are considered with various diversity schemes. We propose a parameterization-based method that allows (semi-)closed-form expressions, linking optimized throughput, optimal rate, and mean SNR, to be derived for any ARQ and repetition redundancy-HARQ method even when a non-parameterized closed-form does not exist. We derive numerous throughput and optimal throughput expressions for various ARQ schemes and diversity scenarios, potentially useful for benchmarking purposes or as design guidelines.

This paper characterizes achievable rate regions for the Gaussian partially cognitive interference channel with multiple cognitive pairs (K-PCIFC), where the cognitive transmitters know one part of the primary transmitter's message. We explore a novel methodology using the deterministic discrete superposition model (DSM). We find codes and their achievable rate regions in the DSM, and we show that they yield achievable rate regions in the Gaussian model. Our coding scheme in the DSM can be applied in general scenarios. We devise an achievable rate region for the K-PCIFC, which is within a constant gap to known outer bounds for K = 2 in the weak interference regime. From our expressions we derive guidelines for designing the cognitive link between the primary transmitter and the cognitive transmitters. Furthermore, we show that the gain from cognition diminishes for increasing K.

Presence of multiple antennas on both sides of a communication channel promises significant improvements in system throughput and power efficiency. In effect, a new class of large multiple-input multiple-output (MIMO) communication systems has recently emerged and attracted both scientific and industrial attention. To analyze these systems in realistic scenarios one has to include such aspects as co-channel interference, multiple access and spatial correlation. In this paper, we study the properties of correlated MIMO multiple-access channels in the presence of external interference. Using the replica method from statistical physics, we derive the ergodic sum-rate of the communication for arbitrary signal constellations when the numbers of antennas at both ends of the channel grow large. Based on these asymptotic expressions, we also address the problem of sum-rate maximization using statistical channel state information and linear precoding. The numerical results demonstrate that when the interfering terminals use discrete constellations, the resulting interference becomes easier to handle compared to Gaussian signals. Thus, it may be possible to accommodate more interfering transmitter-receiver pairs within the same area as compared to the case of Gaussian signals. In addition, we demonstrate numerically for the Gaussian and QPSK signaling schemes that it is possible to design precoder matrices that significantly improve the achievable rates at low-to-mid range of signal-to-noise ratios when compared to isotropic precoding.

This paper analyzes the impact of error propagation on the achievable throughput and throughput-delay tradeoff in wireless networks. It addresses the particular class of multihop routing schemes for parallel unicast that achieve a throughput scaling of Θ(n-1/2) per node in a network of n nodes. It is shown that in the finite-block-length case, necessitated by finite decoding memory at the nodes, the guaranteed per-node throughput in the network cannot scale better than o (n-r) per node for any r > 0. This bound on the guaranteed per-node throughput is tighter than the O (1/n) bound shown previously. Instead of focusing on the probability of error for each link, which is intractable, an approach of bounding mutual information is employed to show tight results on the achievable throughput and throughput-delay tradeoffs. It is shown that for multihop transmission protocols, error propagation leads to significant changes in the tradeoff between the throughput T(n) and the delay D(n), compared to previous results. The best known scaling behavior is only D(n) = Θ (n (log n) T(n)) under maximum throughput scaling, where the block length required scales as Ω (log n). When decoding memory at nodes is constrained to be O (log log n), the achievable tradeoff worsens to D(n) = Θ (n (log n)2T(n)).

The present paper investigates the achievable data rates of multi-hop amplify-and-forward multi-antenna relay channels with arbitrary number of hops K. Each multi-antenna terminal in the system amplifies the received signal and retransmits it upstream. To analyze the ergodic end-to-end mutual information of the system, one has to perform averaging over the fading coefficients. To overcome this difficulty we apply large-system analysis, based on the assumption that the number of antennas grows without bound at every terminal. Using the replica method, we derive an explicit asymptotic expression for the ergodic mutual information between the input and output of the K-hop channel with no restrictions on the channel inputs. Numerical results support the validity of the replica analysis and show that the result is tight even for small antenna arrays.

We propose a decode-forward protocol for streaming over a relay network using sequential random tree codes. An achievable bound on the end-to-end error performance is derived. The bound is parameterised by the number of errors occuring at the relay, which is the sum of correlated Bernoulli processes. The bound is useful for determining the achievable delay-exponent as well as for designing finite-delay relaying schemes. For a wide range of conjectured correlation models, the proposed scheme can achieve the delay-exponent of full source-relay cooperation.

Base station cooperation in cellular networks has been recently recognized as a key technology for mitigating interference, providing thus significant improvements in the system performance. In this paper, we consider a simple scenario consisting of two one-dimensional cells, where the base stations have fixed locations, while the user terminals are randomly distributed on a line. Exploiting the replica method from statistical physics, we derive the ergodic sum-rate under arbitrary signaling for both cooperative and non-cooperative scenarios, when the system size grows large. The obtained results are analytically tractable and can be used to optimize the system parameters in a simple manner. The numerical examples show that the analysis provides good approximations for finite-sized systems.

We propose an adaptive decoding scheme for Luby Transform (LT) codes over noisy channels which exhibits lower complexity as compared to the conventional LT decoder. The corresponding modified degree distributions have been derived for the low-complexity LT decoder. The complexity and performance comparison demonstrate that the decoding complexity can be reduced with negligible degradation in bit error rate performance.

The interference channel (IC) is the basic underlying channel model for many practical multi-terminal communication scenarios. Here, we consider a modified three-user IC with dual-antenna transmitters and receivers where we allow one receiver to have a finite-rate unidirectional link to another receiver. This kind of receiver-to-receiver link may exist in cellular networks with base-station backhaul. For this scenario we propose a scheme that combines the interference-cancellation capability of Alamouti codes with the subspace-overlapping property of interference alignment to achieve a sum-rate of three symbols/channel use. The scheme does also simultaneously provide a diversity gain of two for every symbol which significantly improves the bit-error rate performance compared to zero-forcing techniques.

We consider a pair of secondary users that coexist, in a cognitive network, with multiple primary user pairs. The secondary link is supplied with partial network side information (NSI), which comprises message side information and partial channel side information (CSI), available in different levels at both the transmitter and the receiver of the cognitive link. The cognitive transceiver design has to obey predefined quality-of-service (QoS) criteria, that need to be maintained at the primary receivers, and at the same time properly handle the incoming interference from each primary transmitter in order to establish reliable communication. In this framework, we investigate the design and performance of the combined beamforming and orthogonal space-time block coding (BOSTBC) strategy, whose merits are well-documented, as a candidate transmission scheme for the secondary link. We study both aspects, QoS and interference, of the composite problem and characterize how they affect the beamformer design and the cognitive link performance, in the presence of partial NSI. Further, we propose a CSI quality-dependent model for the QoS criteria which yields an interesting trade-off between the cognitive link design and the primary QoS. Numerical results illustrate the system performance in this framework.

In this paper we consider a scenario, where several mobile multi-antenna terminals communicate with a multi-antenna base station within a cellular communication system over the flat Rayleigh fading channel. In addition, several terminals from the neighboring cell cause interference. For such a scenario, we derive, using the replica method, the asymptotic sum-rate of the communication in the large-system limit for arbitrary signal constellations. Moreover, we show via numerical results that when the interfering terminals use a QPSK constellation, the resulting interference becomes easier to handle. In effect, we may be able to accumulate more interfering transmitter-receiver pairs within the same area as compared to the case of Gaussian signals. Monte-Carlo simulations show that the derived asymptotic expression matches well with the simulated values even for small numbers of antennas.

