Long-range radio-frequency wireless charging has received more and more attention in recent years. Unlike the literature that focuses on the mobile charging scenario, which is formulated as a path-planning problem, we consider a static network that consists of a power beacon (PB) and multiple wireless powered user nodes. Each user node is equipped with a rechargeable battery and harvests energy only from the PB. We assume that all user nodes are either in charge or work mode. Under this assumption, we first propose a charge scheduling scheme that achieves the system's maximal energy efficiency. We then further investigate the system's improvement with a multiantenna PB using the energy beamforming technique. Next, we extend our scheduling scheme to a two-tier network architecture, where a first-tier PB first transfers energy to the second-tier sub-PBs, and then those sub-PBs deliver energy to the user nodes which belong to their clusters. It is shown that energy beamforming with multiple antennas brings a significant improvement to the system's performance. Moreover, the two-tier architecture is shown to be superior to the one-tier architecture in terms of the energy transfer efficiency and the system's realization complexity. Finally, the simulation results demonstrate our theoretical findings.

In this paper, we investigate the tradeoffs between storage and latency for a k-user cache-aided relay interference channel with K antennas at the relay when channel state information (CSI) is not available at the transmitters. We propose a cache placement and content delivery scheme, and mainly focus on the case when each transmitter has a cache size capable of storing 1 out of K files in the library. The main contribution of our work is that by applying the relay decode-and-forward (DF) protocol, we can achieve a normalized delivery time (NDT) δ(μ) = (2K - 1)/K, which is the upper bound for the K-user interference channel with instantaneous CSI at the Transmitter (CSIT) when the normalized cache size at the transmitter is 1/K. We then consider caching at the relay, and based on the sum-Degree of Freedom (DoF) result, we found the achievable NDT to be (Kα + K - 1 - β)/(Ka - β), where a is the file splitting parameter and β is related to the relay cache size. We also analyze the case when the transmitter has a normalized cache size of 1. To our knowledge, no one had studied a relay interference channel with no CSIT but with caching. Our results show that caching at the relay side shortens the latency effectively, especially for a network with a large number of users. Furthermore, the presence of a relay in the network renders instantaneous CSIT unnecessary, which is a more practical situation in such systems.

In many survey-free Wi-Fi indoor localization systems, including the Adaptive indoor Wi-Fi Positioning System (AWPS) we proposed earlier, there is a need to associate unlabeled measurements to a floor plan. In this paper, we address the problem of how to associate a topological radio graph generated by crowd-sourced RSS measurements to an isomorphic Euclidean graph representing the physical space which may come from a geographic information system (GIS) or through automatic image analysis of a paper floor plan. We introduce the concept of Minimum Symmetric Structures (MSS) and Co-rooted Congruent Structures (COCS) as new ways of characterizing automorphism which prevent unambiguous association, and present a structure analysis algorithm for detecting these structures. Then, we derive rules on the number and locations of markers, or RSS measurements with location labels, needed for resolving the automorphism. Applying the analysis proposed in this paper to hypothetical floor plans as well as floor plans used in AWPS and other existing systems, we will demonstrate that often very few location labels are needed in a SLAM system.

We consider a two-user multiple access channel (MAC) with a wireless-powered relay-to-destination (RD) link, where the relay harvests energy from a radio frequency (RF) signal sent by a dedicated Power Beacon (PB). Each frame is divided into three phases. In the first phase, the relay harvests energy from an RF signal sent by a dedicated PB. The relay then receives information from user nodes in the second phase and forwards it to the destination in the third phase using its harvested energy. We investigate the sum rate maximization problem and characterize the capacity region of such a channel with the relay's maximum transmit power constraint, under both the amplify-and-forward (AF) and decode-and-forward (DF) relay strategies. Optimal solutions are obtained for both cases. It is interesting to find that the shape of the capacity region is still pentagonal with the wireless-powered relay. Finally, simulation results demonstrate the correctness of our analysis.

We consider a two-user multiple access channel (MAC) with a wireless-powered relay-to-destination (R- D) link, where the relay adopts the decode-and-forward (DF) relaying strategy and operates in half-duplex mode. Each frame is divided into three phases. In the first phase, the relay harvests energy from a radio frequency (RF) signal sent by a dedicated Power Beacon (PB). The relay then receives information from user nodes in the second phase and forwards it to the destination in the third phase using its harvested energy. We are interested in the system performance with the wireless-powered relay, as compared to the conventional MAC with an R-D link. In particular, we investigate the sum-rate and capacity region of the MAC with wireless-powered relay by jointly optimizing the time scheduling and transmit powers at the user nodes. The optimal scheduling and power allocations are obtained for both the sum-rate and the boundary points on the capacity region. Simulation results validate our theoretical analysis and demonstrate the effectiveness of our proposed solution.

In this paper, we investigate the achievable degree of freedom (DoF) of a fully connected 2-user multiple- input multiple-output (MIMO) relay interference channel with M antennas at each transmitter and N antennas at each receiver when channel state information (CSI) is not available at transmitters and a delayed version of the CSI of direct links from the transmitters to the receivers is known at the relay. We propose a two-phase transmission scheme and obtain different sum-DoF gains (inner bound) under various configurations. We found the achievable sum-DoF values for different antenna configurations at the relay node for the MIMO relay interference channels. The results show that if the relay node has more than 2M antennas, our proposed scheme can achieve the outer bound when the instantaneously CSI is known at the relay and at the receivers. This result implies that with the help of a relay with enough antennas, the requirement for instantaneous CSI can be relaxed to the delayed CSI. Moreover, when compared to the MIMO interference channel with no relay, the presence of relay with delayed global CSI can boost the DoF performance even when there is no CSI at the transmitters.