A multi-antenna cognitive radio network, with a single pair of primary users and a secondary broadcast channel, is considered. Under perfect channel state information (CSI), the rate-optimal strategy for the primary link is waterfilling, resulting in possibly unused dimensions. The secondary base station, supplied with perfect and global CSI, employs block diagonalization for interference-free message precoding and opportunistic interference alignment to avoid disturbing primary communication. In the absence of sufficient resources to serve all secondary users, a low complexity adaptive antenna selection strategy is proposed. This scheme constructs, in each time-slot, the set of active antennas by opportunistically reusing information and resources from the preceding selection round. Numerical results indicate a complexity reduction at a small rateloss penalty, in comparison with existing selection methods.

We propose a LDPC Convolutional Code ensemble together with an expanding-window message-passing decoder that asymptotically have anytime properties when used for streaming transmission on the binary erasure channel. We show analytically that the decoding erasure probability of these codes decays exponentially over decoding delay and determine the corresponding anytime exponents.

This paper explores the trade-off between cooperation and secrecy in cognitive radio networks. We consider a scenario consisting of a primary and a secondary system. In the simplest case, each system is represented by a pair of transmitter and receiver. We assume a secrecy constraint on the transmission in the sense that the message of the primary transmitter has to be concealed from the secondary receiver. Both situations where the secondary transmitter is aware and unaware of the primary message are investigated and compared. In the first case, the secondary transmitter helps by allocating power for jamming, which increases the secrecy of the first message. In the latter case, it can also act as a relay for the primary message, thus improving the reliability of the primary transmission. Furthermore, we extend our results to the scenario where the secondary system comprises multiple receivers. For each case we present achievable rate regions. We then provide numerical illustrations for these rate regions. Our main result is that, in spite of the secrecy constraint, cooperation is beneficial in terms of the achievable rates. In particular, the secondary system can achieve a significant rate without decreasing the primary rate below the benchmark rate achievable without the help of the secondary transmitter. Finally, we investigate the influence of the distances between users on the system's performance.

We consider a pair of secondary nodes (SU) coupled, in Z-topology, with multiple pairs of primary nodes (PU). The secondary (cognitive) transmitter is combining beamforming with orthogonal space-time block coding (BOSTBC) and operates under Quality-of-Service (QoS) constraints that must be guaranteed for the primary receivers (PURx). The cognitive link is designed assuming imperfect channel state information (CSI) for all links, available at the SU transmitter (SUTx). Under this premise we characterize the optimal design in terms of CSI quality and interference and evaluate their impact on the performance of BOSTBC transmission in underlay cognitive networks.

The sparse representation problem of recovering an N dimensional sparse vector x from M1-norm of x under the constraint y = Dx. In this paper, the performance of l1-reconstruction is analyzed, when the dictionary is bi-orthogonal D = [O1O2], where O1, O2are independent and drawn uniformly according to the Haar measure on the group of orthogonal M × M matrices. By an application of the replica method, we obtain the critical conditions under which perfect l1-recovery is possible with bi-orthogonal dictionaries.

This paper studies the asymptotic sum-rate of the primary network within the relay-assisted multi-antenna cognitive radio system performing amplify-and-forward relaying. The achievable sum-rates are derived in the large-system limit by means of the replica method. A closed-form expression for the sum-rate of the primary network is obtained for large antenna arrays as a function of parameters obtained by solving a set of fixed-point equations. Numerical simulations confirm the validity of the results even for systems with only a few antennas at each terminal.

We investigate the design and performance of spatially-coupled rateless codes. A modified encoding process is introduced for spatially-coupled Luby Transform (SCLT) codes which leads to an almost regular variable-node degree distribution at the encoding graph. The proposed SCLT codes outperform its counterparts significantly over binary erasure channels, particularly in the erasure floor region. To further improve the erasure floor performance, the approach of spatial coupling is then extended to Raptor codes by concatenating a high-rate pre-coder to the SCLT codes. It is shown that the spatial coupling improves the convergence threshold of Raptor codes. Different ensembles of spatially-coupled Raptor codes are constructed depending on whether pre-coders and/or LT codes are spatially-coupled. The performance of different ensembles of spatially-coupled Raptor codes is then evaluated and compared based on density evolution, leading to an improved spatially-coupled Raptor code in terms of convergence threshold and lower complexity.

Cooperative communication is shown to be an efficient method of combating fading in wireless networks. By ”sharing” their antennas cooperating single-antenna nodes create a virtual multi-antenna system and therefore, benefit from spatial diversity. Network coding being a particular cooperative communication technique provides substantial gains in data rate, especially in networks with many sink nodes. By allowing intermediate nodes of a network to mix the incoming data streams, one can achieve the multicast capacity. Recently, Xiao and Skoglund showed that binary network coding (BNC) is not optimal for multi-user multi-relay networks in terms of diversity and proposed diversity network coding (DNC) scheme that outperforms BNC approach. Following this approach we examine potential diversity gains of using the DNC scheme for multi-source line networks. We show that the DNC technique outperforms both conventional time-orthogonal transmission and the BNC scheme. Further, the problem of optimal scheduling of the transmission is explored. We formulate the optimization problem and propose efficient solutions. Numerical results are presented to support theoretical findings.

We study the error and diversity-multiplexing tradeoff (DMT) performance of a (secondary) multi-user relay network, where a class of finite field network codes are applied in the relays to efficiently provide spatial diversity. To eliminate spectral efficiency loss induced by half-duplex limitation we adopt the cognitive radio overlay spectrum sharing concept and consider aligning the relays' operation with that of a primary system. To compensate the interference introduced by the secondary relaying, the secondary destination also transmits the primary signals to boost the signal power of the primary system. We also consider exploiting Automatic Repeat Request (ARQ) feedback signals from the secondary destination to minimize the energy consumption of the secondary system. In addition, by allowing multiple secondary sources to transmit non-orthogonally, the performance can be further enhanced.

This paper studies the asymptotic outage performance of incremental redundancy automatic-repeat-request (INR-ARQ) transmission over multiple-input multiple-output (MIMO) block-fading channels with discrete input constellations. We first show that transmission with random codes using a discrete signal constellation across all transmit antennas achieves the optimal outage diversity given by the Singleton bound. The optimal SNR-exponent and outage diversity of INR-ARQ transmission over the MIMO block-fading channel are then analysed. We show that a significant gain in outage diversity is obtained by providing more than one bit feedback at each ARQ round. Thus, the outage performance of INR-ARQ transmission can be remarkably improved with minimal additional overhead. A practical feedback-and-power-adaptation rule is proposed for MIMO INR-ARQ, demonstrating the benefits provided by multibit feedback. Although the rule is sub-optimal in terms of outage performance, it achieves the optimal outage diversity.