We consider a two-way wireless powered cooperative system where the relay not only helps to forward the information for the user nodes, but also acts as an energy beacon. Assuming that due to the hardware limitation, harvesting energy and information transmission cannot be performed simultaneously, we propose a novel three-phase energy harvesting and transmission protocol. In the first phase, the relay broadcasts radio frequency (RF) energy signals which is harvested by both user nodes. In the second and third phase, the user nodes communicate with each other via the relay node. Thus, in order to maximize the network throughput, it is critical to investigate the tradeoff between the durations of the wireless energy harvesting phase and the information transfer phases. In particular, we maximize the throughput for the proposed wireless powered two-way relaying systems by jointly optimizing the durations of wireless energy harvesting and information transmission phases, and the power allocation for transmissions. The optimal solution is obtained, and through simulations, we show the effectiveness of the proposed scheme as compared to the benchmark schemes.

Plug-in electric vehicles (PEVs) are likely to become very popular in the future. With a large number of PEVs across the world, the batteries of PEVs may form a huge energy storage system which can serve as both controllable power loads and power sources. This can help the power grid to regulate the frequency by minimizing the expected imbalance between load and generation under the circumstance of high load uncertainty. In this paper, we propose a distributed algorithm to solve this stochastic minimization problem. The algorithm is very easy to implement. Simulation results show that our proposed algorithm works well and can benefit the power grid in helping frequency regulation.

In this paper, we consider the problem of optimal real and reactive power management for a residential user with renewable energy production, photovoltaic (PV) inverter and battery. The user's objective is to find an optimal control policy of PV inverter and battery to minimize his time average cost. We propose an algorithm based on Lyapunov optimization techniques. This algorithm has low complexity and does not need prior knowledge of system's probability distribution. Simulation results show our algorithm can significantly reduce user's cost. We also prove this algorithm is able to achieve near-optimal performance as the battery size increases.

Multiuser two-way communication suffers from both self and inter-user interference. Conventional interference management scheme based on signal space alignment requires transmit channel-state-information (CSI) to precode the transmitted signals to achieve the alignment, which could be difficult to accomplish in practical communication systems. This paper considers a multiuser two-way communication system where one base station (BS) exchanges information with multiple user equipments (UE), through a relay station (RS) selected from a collection of available RSs. The selection procedure is based on a single real-valued report from each RS. We show that even though neither the BS nor the UEs have the transmit CSI, optimal degrees of freedom (DoF) can still be achieved as long as there are sufficient number of available RSs. We derive a sufficient condition for the number of RSs to achieve the optimal DoF. Numerical results also verify our theoretical analysis.

A two-way relay (TWR) channel is considered where two users exchange their messages with the help of a single relay. With the assumption of separate relay power budget and user power budget, we maximize the sum-rate of the TWR channel using physical-layer network coding (PNC) with flexible time fraction. We propose an optimal power allocation scheme between users and find that in high signal-to-noise ratio (SNR) regime, the user power should be allocated inversely proportional to the channel gains. Moreover, the bidirectional streams of the PNC-TWR enjoy full diversity gain. The analysis of the equal time fraction case and the numerical results of the flexible time fraction case both imply that the PNC relaying performs better than the decode-and-forward based TWR (DF-TWR) if the channel gains are similar, while the DF relaying performs better if the channel gains are quite different.

Obtaining accurate global channel state information (CSI) is critical for interference alignment (IA), in particular for multiple-input multiple-output (MIMO) system with high dimensional space. With limited feedback, a quantization approach is proposed with manageable complexity to quantize the vectors from channel matrices separately. By characterizing the rate loss and bit scaling requirement we further show how the amount of feedback bits affects the numbers of transmit/receive antennas that should be used. Simulations illustrate with this quantization approach the system can attain considerable rate improvement with large number of feedback bits and optimal numbers of transmit/receive antennas.

This paper investigates the achievable degrees of freedom (DoF) of a fully connected K-user multiple-input-multiple-output (MIMO) interference channel with a MIMO relay, where each transmitter (Tx) has M antennas and each receiver (Rx) has N antennas (K-user M × N channel). For the special case where M = N, previous works showed that even with the presence of relays, the sum DoF is still KM/2 and is achieved by interference alignment, assuming all Txs and Rxs have global channel state information (CSI). While this result showed that relays cannot increase the achievable DoF, we find that relay eliminates the CSI requirement at the Txs if global CSI is available at the relay. We propose a two-time-slot transmission scheme through which interference can be aligned, provided that the relay has enough antennas. We obtain the minimum number of antennas required at the relay for each Tx-Rx pair to achieve the maximum DoF and this number is less than that needed in the decode-and-forward approach and all other reported approaches in existing literature. Moreover, this can be achieved with just linear processing at the relay. Then the interference alignment based scheme is generalized to M ≠ N case, where we focus on the achievable symmetric DoF. A lower bound for the number of antennas required at the relay is derived and is shown to be tight in some cases.

We consider a cooperative wireless network with a single source, a single destination and M cooperative relays and show that with limited feedback bits from the destination, using all the relays to perform beamforming may not be optimal. We further assume that the destination chooses N relays with power gains exceeding a threshold to do transmit beamforming and feeds back B bits to specify a precoding vector from a randomly generated precoder codebook. For the given average feedback bits per relay, B̅ = B/M, we find the optimal threshold that maximizes the capacity of a decode-and-forward (DF) system when the number of relays is asymptotically large. We show that the system using this asymptotically optimal threshold has a larger capacity than a system using all relays for finite B̅, especially for small values of B̅. We also obtain numerically the optimal thresholds for systems with a finite number of relays. A simplified approach that uses a fixed number of relays is also proposed and leads to significant improvements. Given a fixed power budget, the power allocation between two phases is also examined in networks with asymptotically large numbers of relays, and the optimal power allocation fraction can be found numerically.