We investigate the error floor performance of Luby Transform (LT) codes over the additive white Gaussian noise channel. We first derive a lower bound on the bit error rate for an LT code, which we subsequently use to show that the corresponding error floor is predominantly caused by low-degree variable nodes. Based on this observation, we propose a modified encoding scheme for LT codes that provides a lower error floor with no increase in encoding and decoding complexities. The convergence behavior of the proposed scheme is analyzed using extrinsic information transfer charts, and shown to be similar to the original LT code. Numerical examples demonstrate the improvements of the modified LT code as a stand-alone code and as a component code of a Raptor code.

We consider a base-station broadcasting a set of order-insensitive packets to a user population over packet-erasure channels. To improve efficiency we propose a relay-aided transmission scheme using instantaneously-decodable binary network coding. Our proposed scheme ensures that a coded packet can be immediately decoded at the user side without delay. Moreover, only binary operations are required in the encoding and decoding processes, which decrease the computational complex. We further analyze the performance of the resulting broadcast scheme, and show that significant improvements in transmission efficiency are obtained as compared to previously proposed ARQ and network-coding- based schemes.

New results on the achievable trade-off between the per-node throughput T(n) and the average delay D(n) in a static wireless network of n nodes are presented for physical link models. For links modeled by channels with additive white Gaussian noise with power-law attenuation, a trade-off of only D(n) = ⊖ (n (log n) T(n)) is guaranteed for T(n) = ⊖(n-½). This follows from showing that there is significant information loss in the network due to error propagation, unless the length of the channel code employed is sufficiently high. Constraining the block length to be bounded yields worse trade-offs: only ⊖(n (log n)2T(n)) is guaranteed for optimal throughput, provided there is rich fading diversity.

A layered wireless network is considered, where information is transmitted in a multi-hop MIMO-like fashion from the source node layer through several intermediate layers of nodes before reaching the sink node layer. Analog network coding is investigated as the network transmission strategy, exploiting the inherent superposition features of the wireless channel. A general myopic transmission protocol is proposed, allowing overhearing across several layers. Special cases are investigated in terms of diversity and bit error rate when using different types of linear detectors. Conditions for successful decoding of all source node messages at each sink node are derived.

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High- and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation.

We investigate efficient scheduling algorithms for a relay-aided broadcasting system using random network codes, where our objective is to maximize the transmission efficiency. The broadcast from a base-station (BS) is divided into an information phase and a redundancy phase, where the half-duplex relay assists in the redundancy phase. Time-division transmission is used over packet-erasure channels, where the erasure probabilities of the BS-to-relay and relay-to-user links are lower than the BS-to-user links. Following the information phase, each user provides feedback on the status of received packets to the BS and the relay, which in turn both generate redundancy packets for the redundancy phase. To improve efficiency, we formulate a scheduling problem for the transmissions of redundancy packets from the BS and the relay. We consider two scenarios; namely instantaneous feedback after each redundancy packet, and feedback after multiple redundancy packets. In the first case the schedule is determined using a greedy algorithm, while in the second case the schedule is determined using dynamic programming. To determine the performance with instantaneous feedback, we develop an analytic approach based on a Markov chain. Numerical results show that the transmission efficiency of the dynamic programming algorithm is close to the performance of the greedy algorithm, but requires significantly less feedback.

We consider serial concatenation of a Luby Transform (LT) code with a differential quadrature phase-shift-keying (DQPSK) modulator for transmission over an additive white Gaussian noise (AWGN) Channel. Assuming a target average rate for the operation of the rateless LT DQPSK scheme, the degree distribution of the LT code is optimized in terms of convergence threshold using extrinsic information transfer (EXIT) charts. From the EXIT chart analysis, we show that the proposed LT DQPSK scheme has a similar convergence performance, but lower complexity, as compared to a Raptor code with differential modulation, and a LDPC code optimized for DQPSK. The EXIT chart analysis framework is also applied to evaluate the throughput performance for the three schemes in terms of the average code rate as a function of the signal-to-noise ratio. The comparison demonstrates that the proposed structure is well-suited for adaptive-rate transmission over a wide range of rates.

An improved concatenated code structure, which generalizes parallel and serially concatenated convolutional codes is presented and investigated. The structure is ideal for designing low-complexity rate-compatible code families with good performance in both the waterfall and error floor regions. As an additional feature, the structure provides a unified analysis and design framework, which includes both parallel and serially concatenated codes as particular cases. We derive design criteria for the generalized class of concatenated convolutional codes based on union bounds for the error probability and extrinsic information transfer (EXIT) charts for the decoding threshold.

We consider the design of bilayer-expurgated low density parity-check (BE-LDPC) codes as part of a decode and-forward protocol for use over the full-duplex relay channel. A new ensemble of codes, termed multi-edge-type bilayer expurgated LDPC (MET-BE-LDPC) codes, is introduced where the BE-LDPC code design problem is transformed into the problem of optimizing the multinomials of a multi-edge-type LDPC code. We propose two design strategies for optimizing MET-BE-LDPC codes; the bilayer approach is preferred when the difference in SNR between the source-to-relay and the source to-destination channels is small, while the bilayer approach with intermediate rates is preferred when this difference is large. In both proposed design strategies multi-edge-type density evolution is used for code optimization. The resulting MET-BE-LDPC codes exhibit improved threshold and bit-error-rate performance as compared to previously reported bilayer LDPC codes.

We study the error probability of LDPC codes in delay-limited block-fading channels with channel state information (CSI) at the transmitter and the receiver. We derive the optimal power allocation algorithms for LDPC codes with specific degree distributions using multi-edge-type density evolution error boundaries. The resulting performance approaches the outage probability for a number of power constraints. Furthermore, we adapt the algorithm for finite-length codes and show that the proposed algorithm enables gains larger than 10 dB over uniform power allocation. The method is valid for general, possibly correlated, fading distributions. This represents the first analysis of specific LDPC codes over block-fading channels with full CSI.

We consider lower bounds on the rate-distortion performance for the binary erasure source(BES) introduced by Martinian and Yedidia, using sparse graph codes for compression. Our approach follows that of Kudekar and Urbanke, where lower bounds on the rate distortion performance of low-density generator matrix (LDGM) codes for the binary symmetric source(BSS) are derived. They introduced two methods for deriving lower bounds, namely the counting method and the test channel method. Based on numerical results they observed that the two methods lead to the same bound. We generalize these two methods for the BES and prove that indeed both methods lead to identical rate-distortion bounds for the BES and hence, also forthe BSS.

We investigate the design and use of systematic binary deterministic rateless (BDR) codes for information transmission over block-erasure broadcast channels. BDR codes are designed to obtain a level of maximal distance separable (MDS) properties, making these codes ideal for the considered broadcast scenario. For a certain number of encoded redundancy blocks, we derive an expression for the probability that the MDS properties are maintained. Moreover, if limited feedback is available, we extend the BDR coding protocol to further improve the system performance. Numerical results show that for a finite number of source blocks and as the number of users grows the proposed systematic BDR codes performs significantly better than LT codes. The proposed schemes with feedback have better performance than traditional ARQ schemes.

We formulate the maximum a posteriori (MAP) rule for the decode-and-forward transmission strategy operating with a noisy relay. From the MAP rule we derive an analytical bound on the error probability, taking into account decoding errors at the relay. We further determine a practical close-to-MAP decoding scheme based on a convenient error model for the decoding operation at the relay. This error model allows for a trellis representation of the code described jointly by the encoding process at the source and the re-encoding process at the relay. Numerical results demonstrate a close agreement between our analytical results and monte carlo simulations.

We study the outage diversity of the multiple-input multiple-output (MIMO) Rayleigh block-fading channel when causal channel state information (CSI) is available at the transmitter (CSIT). Within this setting, we consider the optimal power allocation for blocks b = 1, ..., B given perfect CSIT for blocks 1, ..., b-u only, subject to a long-term power constraint. The parameter 0 ≤ u ≤ B is a fixed arbitrary integer that determines the delay in acquiring perfect knowledge of the CSI at the transmitter. Without explicitly solving the optimal power allocation problem, we derive the outage diversity of the system. For general 0 ≤ u ≤ B, we derive a simple recursive expression for computing the outage diversity. For the special case u = 0, it is shown that the outage diversity is infinite, coinciding with previously known results. For 1 ≤ u ≤ B, the outage diversity becomes finite and for the special case of u = 1, 2 it can be expressed in simple closed form.

We consider the Binary Erasure Source (BES) introduced by Martinian and Yedidia. Based on the technique introduced by Martinian and Wainwright, we upper bound the rate-distortion performance of the check regular Poisson LDGM ensemble and the compound LDGM-LDPC ensemble for the BES. We also show that there exist compound LDGM-LDPC codes, with degrees independent of the block-length, which can achieve any given point on the Shannon rate-distortion curve of the BES.

We investigate a relay-aided multi-cell broadcasting system using random network codes, where the focus is on devising efficient scheduling algorithms between relay and base stations. Two scheduling algorithms are proposed based on different feedback strategies; namely, a one-step scheduling algorithm with instantaneous feedback for each redundancy packet; and a multi-step scheduling algorithm with feedback only after multiple redundancy packets. For the latter case, dynamic programming is applied to determine optimal scheduling. Numerical results show that the transmission efficiency of the multi-step algorithm approaches that of the one-step algorithm, but requires significantly less feedback. They both significantly outperform corresponding ARQ and random scheduling approaches.

It has been shown in the literature that network coding can improve the transmission efficiency of wireless broadcasting as compared to traditional ARQ schemes. In this paper, we propose an improved network coding scheme that can asymptotically achieve the theoretical lower bound on transmission overhead for a sufficiently large number of information blocks. The proposed scheme makes use of an index allocation algorithm that distributes information blocks that have been erased during transmission into a minimum number of encoding sets, where each set represents the erased blocks to be jointly network encoded and retransmitted. Numerical results show that the proposed scheme enables higher transmission efficiencies than traditional ARQ, and previously proposed networks coding schemes for wireless broadcasting.

Power allocation is studied for fixed-rate transmission over block-fading channels with arbitrary continuous fading distributions and perfect transmitter and receiver channel state information. Both short- and long-term power constraints for arbitrary input distributions are considered. Optimal power allocation schemes are shown to be direct applications of previous results in the literature. It is shown that the short- and long-term outage exponents for arbitrary input distributions are related through a simple formula. The formula is useful to predict when the delay-limited capacity is positive. Furthermore, this characterization is useful for the design of efficient coding schemes for this relevant channel model.

A novel adaptive binary decoding algorithm for LDPC codes is proposed, which reduces the decoding complexity while having a comparable or even better performance than corresponding non-adaptive alternatives. In each iteration the variable node decoders use the binary check node decoders multiple times; each single use is referred to as a sub-iteration. To process the sequences of binary messages in each iteration, the variable node decoders employ pre-computed look-up tables. These look-up tables as well as the number of sub-iterations per iteration are dynamically adapted during the decoding process based on the decoder state, represented by the mutual information between the current messages and the syndrome bits. The look-up tables and the number of sub-iterations per iteration are determined and optimized using density evolution. The performance and the complexity of the proposed adaptive decoding algorithm is exemplified by simulations.

We consider improving the outage performance of incremental-redundancy automatic repeat request (INR-ARQ) transmission over the multiple-input multiple-output (MIMO) block-fading channel by allowing multi-bit receiver feedback. We show that multi-bit feedback offers significant gain in outage diversity when power adaptation is employed. A suboptimal feedback and power adaptation rule is proposed, illustrating the benefits provided by multi-bit feedback.

The performance of bit-interleaved coded modulation (BICM) with (or without) iterative decoding (ID) is significantly influenced by the mapping of bits to the symbol constellation. Our main objective in this paper is to develop a systematic design approach for BICM-ID schemes, ensuring the best possible performance with iterative decoding. Although useful mappings for BICM-ID have been found based on various search strategies, no attempt has been made to systematically enumerate and classify all unique mappers for a given constellation. As the basis for a systematic enumeration and classification, we define the average bit-wise distance spectrum for a mapping from bits to symbols. Different bit-wise distance spectra are derived assuming no prior information or full prior information, respectively. The bit-wise distance spectra determine corresponding bit-wise error probability and bit-wise mutual information. The latter allows us to use the classification of mappings with unique bit-wise distance spectra to also classify mappings with unique extremal points in the corresponding extrinsic information transfer (EXIT) curves. As an example of our approach, we classify 8PSK mappings into 86 classes of unique mappings according to bit-wise distance spectra. The classification can be used to significantly reduce the complexity of the search for suitable mappers for BICM-ID. For 8PSK and a given encoder, only 86 different mappings need to be investigated. As examples of the systematic design approach, the best 8PSK mappings for minimizing the convergence threshold are found for concatenation with the rate 1/2 (5,7)8 and (133,171)8 convolutional codes, and the rate 1/2 UMTS turbo code with identical constituent convolutional codes (15/13)8.

We propose a systematic design framework for optimal, low-complexity punctured multiple parallel concatenated codes (MPCCs), based on minimizing the convergence threshold using extrinsic information transfer (EXIT) charts. As the convergence threshold is related to the area between the two EXIT curves, the corresponding optimization problem is equivalent to a curve-fitting problem. The EXIT curves are determined by the respective EXIT functions of the constituents, which can be conveniently shaped through the use of random puncturing and unequal energy allocations across parallel coding streams. The design task is therefore to find the optimal combination of constituents, puncturing ratios, and energy allocation for matching the EXIT curves. A search over all rate-one convolutional codes of memory length four or less is performed, identifying 98 classes of codes with unique EXIT functions out of a total of 310 codes. Low-complexity MPCCs with up to four constituents are found, where the convergence thresholds are observed to be within 0.1 dB or less of the fundamental minimum signal-to-noise ratio (SNR) corresponding to the binary phase-shift keying (BPSK) capacity for code rates1/3lesRles 7/8. Further allowing for unequal energy allocation, the convergence thresholds for lower code rates are similarly improved.

We consider power allocation strategies for arbitrary input channels with peak, average and peak-to-average power ratio (PAPR) constraints. We are focusing on systems with a fixed and finite input constellation, as encountered in most practical systems. Generalizing previous results, we derive the optimal power allocation scheme that minimizes the outage probability of block-fading channels with arbitrary input constellations, subject to PAPR constraints. We further show that the signal-to-noise ratio exponent for any finite peak-to-average power ratio is the same as that of the peak-power limited problem, resulting in an error floor. We also derive the optimal power allocation strategies that maximize the ergodic capacity for arbitrary input channels, subject to average and PAPR constraints.We show that capacities with peak-to-average power ratio constraints, even for small ratios, are close to capacities without peak-power restrictions. For both delay-limited and ergodic block-fading channels, the optimal power allocation strategies rely on the first derivative of the input-output mutual information, which may be computationally prohibitive for efficient practical implementation. To overcome this limitation, we develop suboptimal power allocation schemes that resemble the traditional water-filling technique. The suboptimal power allocation schemes significantly reduce computational and storage requirements, while enjoying minimal performance losses as compared to optimal schemes.