Interference alignment (IA) has been shown as a promising technique to achieve the optimal capacity scaling of a multiuser interference channel at asymptotically high signal-to-noise-ratio (SNR). However, in practical communication systems, mitigating all interference via IA is not necessary since some of them only have negligible effect due to path loss. Moreover, IA feasibility constraint hinders its application to all users. Clustered IA provides a mechanism to mitigate the IA feasibility constraint and maximize the achievable rate. However, how to form IA clusters properly has not been well addressed. In this paper, we consider the problem of IA clustering in a multiuser interference channel at finite SNR. By exploiting the statistics of the channel state information (CSI), two novel clustering algorithms based on graph partitioning and heuristic are proposed. It is shown that the proposed schemes lead to significant gain in achievable rate when compared with non-cooperative transmission scheme.

In the two-user MISO interference channel using transmit zero-forcing (ZF) strategy, if transmit antenna selection based on direct link channel gain is applied to select no less than two transmit antennas, we find that under limited feedback using more transmit antennas will actually induce more interference to the other users. In the high SNR region, the upper bounds of the throughput and the relative rate loss to the perfect channel state information (CSI) case are obtained. It is interesting to note that using a small number of transmit antennas can improve the performance considerably compared with that of using all the available antennas, even though some of the feedback bits are used to indicate the selected antennas. Numerical results also show that using selection can enjoy gains in throughput in the more than two users cases.

Location and tracking of healthy or infirm elders is a potentially useful application as society aging is accelerating worldwide and as technologies such as cellular positioning and Assisted Global Positioning System (AGPS) are maturing. For a wearable device to be used in such an application, the battery operating hour is often a key consideration. This paper describes an energy-efficient cellular and AGPS tracking algorithm based on the concept of Personal Common Location (PCL) that we define as the locations at which an elder spends most of his/her time, as recognized from historic cell ID record. During the tracking process, AGPS fixes are avoided if the elderly carrier is determined to be located within a PCL, if the destination PCL can be predicted, or if AGPS signals are likely to be unavailable. This paper also describes our approach for off-line PCL recognition, the necessity of cell ID clustering, as well as the results from our tracking experiments.

We present a suboptimal multicast strategy to facilitate the communication in the two-way relay (TWR) channel with multiple antennas using physical layer network coding (PNC). We study the sum-rate of the TWR channel and find an upper bound. Such a system enjoys the benefits of having fewer time slots due to the use of PNC and the additional spatial degree of freedom created by multiple antennas. The same number of antennas is assumed in the relay and two terminals, which makes the multicast problem much more complicated. With the assumption of channel reciprocity and the CSI at the transmitters, we design a suboptimal codebook for the multicast and a criterion for the uplink data rates selection to optimize the sum-rate. The analysis shows that the data rate achieved via this suboptimal multicast scheme is very close to the optimal multicast capacity. We also observe in the optimization process that maximizing the uplink data rates may not increase the sum-rate and instead, they should be adjusted according to the downlink data rate in order to maximize the sum-rate of the TWR channel.

This paper investigates the problem of achieving the degrees of freedom (DoF) of a K-user multiple-input-multipleoutput (MIMO) interference channel with a MIMO relay, where each transmitter and receiver is equipped with M antennas. We propose a two-hop relay aided transmission scheme based on the idea of interference alignment to achieve the full DoF KM/2. The scheme requires global channel state information (CSI) at the MIMO relay only while other nodes only need to have their local CSI. We also study the number of antennas needed at the MIMO relay to achieve interference alignment. In particular, we find that using just linear processing at the relay, the minimum number of antennas needed at the relay for each transmitter-receiver pair to achieve the maximum M/2 DoF per channel use is (K-1)M, less than what is needed for decode-and-forward approach and all other reported approaches in existing literatures.

We consider a cooperative relay system with multiple users sending packets to a single destination in a two-phase transmission scheme. In the first phase, users broadcast their packets to the destination via independent channels and attempt to receive packets transmitted by other users. Assuming the ACK/NAK feedback from the destination is received by all users, users act as relays in the second phase to forward the negatively acknowledged packets they received correctly in the first phase to the destination. We show that by making use of the knowledge of the number of ACK and NAK packets, users can optimize their transmit power levels accordingly to lower the outage probability under an average power constraint. In particular, we derive analytically the optimal power allocation, as a function of the number of acknowledged packets, to minimize the outage probability. We compare the performance achieved by the optimal power allocation to those achieved by other transmit power strategies with the same average power constraint and find that adaptively setting the transmit power based on number of acknowledged packets can improve the outage probability performance significantly.

We consider a cooperative wireless network with a single source, a single destination, and M cooperative relays. We show that, with only limited feedback, MB̅ bits, from the destination, using all the relays to perform beamforming may not be optimal. Assuming that the destination selects the relays whose power gains exceed a threshold and feeds back MB̅ bits to specify a preceding matrix from a randomly generated precoder codebook, we find the optimal threshold that maximizes the capacity of a Decode-and-Forward (DF) system for a given B̅, asymptotically in the number of relays, M. We show that the system using the optimal threshold has a higher capacity than a system using all relays for all B, especially for small values of B̅. Furthermore, using a fixed fraction (β* which is obtained from the optimal threshold) of relays in systems with finite number of relays also leads to a significant improvement in outage probability, comparing to that of the systems using all relays, in both DF and Amplify-and-Forward (AF) cooperating schemes.

We extend the idea of hybrid decode-and-forward (DF)/amplify-and-forward (AF) relaying scheme for single relay to the multiple relays scenario and refer to it as dynamic DF/AF scheme. In this dynamic scheme, each relay in the system chooses, packet by packet, between DF and AF dynamically and independently by examining the cyclic redundancy check (CRC) result of the packet. The relays encode the mixed DF/AF signals into a distributed linear dispersion code (DLDC), and then transmit the coded signals to the destination. We show that our proposed dynamic DF/AF scheme outperforms the DF and AF schemes over a wide signal-to-noise ratio (SNR) range. We also propose a more general and flexible form of DLDC, which treats the source-relay link and relay-destination link separately and allows their packet durations to be different. In particular, we assume that the destination has multiple antennas and uses a general two-stage linear MMSE receiver to detect the possibly mixed DF/AF signals, without knowing the forwarding types adopted at the relays. A channel estimator is embedded in the receiver to estimate the source-relay link channel state information (CSI). With this receiver, only partial CSI (the CSI of the combined source-relay and relay-destination link) is required at the destination. The simulation results show that the degradation due to this two-stage receiver is minimal when compared to the optimal, but more complex, ML receiver with full CSI and knowledge of relay forwarding types.

It is well known that cross-layer scheduling which adapts power, rate and user allocation can achieve significant gain on system capacity. However, conventional cross-layer designs all require channel state information at the base station (CSIT) which is difficult to obtain in practice. In this paper, we focus on cross-layer resource optimization based on ACK/NAK feedback flows in orthogonal frequency-division multiplexing (OFDM) systems without explicit CSIT. While the problem can be modeled as Markov decision process (MDP), brute-force approach by policy iteration or value iteration cannot lead to any viable solution. Thus, we derive a simple closed-form solution for the MDP cross-layer problem, which is asymptotically optimal for sufficiently small target packet error rate (PER). The proposed solution also has low complexity and is suitable for real-time implementation. It is also shown to achieve significant performance gain compared with systems that do not utilize the ACK/NAK feedbacks for cross-layer designs or cross-layer systems that utilize very unreliable CSIT for adaptation with mismatch in CSIT error statistics. Asymptotic analysis is also provided to obtain useful design insights.

A new MIMO channel model based on angular-domain, double-directional channel model is proposed. Angular domain is a more appropriate coordinate to describe the MIMO channel, since the incoming rays and outgoing rays appear in clusters in the real world. This model is developed based on linear space and sampling theory and is applicable to any practical antenna geometry and includes the actual radiation pattern of the antenna array. It is compared with other existing models, including i.i.d., Kronecker, virtual channel representation and eigenbeam model, using channel estimation based model validation. Both simulation and experimental results show that it outperforms other angular-domain based models in terms of channel estimation error. A more accurate channel model not only facilitates better performance analysis, but also channel estimation in practical communication system.

The performance degradation in convolutionally coded V-BLAST system is analyzed in this paper. Compared with coded linear filtering approach, it is shown that the coded V-BLAST suffers from serious degradation due to the effect of error propagation. Considering the constraint of the system, a performance improvement method is proposed. It adjusts the weighting of soft bits, where the weighting for one stream is found based on the equivalent error rate of that stream. Additional computation needed by the proposed method is neglectable. Both theoretical analysis and simulation verify the effectiveness of the proposed method.

Maximizing the rate of transmission over a network with fixed amount of power gives the most economic way to communicate in a network. This paper investigates accumulative repetition forwarding strategy in a wireless ad-hoc network using cooperative forwarding approaches that allow adaptive power allocation among nodes. We analyze the feasibility and performance gain of channel reuse over this network, where multiple transmit-and-receive pairs coexist simultaneously using the same channel. Under this framework, we present the jointly optimal power allocation and channel reuse solution. This solution can be computed in polynomial time and brings significant improvement in network performance.

A critical factor in the deployment of spatial multiplexing multiple-input multiple-output (MIMO) systems is the cost of multiple analog transmit/receive chains at the mobile terminal side. To mitigate this problem, antenna subset selection at the transmitter/receive has been proposed. With antenna selection, a small number of analog chains are multiplexed between a larger number of transmit/receive antenna elements. In this paper, we derive simple and robust criteria to antenna selection for V-BLAST error rate performance maximization. Both cases, where channel state information (CSI) at the transmitter is available and unavailable, are studied. Simulation results show that the proposed algorithm provides a very close performance to the optimum exhaustive search performance.

A power spectral density constrained adaptive modulation with frequency spreading orthogonal frequency division multiplexing (OFDM) scheme is proposed. Our objective is to improve the overall throughput under target packet-error-rate (PER) for OFDM transmission. We investigated the performance of a coded adaptive modulation scheme with and without bit interleaver and apply the results to determine the SNR thresholds of the frequency spreading OFDM scheme. Using these SNR thresholds, we derive a frequency spreading adaptive modulation scheme and obtain its performance. For comparison, we derive an algorithm which provides a tight upper bound. Simulation results indicate that our proposed scheme exhibits more than 5 dB signal-to-noise-ratio (SNR) gain relative to the constant transmit power adaptive modulation without frequency spreading in the low SNR region. When compared with the multiband UWB system, the proposed algorithm achieves up to at least 7 dB and 4 dB improvements at the high SNR region and the low SNR region respectively. The transmission ranges are improved by at least 60% for the 80Mbps data rate and 120% for the 480 Mbps.

Adapting user selection, power allocation and rate allocation, cross layer centralized scheduling can achieve a tremendous gain due to multiuser selection diversity in wireless networks. Yet, conventional cross layer designs all require channel state information at transmitters (CSIT), which is difficult to obtain in practice. In this paper, a closed loop cross layer design with no CSIT in a block fading frequency selective environment is proposed as an extension of flat fading case in (Ka Ming Ho, 2006). The solution to optimal power, rate allocation and user selection involves stochastic programming and thus has high complexity, especially when the channel is highly frequency selective. Instead, we would like to focus on two suboptimal algorithms, namely CP-TX and OP-TX, which are based on ACK/NAK feedbacks from selected mobiles. In practical situations, OP-TX can achieve more than 67 % of the goodput of the optimal algorithm.