Power allocation with peak-to-average power constraints over Nakagami-m block-fading channels with arbitrary input distributions is studied. In particular, we find the solution to the minimum outage power allocation scheme with peak-to-average power constraints and arbitrary input distributions, and show that the signal-to-noise ratio exponent for any systems with a finite peak-to-average power ratio constraint is the same as that of systems with peak-power constraints, resulting in an error floor.

We characterize the asymptotic outage performance of power allocation techniques for systems with average power constraints. We show that the outage diversity of a system with average power constraints can be obtained from the diversity of the corresponding system with peak power constraints. The characterization is therefore useful since the asymptotic performance of systems with peak power constraints is well known in the literature.

In this paper, a theoretical framework of divergence minimization (DM) is applied to derive iterative receiver algorithms for coded CDMA systems. The DM receiver obtained performs joint channel estimation, multiuser decoding, and noise- covariance estimation. While its structure is similar to that of many ad-hoc receivers in the literature, the DM receiver is the result of applying a formal framework for optimization without further simplifications, namely the DM approach with a factorizable auxiliary model distribution. The well-known expectation- maximization (EM) algorithm and space-alternating generalized expectation-maximization (SAGE) algorithm are special cases of degenerate model distributions within the DM framework. Furthermore, many ad-hoc receiver structures from literature are shown to represent approximations of the proposed DM receiver. The DM receiver has four interesting properties that all result directly from applying the formal framework: (i) The covariances of all estimates involved are taken into account, (ii) The residual interference after interference cancellation is handled by the noise-covariance estimation as opposed to by LMMSE filters in other receivers, (iii) Posterior probabilities of the code symbols are employed rather than extrinsic probabilities, (iv) The iterative receiver is guaranteed to converge in divergence. The theoretical insights are illustrated by simulation results.

In this paper, we consider an automatic-repeat-request (ARQ) retransmission protocol signaling over a block-fading multiple-input–multiple-output (MIMO) channel. Unlike previous work, we allow for multiple fading blocks within each transmission (ARQ round), and we constrain the transmitter to fixed rate codes constructed over complex signal constellations. In particular, we examine the general case of average input-power-constrained constellations with a fixed signaling alphabet of finite cardinality. This scenario is a suitable model for practical wireless communications systems employing orthogonal frequency division multiplexing (OFDM) techniques over a MIMO ARQ channel. Two cases of fading dynamics are considered, namely, short-term static fading where channel fading gains change randomly for each ARQ round, and long-term static fading where channel fading gains remain constant over all ARQ rounds pertaining to a given message. As our main result, we prove that for the block-fading MIMO ARQ channel with a fixed signaling alphabet satisfying a short-term power constraint, the optimal signal-to-noise ratio (SNR) exponent is given by a modified Singleton bound, relating all the system parameters. To demonstrate the practical significance of the theoretical analysis, we present numerical results showing that practical Singleton-bound-achieving maximum distance separable codes achieve the optimal SNR exponent.

The performance of bit-interleaved coded modulation with iterative decoding is significantly influenced by the mapping of bits to the symbol constellation. A range of mappers have been suggested in the literature, however, no attempt has been made to systematically enumerate all unique mappers for a given signal constellation. In this paper, we classify 8PSK mappers based on bit-wise distance spectra for no prior information, and full prior information, respectively.

In this paper, we consider an automatic-repeat-request (ARQ) retransmission protocol signaling over a block-fading multiple-input, multiple-output (MIMO) channel. In particular, we consider fixed rate codes constructed over discrete complex signal constellations. We show that the optimal signal-to-noise ratio (SNR) exponent is given by a modified Singleton bound, relating all the system parameters. To demonstrate the practical significance of the theoretical analysis, we present numerical results showing that practical Singleton-bound-achieving maximum distance separable codes achieve the optimal SNR exponent.

In this paper, we propose a tight lower bound to the outage probability of Nakagami-m block-fading channels. The approach permits an efficient method for numerical evaluation of the bound, providing an additional tool for system design. The optimal rate-diversity trade-off for the Nakagami-m block-fading channel is also derived and a tight upper bound is obtained for the optimal coding gain constant.

In this correspondence, a tight lower bound to the outage probability of discrete-input Nakagami-$m$block-fading channels is proposed. The approach permits an efficient method for numerical evaluation of the bound, providing an additional tool for system design. The optimal rate-diversity tradeoff for the Nakagami-$m$block-fading channel is also derived and a tight upper bound is obtained for the optimal coding gain constant.

In this paper a simplified parallel belief propagation (BP) algorithm is suggested as a suboptimal soft-input soft-output multiuser detector in an iterative multiuser decoding scheme. The iterative decoding scheme itself is based on applying an outer BP algorithm for message passing between the BP multiuser detector and the single-user decoders. The performance of the iterative decoding process is investigated based on parallel scheduling of the outer BP algorithm. In addition, we analyze the large system BER performance of the corresponding multiuser decoding algorithms. By making Gaussian assumptions on the output of the single-user decoders and the BP multiuser detector, we derive expressions which describe approximately the BER performance of the algorithms. Finally, numerical examples are presented, demonstrating the accuracy of this approximation

In this paper, a class of nonlinear minimum mean-squared error multiuser detectors is derived based on a multivariate Gaussian approximation of the multiple-access interference for large systems. This approach leads to expressions identical to those describing the probabilistic data association (PDA) detector, thus providing an alternative analytical justification for this structure. A simplification to the PDA detector based on approximating the covariance matrix of the multivariate Gaussian distribution is suggested, resulting in a soft interference-cancellation scheme. Corresponding multiuser soft-input, soft-output detectors delivering extrinsic log-likelihood ratios are derived for application in iterative multiuser decoders. Finally, a large-system performance analysis is conducted for the simplified PDA, showing that the bit-error rate (BER) performance of this detector can be accurately predicted and related to the replica method analysis for the optimal detector. Methods from statistical neurodynamics are shown to provide a closely related alternative large-system prediction. Numerical results demonstrate that for large systems, the BER is accurately predicted by the analysis and found to be close to optimal performance.

In this paper we show how to find optimal energy distribution together with optimal puncturing ratios for parallel concatenated codes with two or more constituent codes. The energy distribution and the puncturing ratios are optimal in terms of minimizing the average signal-to-noise ratio convergence threshold. The extrinsic information transfer functions of the constituent codes are used for the optimization. Using this technique we obtain additional degrees of freedom for constructing codes with low convergence thresholds over a large range of code rates.