Previous work on antenna selection in MIMO systems, which deal with error performance, has mainly focused on frequency-flat channels. As a result, the objective was to minimize the symbol error rate (SER) or pairwise error probability (PEP). However, in present and future communication systems, where high throughput is one of the major features, wideband systems with frequency selectivity are now becoming common. Therefore, SER in flat-fading channels may not be a good measure for evaluating antenna selection in practical systems. In this paper, instead, we formulate the antenna selection problem based on a frequency-selective WLAN system. Hence the objective is to reduce the packet error rate (PER). We propose different antenna selection algorithms depending on the extent of channel state information we have. Simulation results are provided to demonstrate the effectiveness of the algorithms proposed.

Cognitive radio technology facilitates spectrum reuse and alleviates spectrum crunch. One fundamental problem in cognitive radio is to avoid the interference caused by other communication systems sharing the same frequency band. However, spectrum sensing cannot guarantee accurate detection of the interference in many practical situations. Hence, it is crucial to design robust receivers to combat the in-band interference. In this paper, we first present a simple pilot aided interference detection method. To combat the residual interference that cannot be detected by the interference detector, we further propose a robust joint interference detection and decoding scheme. By exploiting the code structure in interference detection, the proposed scheme can successfully detect most of the interfered symbols without requiring the knowledge of the interference distribution. Our simulation results show that, even without any prior knowledge of the interference distribution, the proposed joint interference detection and decoding scheme is able to achieve a performance close to that of the maximum likelihood decoder with the full knowledge of the interference distribution

Link adaptation allows the transmitter to adapt to changing channel conditions. Critical to the design of link adaptation is the accuracy of channel state information at the transmitter. In this paper, we investigate the effect of imperfect channel state information and feedback delay on the performance of a multiple-input multiple-output zero-forcing receiver with adaptive power allocation. A closed-form approximate upper bound on bit error rate is derived for M-ary phase shift keying and M-ary quadrature amplitude modulation and it is valid for arbitrary numbers of transmit and. receive antennas. Comparison with Monte Carlo simulations is also provided, showing that the results derived from this analytical bound are useful for system design.

This paper considers the optimal resource allocation for a multiuser MIMO-OFDMA downlink system using zero-forcing SDMA, with the objective of maximizing the system capacity. We provide the general mathematical formulation of the capacity maximization problem whose resource allocation includes user selection, power allocation and receive signal subspace selection. While the optimal solution of this problem is difficult to obtain, we consider two special cases: user selection based only and antenna selection based only optimization, and develop the optimal solution by reformulating the combinatorial optimization problem into a convex problem. Our proposed algorithms for these special cases can be extended to develop a suboptimal algorithm for the original general optimization problem which allows subspace selection. Moreover, we develop reduced-complexity algorithms for these problems which incur negligible capacity loss. Numerical results and analysis are provided to evaluate the system capacity and to study the effect of the number of users and the receive antennas per user on the performance. Comparisons on the capacity achieved by user selection only, antenna selection only and suboptimal subspace selection are discussed

Orthogonal frequency division multiple access (OFDMA) and multicarrier code division multiple access (MC-CDMA) have recently drawn much attention for being potential candidates of future generation cellular systems. In single-cell scenario, while MC-CDMA is good at achieving frequency diversity when there is no channel state information available at the transmit side (CSIT), OFDMA achieves higher capacity than MC-CDMA due to its finer resolution in exploiting multiuser diversity with CSIT. Whether multiple-input-multiple-output (MIMO) MC-CDMA or OFDMA is a better option in multi-cell system remains unjustified in the literature. In this paper, we study the ergodic capacity and the goodput of MIMO-MC-CDMA and MIMO-OFDMA downlink systems with CSIT in multi-cell scenario assuming that the base station has the knowledge of the average inter-cell interference level only. Several types of users modeling different interference patterns are considered: (I) high data rate delay-insensitive users, (II) high data rate delay-sensitive .users, and (III) voice users (low data rate and bursty). Optimal resource allocation algorithms are used to compute the capacities of the systems, while a simple heuristic is used to obtain the achievable goodputs for both systems. The effects of path loss, number of antennas and different user types are studied and insightful results are obtained. We find that OFDMA has a higher system goodput for both Type I and Type II high data rate users, while MC-CDMA has a higher goodput for Type III users. Compared to MC-CDMA, the goodput of an OFDMA system is more sensitive to the activity factor of the voice users and suffers from noticeable loss. This demonstrates the superiority of the two systems in different practical situations.

In this paper, we examine and compare the potential maximum sum capacity of downlink multiple-input-multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) and multiple-input-multiple-output multicarrier code division multiple access (MIMO-MC-CDMA) in a single-cell multiuser environment with channel side information at the transmitter, with and without a fairness constraint. The resource allocation is formulated as a cross-layer optimization framework and optimal power allocation and user selection algorithms are proposed for both scenarios. We find that for delay-sensitive applications, where fairness is imposed, the performance gain of OFDMA over MC-CDMA is quite large at moderate path loss exponents and number of antennas. However, for delay-insensitive applications, the benefits of OFDMA over MC-CDMA are significantly reduced when the path loss exponent or the number of antennas is large

By employing spatial multiplexing, multiple-input multiple-output (MIMO) wireless antenna systems provide increases in capacity without the need for additional spectrum or power. Zero-forcing (ZF) detection is a simple and effective technique for retrieving multiple transmitted data streams at the receiver. However the detection requires knowledge of the channel state information (CSI) and in practice accurate CSI may not be available. In this letter, we investigate the effect of channel estimation error on the performance of MIMO ZF receivers in uncorrelated Rayleigh flat fading channels. By modeling the estimation error as independent complex Gaussian random variables, tight approximations for both the post-processing SNR distribution and bit error rate (BER) for MIMO ZF receivers with M-QAM and M-PSK modulated signals are derived in closed-form. Numerical results demonstrate the tightness of our analysis