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise standard deviation, channel reliability constant and bit-error rate are derived and it is shown how these parameters relate to the signal-to-noise ratio (SNR). An alternative derivation of the iterative maximum likelihood (ML) SNR estimator is presented together with a novel, low complexity NDA SNR estimator. The performance of the proposed estimator is compared to previously suggested estimators and the CRLB. The results show that the proposed estimator performs close to the iterative ML estimator at significantly lower computational complexity

It has been shown that the stable fixed points of belief propagation (BP) algorithms correspond to extrema of the Bethe free energy. In this paper, we describe the dual problem for the minimization of the Bethe free energy and solve it using simple nonlinear block Gauss-Seidel and Jacobi algorithms. The use of the nonlinear block Gauss-Seidel algorithm corresponds to serial scheduling for the BP algorithm. In addition, it is shown that applying the nonlinear block Jacobi algorithm on the dual of the Bethe free energy corresponds to the parallel BP algorithm.

An interesting practical consideration for decoding of serial or parallel concatenated codes with more than two components is the determination of the lowest complexity component decoder schedule which results in convergence. This correspondence presents an algorithm that finds such an optimal decoder schedule. A technique is also given for combining and projecting a series of three-dimensional extrinsic information transfer (EXIT) functions onto a single two-dimensional EXIT chart. This is a useful technique for visualizing the convergence threshold for multiple concatenated codes and provides a design tool for concatenated codes with more than two components.

Optimal puncturing ratios for parallel concatenated codes with two or more constituent codes are found using extrinsic information transfer functions. These ratios minimize the signal-to-noise ratio convergence threshold and provide additional degrees of freedom for constructing codes with low thresholds over a wide range of code rates.

In this paper we apply the concept of recursive maximal ratio combining over iterations in an iterative multiuser decoder. The principle can be applied to any multiuser estimator that does not exploit information across iterations. The estimates over all iterations are combined based on MRC, such that the resulting SNR is maximized.

We consider a multiuser detector based on modelling the multiple-access interference (MAI) as a vector of Gaussian random variables. This approach leads to the probabilistic data association (PDA) multiuser detector, which outputs good approximations to marginal posterior-mode optimal decisions. A simplification to the PDA detector is suggested, leading to a soft interference cancellation scheme. In the large system limit, the bit error rate performance of this detector can be accurately predicted, and shown to be identical to the optimal detector.

One powerful approach for multiuser decoding is to iterate between a linear multiuser filter (which ignores coding constraints) and individual decoders (which ignore multiple-access interference). Subject to clearly formulated statistical assumptions and the history of input signals provided by the outer decoders over all previous iterations, an extrinsic Kalman filter is suggested. This approach is motivated by the recent observation that decoder outputs are loosely correlated during initial iterations. Numerical results show that iterative decoding using this filter provides better performance in terms of the supportable load and convergence speed as compared to previously suggested linear-filter-based iterative decoders.

In this paper, we compare several optimization methods for solving the optimal multiuser detection problem exactly or approximately. The purpose of using these algorithms is to provide complexity constraint alternatives to solving this nondeterministic polynomial-time (NP)-hard problem. An approximate solution is found either by relaxation or by heuristic search methods, while the branch and bound algorithm is used to provide an exact solution. Simulations show that these approaches can have bit-error rate (BER) performance which is indistinguishable from the maximum likelihood performance. A tabu search method is shown to be an effective (in terms of BER performance) and efficient (in terms of computational complexity) heuristic when compared to other heuristics like local search and iterative local search algorithms. When the number of users increases, the tabu search method is more effective and efficient than the semidefinite relaxation approach.

We consider serially concatenated block codes in a hybrid ARQ scheme using iterative decoding. The extrinsic information generated in the iterative decoding process is saved and used when a retransmission is decoded. Two different strategies are examined; one using the extrinsic information only in the very first iteration, whereas the other uses it in all subsequent iterations until another retransmission arrives. The latter can be seen as turbo or concatenated code combining whereas the former, where the extrinsic information is used only once may be seen as code doping, providing an alternative perspective. The strategy of saving the extrinsic information is also compared to traditional type-III, equal gain diversity combining. Using the extrinsic information from previous retransmission is shown to improve performance not only in terms of bit error rate but also in terms of throughput and convergence speed and requires only negligible additional decoder complexity. The performance of this strategy is however not as good as simple equal gain combining. As a consequence, the investigated schemes are not competitive alternatives, however, the code doping procedure can be used in conjunction with traditional diversity combining schemes, improving further on convergence speed.

The convergence behavior of linear parallel interference cancellation is investigated. Especially the so-called ping-pong effect, where the bit-error rate performance is found to oscillate between two different convergence patterns is studied in detail. This effect is shown to be a direct consequence of the extreme eigenvalues of the correlation matrix, allowing for an analytical approach. Intervals for the dominating eigenvalues within which ping-pong effects can occur are specified and illustrated by examples. It is shown that the decision statistic for traditional parallel cancellation will always exhibit oscillating behavior with either short or long codes. Relaxation factors, leading to weighted cancellation, are shown to be effective for alleviating oscillations and ping-pong effects at the expense of convergence rate. Asymptotic analysis for large systems is applied to uncover the convergence behavior for long code systems.

Convergence analysis of iterative detectors for narrow-band multiple access is performed using extrinsic information transfer charts. The system has no bandwidth expansion, so K users use the same bandwidth as a single user. The load (the number of bits used per channel) of the system is therefore higher than the load in, for example, conventional CDMA systems. The analysis provides useful guidelines on how to combine outer codes with the chosen mapper for different loads of the system. Both memoryless mappers and differential mappers are evaluated. We present the limitations of the system measured with the maximum number of users and the required SNR for different scenarios.

Trellis-code multiple-access (TCMA) is a narrow-band multiple-access scheme based on trellis-coded modulation. There is no bandwidth expansion, so K users occupy the same bandwidth as one single user. The load of the system, in number of bits per channel use, is therefore much higher than the load in, for example, conventional code-division multiple-access systems. Interleavers are introduced as a new feature to separate the users. This implies that the maximum-likelihood sequence detector (MLSD) is now too complex to implement. Iterative detectors are therefore suggested as an alternative to the joint MLSD. The conventional interference cancellation (IC), detector has lower complexity than the MLSD, but its performance is shown to be far from acceptable. Even after a novel improvement of the IC detector, the performance is unsatisfactory. Instead of using IC, another iterative detector is suggested. This detector updates the branch metric for every iteration, and avoids the standard Gaussian approximation. Simulations show that the performance of this detector can be close to single-user performance, even when the interleaver and the phase offset are the only user-specific features in the TCMA system.

This paper proves large-system asymptotic normality of the output of a family of linear multiuser receivers that can be arbitrarily well approximated by polynomial receivers. This family of receivers encompasses the single-user matched filter, the decorrelator, the minimum mean square error (MMSE) receiver, the parallel interference cancelers, and many other linear receivers of interest. Both with and without the assumption of perfect power control, we show that the output decision statistic for each user converges to a Gaussian random variable in distribution as the number of users and the spreading factor both tend to infinity with their ratio fixed. Analysis reveals that the distribution conditioned on almost all spreading sequences converges to the same distribution, which is also the unconditional distribution. This normality principle allows the system performance, e.g., the multiuser efficiency, to be completely determined by the output signal-to-interference ratio (SIR) for large linear systems.

Trellis code multiple access (TCMA) is a narrowband multiple access scheme. There is no bandwidth expansion, so K users are using the same bandwidth as one single user. The load (the number of bits per channel use) of the system is therefore much higher than the load in, for example, conventional CDMA systems. It is shown here that the maximum number of users in a TCMA system is usually modest. This fact is based on constellation-constrained capacity, ie, the maximum capacity of a system with a specific constellation of the transmitted symbols. The minimum required signal-to-noise ratio for reliable transmission is also given for different code rates.

In this paper, the convergence behaviour of linear parallel interference cancellation is investigated. Especially the so-called ping-pong effect where the bit error rate performance is found to oscillate between two different convergence patterns is studied in detail. This effect is shown to be a direct consequence of the extreme eigenvalues of the correlation matrix, allowing for an analytical approach. Intervals for the dominating eigenvalues within which ping-pong effects can occur are specified and illustrated by examples. Relaxation factors, leading to weighted cancellation, are shown to be effective for alleviating oscillations and ping-pong effects at the expense of convergence rate.

Iterative detectors for trellis code multiple access (TCMA) are suggested as an alternative to the joint maximum likelihood sequence detector (MLSD). Interleavers are introduced in the TCMA system as a new feature to separate the users. This implies that MLSD is now too complex to implement. The conventional interference cancellation (IC) detector has lower complexity, but its performance is shown to be far from acceptable. Another iterative detector having close to single user performance is therefore suggested. Instead of using IC, this detector updates the branch metric for every iteration and avoids the standard Gaussian approximation. It is also shown that the users can be detected when the interleaver is the only user specific feature in the TCMA system.

Trellis code multiple access (TCMA) is a narrow-band multiple access scheme. There is no bandwidth expansion, so K users are using the same bandwidth as one single user. The load (the number of bits per channel use) of the system is therefore much higher than the load in, for example, conventional CDMA systems. It is shown here that the maximum number of users in a TCMA system is usually modest. This fact is based on constellation-constrained capacity, i.e., the maximum capacity of a system with a specific constellation of the transmitted symbols. The minimum required signal-to-noise ratio for reliable transmission is also given for different code rates.

A detection strategy based on a semidefinite relaxation of the CDMA maximum-likelihood (ML) problem is investigated. Cutting planes are introduced to strengthen the approximation. The semidefinite program arising from the relaxation can be solved efficiently using interior point methods. These interior point methods have polynomial computational complexity in the number of users. The simulated bit error rate performance demonstrates that this approach provides a good approximation to the ML performance.

The detection strategy usually denoted optimal multiuser detection is equivalent to the solution of a (0, 1)-constrained maximum-likelihood (ML) problem, a problem which is known to be NP-hard. In contrast, the unconstrained ML problem can be solved quite easily and is known as the decorrelating detector. In this paper, we consider the constrained ML problem where the solution vector is restricted to lie within a closed convex set (CCS). Such a design criterion leads to detector structures which are ML under the constraint assumption. A close relationship between a sphere-constrained ML detector and the well-known minimum mean square error detector is found and verified. An iterative algorithm for solving a CCS constraint problem is derived based on results in linear variational inequality theory. Special cases of this algorithm, subject to a box-constraint, are found to correspond to known, nonlinear successive and parallel interference cancellation structures, using a clipped soft decision for making tentative decisions, while a weighted linear parallel interference canceler with signal-dependent weights arises from the sphere constraint. Convergence issues are investigated and an efficient implementation is suggested. The bit-error rate performance is studied via computer simulations and the expected performance improvements over unconstrained ML are verified.

Linear parallel interference cancellation (PIC) schemes are described and analyzed using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the chip-matched filtered received signal vector. An expression for the exact bit-error rate (BER) is obtained, and conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence are derived. The close relationship between the linear multistage PIC and the steepest descent method (SDM) for minimizing the mean squared error (MSE) is demonstrated. A modified weighted PIC structure that resembles the SDM is suggested which approaches the minimum MSE (MMSE) detector rather than the decorrelator. It is shown that for a K-user system, only K PIC stages are required for the equivalent matrix filter to be identical to the the MMSE filter. For fewer stages, techniques are devised for optimizing the choice of weights with respect to the MSE. One unique optimal choice of weights is found, which will lead to the minimum achievable MSE at the final stage. Simulation results show that a few stages are sufficient for near-MMSE performance.

In this paper, we describe linear successive interference cancellation (SIC) based on matrix-algebra. We show that linear SIC schemes (single stage and multistage) correspond to linear matrix filtering that can be performed directly on the received chip-matched filtered signal vector without explicitly performing the interference cancellation. This leads to an analytical expression for calculating the resulting bit-error rate which is of particular use for short code systems. Convergence issues are discussed, and the concept of /spl epsiv/-convergence is introduced to determine the number of stages required for practical convergence for both short and long codes.

It has previously been shown that well known iterations for solving a set of linear equations correspond to linear interference cancellation structures. Here, we suggest applying a block-wise iteration that consists of an outer and an inner iteration. The outer iteration used is the Gauss-Seidel (GS) method, while for the inner iteration, we study direct matrix inversion, the Jacobi over-relaxation iteration, and the conjugate gradient iteration. When a true inner iteration is used, this approach allows for a timely derivation of the acceleration parameters required by advanced iterations. The block iteration is based on a symbol-level implementation which leads to the same detection delay profile for both parallel and serial structures at the expense of differences in the amount of serial processing required. This is discussed in some detail and quantified for comparison. The performance of the detectors is studied via computer simulations where it is found that the block approach can provide significantly faster convergence, leading to improved detection delay over the simpler GS iteration. The improvements are obtained at the expense of an increase in the required serial processing speed.

Parallel interference cancellation (PIC) is a promising detection technique for code division multiple access (CDMA) systems. It has previously been shown that the weighted multistage PIC can be seen as an implementation of the steepest descent algorithm used to minimize the mean squared error (MSE). Following this interpretation, a unique set of weights, based on the eigenvalues of the correlation matrix, was found to lead to the minimum achievable MSE for a given number of stages in a short-code system. In this paper, we introduce a method for finding an appropriate set of time-invariant weights for systems using long codes. The weights are dependent on moments of the eigenvalues of the correlation matrix, exact expressions of which can be derived. This set of weights is optimal in the sense that it minimizes the ensemble averaged MSE over all code-sets. The loss incurred by averaging rather than using the optimal, time-varying weights is practically negligible, since the eigenvalues of sample correlation matrices are tightly clustered in most cases of interest. The complexity required for computing the weights increases linearly with the number of users but is independent of the processing gain, hence on-line weight updating is possible in a dynamic system. Simulation results show that a few stages is usually sufficient for near-MMSE performance.

We introduce a multiuser receiver based on the Kalman filter, which can be used for joint symbol detection and channel estimation. The proposed algorithm has the advantage of working even when the spreading codes used have a period larger than one symbol interval ("long codes"), unlike adaptive equalizer-type detectors. Simulation results which demonstrate the performance advantage of the proposed receiver over the conventional detector, the minimum mean squared error (MMSE) detector and a recursive least squares (RLS) multiuser detector are presented. A thorough comparison of the MMSE detector and the proposed detector is attempted because the Kalman filter also solves the MMSE parameter estimation problem, and it is concluded that, because the state space model assumed by the Kalman filter fits the code division multiple access (CDMA) system exactly, a multiuser detector based on the Kalman filter must necessarily perform better than a nonrecursive, finite-length MMSE detector. The computational complexity of the detector and its use in channel estimation are also studied.