Few works have addressed the effect of CFO (carrier frequency offset) on channel estimation performance. In this paper, compact analytical expressions on the mean square error of channel estimation in the presence of CFO are derived for OFDM (orthogonal frequency division multiplexing) systems employing single and multiple antennas. Concise upper bounds are also derived for SISO-OFDM systems. It is revealed that channel estimation MSE (mean square error) increases at the rate of approximately the square of the CFO and increasing the number of pilots does not contribute to better suppression of the MSE caused by CFO. In addition, it is observed that LMMSE (linear minimum mean square error) channel estimation is more resistant to CFO compared to LS (least square) in terms of channel estimation MSE. Furthermore, from the results derived herein, a clue for the pilot design of OFDM systems with CFO can be obtained

In wireless networks with centralized base station, cross layer scheduling to adapt user selection, power allocation and rate allocation can achieve a tremendous gain due to multiuser selection diversity. However, conventional cross layer designs all require channel state information at the base station (CSIT), which is difficult to obtain in practice. In this paper, we propose a closed loop cross layer design with no CSIT. The optimal power, rate allocation and user selection has high complexity as it involves stochastic programming. Instead, we would like to focus on two suboptimal algorithms, namely CP-TX and OP, which are based on ACK/NAK feedbacks from selected mobiles. Under practical circumstances, OP can achieve more than 88% goodput of the optimal algorithm.

Previous works on joint, both transmit and receive, antenna selection in MIMO systems have placed the computation burden to the receiver side, where perfect channel state information (CSI) at the receiver is assumed and the selected transmit antenna indices are sent back to the transmitter. This solution might not be practical, since with bursty packet transmission, the selected antenna subset may no longer be a good choice at the instant of actual transmission. In light of this, we formulate the problem such that the transmitter is performing the selection based on the CSI estimated a while back, or outdated CSI. A space-time coded MIMO channel with correlated flat fading and joint antenna selection is considered. Our closed-form optimal selection criterion incorporating the outdatedness of the CSI outperforms the existing solutions which treat the outdated CSI as the actual CSI.

The orthogonal frequency division multiplexing (OFDM) systems that exploit Alamouti transmit diversity technique can be divided into two categories, i.e. Alamouti space-time block-coded OFDM (STBC-OFDM) and space-frequency block-coded OFDM (SFBC-OFDM). In time-varying multipath Rayleigh fading channels, these systems suffer from both time and frequency selectivity of channels. Recently, several detection schemes have been proposed to improve the bit error rate (BER) performance of these systems. In this paper, the achievable average capacities of different detectors are investigated. Based on the probability density function (pdf) of the effective instantaneous signal-to-noise ratio (SNR) obtained by each detector, the analytical expressions of achievable average capacities for those systems with different detectors are derived. Numerical results are also presented to give some insights

By transmitting different substreams in different antennas simultaneously, a multiple element antenna array system provides increased capacity that grows linearly with the number of transmit antennas. Layered space-time processing that performs nulling, detection and cancellation for each substream can be used for reception, with a linear growth in receiver complexity. This paper considers this multi-input multi-output system over a slow time-varying frequency selective Rayleigh fading channel environment. With the equivalent channel tap delay line model, each delayed tap in every transmit-receive antenna pair can be considered as an imaginary antenna transmitting a delayed version of the substreams. Based on this idea, we propose a layered maximum likelihood detection (L-MLD) scheme which performs layered processing and maximum likelihood detection for each substream and its delayed elements. To further improve the performance, a group maximum likelihood detection (G-MLD) scheme is also proposed by grouping the substreams and performing layered processing in groups and maximum likelihood detection within the group. However, both schemes increase the required number of receiving antennas, which increases hardware cost and size. To reduce this requirement, we propose the use of oversampling technique to increase the dimension of the received signal. Simulation results show that the L-MLD scheme achieves frequency diversity and outperforms existing schemes such as the V-BLAST system with OFDM and multi-input multi-output decision feedback equalizers (MIMO-DFE). Moreover, the G-MLD scheme performs better than L-MLD with an increased detection complexity. In addition, it was showed that further increasing the oversampling rate beyond the minimum requirement does not improve the performance.

Space-time trellis code (STTC) in frequency selective fading channel using maximum likelihood equalization and detection (MLED), and orthogonal frequency division multiplexing (OFDM) are compared in this paper for channels with arbitrary delay profile. The performance bound for both schemes are first derived and their performances are compared both analytically and through simulations. Code design, receiver complexity, interleaver design and the robustness issues are addressed in these comparisons

This paper considers the power allocation for a multiuser MIMO-OFDM downlink system using zero-forcing multiplexing, with the objective to maximize the system capacity. An optimal power allocation algorithm has been developed and is presented. While the optimal power allocation algorithm achieves promising capacity, its complexity increases exponentially with the number of users. We develop two power allocation algorithms whose complexities increase only linearly with the number of users, with only negligible loss of capacity compared to the optimal algorithm. Numerical results and analysis are provided to evaluate the system capacities of the optimal and the reduced-complexity algorithms. At SNR of 10 dB, the optimal and the suboptimal schemes attain 40% capacity gain over a round-robin scheme with water filling and 60% capacity gain over a round-robin scheme with equal power allocation

This paper considers the resource allocation problem in space-division multiple access (SDMA)/multi-input-single-output (MISO)/OFDM systems. Our objective function is to maximize the total system data rate subject to total power constraint and each user's quality-of-service (QoS) requirement. In this SDMA/MISO/OFDM multiuser system, each user possesses a spatial filter in each subcarrier to remove interference from other users in that subcarrier. We observe that the number of users in a subcarrier has two conflicting effects on the system throughput. Adding more users in a subcarrier increases the number of spatial channels; however, at the same time, it introduces more interference among the users which reduces the throughput in each spatial channel. This paper takes into consideration these effects to solve the rate maximization problem.

This paper considers the resource allocation in space-division multiple access (SDMA)/multiinput-single-output (MISO)/OFDM downlink transmission system. Our objective function is to maximize the total system data rate subject to total power constraint and each user's quality-of-service (QoS) requirement The QoS requirement can be BER requirement or SER requirement for any modulation schemes. Our earlier results in (Y. M. Tsang et al., 2004) showed that a significant improvement on total data rate can be obtained by optimizing the number of users in each subcarrier of the system. However, the solution presented in (Y. M. Tsang et al., 2004) is suboptimal. In this paper, we will exploit the properties of this rate maximization problem to reformulate it as a convex optimization problem and obtain the optimal solution.

An iterative receiver for a space-time trellis coded system in frequency-selective fading channel is proposed. It performs channel gain estimation and sequence detection by using the expectation-maximization (EM) algorithm. Channel order estimation is included in the receiver to avoid unnecessary trellis computations by using the conditional model order estimator (CME). In addition, three modifications to the original CME criterion are proposed to improve the estimation accuracy. Simulation results show that the proposed receiver has a slight degradation in frame error rate performance to the known channel maximum likelihood receiver. Moreover, it outperforms the conventional fixed long-tap length EM receiver with a lesser complexity. Furthermore, the proposed modifications to the CME criterion improve the channel order estimation accuracy, thus minimizing unnecessary computations.

We present the architecture of generalized layered space-time codes (GLST) as a combination of Bell Labs layered space-time (BLAST) architecture and space-time coding (STC) in multiple-antenna wireless communication systems. This approach provides both spectral and power efficiency with moderate complexity. The framework is to partition all the available transmit antennas into groups and apply STC on each group as component codes. Based on the mappings from coded symbols to transmit antenna groups, we can construct different GLST systems. Particularly, horizontal mapping and diagonal mapping are introduced and referred to as HGLST and DGLST respectively. The basic decoding of GLST, under quasi-static flat Rayleigh fading environments and assuming perfectly known channel state information (CSI) at the receiver, combines group interference suppression and group interference cancellation techniques. As a result, the individual STC on each group is decoded serially. To improve the overall system performance, we derive the optimal power allocation among all space-time codewords without requiring the knowledge of CSI at the transmitter and suitable for all GLST systems. We also derive the optimal serial decoding order based on the channel realizations at the receiver for HGLST systems without power allocation. Simulation results show that both can provide much improvement. To further enhance the system performance, we propose a low complexity hard-decision iterative decoding method. This method efficiently exploits full receive antenna diversity and, hence, dramatically improves the system performance which is confirmed by simulation.

Coding and modulation for multiple-antenna systems have gained much attention in wireless communications. This paper investigates a noncoherent trellis-coded scheme based on differential unitary space-time modulation when neither the transmitter nor the receiver know the channel. In a time-varying flat Rayleigh fading environment, we derive differentially noncoherent decision metrics and obtain performance measures for systems with either an ideal interleaver or no interleaver. We demonstrate that with an ideal interleaver, the system performance is dominated by the minimum Hamming distance of the trellis code, while without an interleaver, the performance is dominated by the minimum free squared determinant distance (a novel generalization of the Euclidean distance) of the code. For both cases, code construction is described for Ungerboeck-type codes. Several examples that are based on diagonal cyclic group constellations and offer a good tradeoff between the coding advantage and trellis complexity are provided. Simulation results show that, by applying the soft-decision Viterbi decoder, the proposed scheme can achieve very good performance even with few receive antennas. Extensions to trellis-coded differential space-time block codes are also discussed.

We propose an adaptive rank-estimation method for the additive white or colored Gaussian noise model. The main contribution of this paper has three parts. (1) We investigate the rank mismatch problem in the group-blind multiuser detector of Wang and Host-Madsen (see IEEE J. Select. Areas Commun., vol.17, p.1971-1984, Nov. 1999), and find that underestimating the rank causes significant performance degradation, whereas, rank overestimation can achieve performance gain in the low signal-to-noise-ratio (SNR) region. However, rank overestimation can lead to inaccurate channel estimation, which degrades the detector performance significantly in the high SNR region. (2) We propose a heuristic criterion for initial rank estimation which is robust for nonwhite noise cases. (3) In order to mitigate the rank mismatch problem, we introduce a hypothesis testing criterion for rank and signal subspace decisions, which selects the most probable rank for the group-blind detectors. Simulation results show that the performance of the group-blind detector using this adaptive rank estimation algorithm is comparable to the group-blind with perfect knowledge of the rank, and even better in the low-to-medium SNR region.

This paper presents a simplified bit allocation algorithm for OFDM multiple-input multiple-output (MIMO) systems that uses V-BLAST as a detection algorithm. The advantage of our approach is that only minimal feedback of information back to the transmitter is required while still maintaining good performance. We demonstrate by computer simulation that the proposed simplified bit allocation algorithm can significantly improve the system performance and still maintain a reasonable feedback loading compared to the traditional V-BLAST for an OFDM MIMO system in a frequency selective fading channel model.

This paper considers V-BLAST (vertically layered Bell Laboratories layered space-time) over a frequency selective fading channel environment. By considering the delayed elements in each transmit-receive antenna pair as imaginary antennas transmitting delayed versions of the substreams, we proposed a layered maximum likelihood detection (L-MLD) scheme in So and Cheng (2002). This scheme performs ordered nulling, detection and cancellation to each substream and its delayed elements. However, it increases the required number of receiving antennas, thus increasing hardware cost and size. We propose the use of oversampling technique to increase the dimension of the received signal, hence reducing the minimum requirement on the number of receiving antennas. Simulation results show that the L-MLD scheme achieves frequency diversity and outperforms the V-BLAST system with OFDM. It also shows that further increasing the oversampling rate of L-MLD does not improve the performance.