In this letter we present a simplified proof for the convergence of the windowed Cholesky factorization of the time-varying asynchronous code-division multiple-access (CDMA) channel.

We consider a CDMA system with error-control coding. Optimal joint decoding is prohibitively complex. Instead, we propose a sequential approach for handling multiple-access interference and error-control decoding. Error-control decoding is implemented via single-user soft-input decoders utilizing metrics generated by linear algebraic multiuser metric generators. The decorrelator, and a new scheme termed the projection receiver, are utilized as metric generators. For a synchronous system, the coded performance of the projection receiver metric is shown to be superior to the decorrelator even though they are equally complex. Also, the theoretical degradation relative to the single user bound is derived.

Existing multiuser code-division multiple-access (CDMA) detectors either have to rely on strict power control or near-perfect parameter estimation for reliable operation. A novel adaptive multiuser CDMA detector structure is introduced. Using either an extended Kalman filter (EKF) or a recursive least squares (RLS) formulation, adaptive algorithms which jointly estimate the transmitted bits of each user and individual amplitudes and time delays may be derived. The proposed detectors work in a tracking mode after initial delay acquisition is accomplished using other techniques not discussed here. Through computer simulations, we show that the algorithms perform better than a bank of single-user (SU) receivers in terms of near-far resistance. Practical issues such as the selection of adaptation parameters are also discussed.

In this letter, we derive a recursive, additive metric for complexity-constrained maximum likelihood detection for multiuser CDMA using breadth-first detection algorithms. The metric requires linear filtering of the matched-filtered received signal vector. It is shown that a class of filters fulfilling certain requirements lead to identical performance.

Simple reduced tree-search detection schemes of the breadth-first type are applied to suboptimal joint multiuser detection in bit-synchronous code-division multiple access (CDMA) systems over both Gaussian and two-path Rayleigh-fading channels. It is pointed out that in contrast to the case of the optimal multiuser detector, the choice of the receiver filter severely influences the performance of suboptimal multiuser detectors. Simulation results supported by analysis show that breadth-first tree-search algorithms using a decorrelating noise whitening receiver filter perform better than similar receivers, which solely use a matched filter (MF) for virtually all nonsingular spreading code sets studied. Most of the code sets are randomly generated. The M- and T-algorithm detectors based on decorrelating noise whitening filter (WF) outputs can achieve near optimum performance at a very low complexity compared to the optimal detector, although the proposed detectors are more complex than some known suboptimum detectors. Furthermore, the use of combining techniques is considered for a two-path Rayleigh-fading channel, and a semi-synchronous CDMA structure is proposed. It is shown that if maximum ratio combining (MRC) is employed, the decorrelating noise WF still exists. The corresponding suboptimal combining detector with a decorrelating noise WF outperforms a similar noncombining detector.

Narrowband interference cancellation techniques described in the literature often overlook the possibility of using prior information known to the receiver in a commercial radio environment to improve their performance. This paper examines an adaptive receiver which exploits knowledge about the narrowband interference which is readily available in commercial CDMA systems, namely its frequency and signal pulse shape, to remove it. The proposed algorithm uses only one adaptive weight per interferer, as opposed to a transversal filter interference canceller which would require many more. Attendant advantages include faster convergence, removal of the need for filter order selection and reduced distortion of the desired signal.

Multicarrier CDMA and direct sequence CDMA have been suggested for both narrowband and broadband multiple access systems. A series of concepts have further been proposed for variable rate broadband transmission within a CDMA system. These principally different techniques exhibit certain common characteristics that can be exploited. We propose a generalised unifying discrete-time model for describing both MC-CDMA, DS-CDMA and hybrid DSMC-CDMA narrowband and variable rate broadband schemes. The model leads to a system description which is similar to the matrix algebraic formulation of a traditional DS-CDMA system.

A near ideal noise whitening filter for a time-varying code-division multiple-access (CDMA) system is examined. First, the structure of the ideal noise whitening filter is determined. The ideal noise whitening filter for a time-varying CDMA system is dependent on unknown future system parameters and is, therefore, impractical. A near ideal, realizable whitening filter is introduced as a solution. The convergence of the factorization method for a time-varying CDMA system is considered. The truncation of the number of taps of the ideal noise whitening filter is studied and a metric function based on the near ideal noise whitening filter for a tree search detection algorithm is formulated. Simulation results are obtained for five and ten-user time-varying CDMA systems with binary random signature sequences of length 10 and a rectangular chip waveform. The results show that the near ideal noise whitening filter can accurately approximate the ideal noise whitening filter at a low complexity level. The performance degradation of a suboptimal tree search detector for a time-varying, asynchronous CDMA system using a typical near ideal noise whitening filter is minimal compared to an identical system using the ideal noise whitening filter.

A trellis-coded, type-I hybrid-ARQ protocol using CRC codes as the error-detecting mechanism is described and analyzed. Bounds on both the reliability and throughput performance of the resulting error-control scheme are derived for AWGN channels and slowly fading Rician channels. Examples are included to illustrate the achievable gain of the proposed system relative to ordinary FEC trellis-coded systems. For slowly fading Rician channels, hybrid-ARQ protocols based on ordinary trellis-coded modulation and multiple trellis-coded modulation are also compared. All analytical results are supported by data from a series of simulations.>

It has been shown that the performance of sub-optimal multiuser receivers for synchronous DS/SSMA is improved by using a noise whitening matched filter (WMF) as a receiver filter. In the asynchronous case the performance is also improved through the use of a WMF. We present an efficient technique for deriving the WMF for an asynchronous DS/SSMA system. The WMF is determined as the Cholesky decomposition of X where X is the solution to X=R/sub 0/-R/sub 1//sup T/X/sup -1/R/sub 1/. A recursive algorithm for determining X is proposed. Constraints on the spreading codes that ensure convergence of the algorithm are derived and the efficiency of the technique is demonstrated by simulation.

Trellis coded modulation is widely used for digital transmission over fading channels. Classical diversity techniques are also frequently employed to combat fading. Two different combining strategies are compared. One scheme is based on an interleaved code combining technique. The alternative scheme is based on averaged diversity combining. The well known transfer function bounding technique for trellis codes is used to obtain expressions for the bit error rate performance of the two trellis coded diversity receivers over a slowly fading Rayleigh channel. The analysis of interleaved code combining is a straightforward modification of the analysis for multiple trellis coded modulation. The analysis of averaged diversity combining is accommodated through a more involved, novel modification of the branch labeling of the error state diagram.

A method is described for modifying trellis coded modulation systems for use in type-1 hybrid-ARQ protocols. The difference between the partial path metric of the survivor and that of the best nonsurvivor at each node in the trellis is used to determine the desirability of a retransmission request for a given received packet. Bounds on the reliability and throughput performance of the resulting error control scheme are derived for AWGN channels and slowly fading Rician channels. Examples are included to illustrate the achievable gain of the proposed system relative to ordinary forward-error-correcting trellis coded systems. Hybrid-ARQ protocols based on ordinary trellis coded modulation and multiple trellis coded modulation are also compared over slowly fading Rician channels. The dependence of performance on packet length is examined and illustrated by examples. All analytical results are supported by data from a series of simulations.>