This paper studies the performance of two major space-time trellis code (STC) transmission and detection schemes over frequency selective fading channels: (1) maximum likelihood equalization and detection (MLED), and (2) orthogonal frequency division multiplexing (OFDM). Their performance is evaluated and compared both analytically and empirically. It shows that the maximum achievable diversity order for MLED and OFDM approaches are both identical as NML, where N, M is the number of transmit and receive antennas respectively, and L is the channel tap length. To achieve a certain amount of diversity order, the MLED approach requires a weaker code, but the decoding trellis complexity for both MLED (with combined trellis detector) and OFDM are the same. For codes that do not achieve the maximum diversity order, MLED always achieves higher diversity order than OFDM. Moreover, the use of interleaver in STC OFDM is essential in avoiding rank deficiency caused by clustering of path arrivals, which reduces the diversity order of the system. Simulation results support these arguments, and show that the MLED approach outperforms OFDM when the same maximum diversity order achievable code is used.

In this paper, we study the performance of the OFDM receiver using FFT based on the log number system (Log-FFT) in a wireless environment. By using the log number system (LNS), complex multiplications of the FFT are reduced to simple additions. The effect of finite bit precision on the receiver performance is analyzed theoretically under the AWGN channel. Simulation results for both AWGN and fading channels are presented. It is shown that the bit width requirement of the receiver is quite small. In a coded OFDM system, there is no degradation in bit error rate performance when only two fractional bits are used for the LNS under a slow fading channel. The size of the look-up tables are small and the complexity of the log-FFT implementation is simple. Thus log-FFT is an attractive implementation method for the OFDM receiver design in wireless environment.

This paper presents an iterative bit and power allocation algorithm for an OFDM multiple-input multiple-output (MIMO) system in frequency selective fading channels and uses V-BLAST as a detection algorithm. Assuming knowledge of the instantaneous channel gains for all spatial channels at all the subcarriers in the receiver, bit and power is assigned to each spatial channel to minimize the total transmission power for a fixed bit error rate (BER). We demonstrate by computer simulation that the proposed iterative bit and power allocation algorithm can significantly improve the system performance compared to the traditional V-BLAST and singular value decomposition (SVD) algorithm for an OFDM MIMO system in a frequency selective fading channel model.

V-BLAST (Vertically-layered Bell Laboratories Layered Space-Time) is a multiple transmit and receive antenna system that provides very high capacity compared to single antenna systems. However, most research in this area had assumed a flat-fading channel environment. This paper considers a frequency selective Rayleigh fading channel environment for multi-input and multi-output (MIMO) systems. Three different detection techniques with ordered successive interference cancellation are proposed: (1) zero-forcing maximal ratio combining (ZF-MRC); (2) layered maximum likelihood detection (L-MLD); and (3) group maximum likelihood detection (G-MLD). All these schemes consider the delayed elements in each transmit-receive antenna pair as imaginary antennas transmitting delayed versions of the substreams. Constraints on the number of receive antennas are also discussed, with G-MLD requiring the least elements. Simulation results show that G-MLD provides the best performance with ZF-MRC performing the worst.

This paper considers trellis-coded differential unitary spacetime modulation for multiple-antenna systems when neither the transmitter nor the receiver has access to channel state information. The channel is assumed to be slowly time-varying flat Rayleigh fading with ideal interleaver. We derive the metric for maximum likelihood differential decoding and the Chernoff bound for pairwise error probability. We show that performance is dominated by the minimum Hamming distance which contributes linearly to the order of diversity. Code construction is described for rate m/(m + 1) trellis codes. Several code examples are provided based on diagonal cyclic group constellations for two transmit antennas with data rate 1 and 2 bits/s/Hz. Simulation results show that the proposed trellis-coded differential scheme can achieve high data rate communications by medium signal-to-noise ratio without channel estimation.

We propose a new differential modulation scheme for multiple-antenna systems based on square space-time block codes (STBC) when neither the transmitter nor the receiver knows channel state information. Compared with the known differential unitary space-time modulation (DUSTM), the proposed constellations generally have multiple amplitudes and do not have group properties. This generalization potentially allows the spectral efficiency to be increased by carrying information not only on orientations (or phases) but also on amplitudes. Two non-coherent decoders, optimal differential decoder (DD) and near-optimal DD, are derived for flat Rayleigh fading channels. Particularly, the near-optimal DD inherits the decomposition decoding property retained by STBC with coherent receiver and thus has linear complexity. Compared with the best-known cyclic group constellations designed for DUSTM, our proposed constellations with the near-optimal DD have significantly lower probability of error and lower decoding complexity.

In the multipath CDMA reverse link, the base station knows the signature waveforms of users within its cell, but has no knowledge of channel coefficients of different users. In this paper, we propose a subspace-based blind noise suppression decorrelating multiuser detector making full use of estimated noise subspace and signature sequences of different users. This subspace blind detection approach has the advantages that it does not need the training sequences and channel coefficients of all users. The proposed blind multiuser detection technique offers substantial performance gain over the conventional Rake receivers with channel coefficients and has better performance when compared with the subspace-based blind detectors with known channel coefficients in Wang et al. (1998), in a multipath CDMA reverse link environment.

We consider a generalized layered space-time (GLST) architecture with parallel space-time (ST) codes and derive an optimal power allocation (PA) scheme over the space-time encoders to minimize the overall frame error rate. We prove that the optimal power allocation scheme will equate the derivatives of the frame error rate functions of all the ST codes. From simulation, we show that the derived optimal power allocation has a 1-2 dB gain over the equal power scheme. Also, the proposed scheme has a better performance than the power allocation scheme proposed by Tarokh, Naguib, Seshadri and Calderbank (see IEEE Trans. Inform. Theory, vol.45, no.4, p.1121-28, 1999). Since various power allocation schemes have the same receiver structure, the gain can be achieved simply using the optimized parameters with no increase in complexity.

Space division multiple access (SDMA) is a promising solution for the significant increase of system capacity and spectral efficiency in wireless LANs. To make the system more robust against the detrimental effects of frequency selective fading channels, a combined OFDM/SDMA based WLAN has been previously proposed. In particular, it has been shown that MLD (maximum likelihood detection) has the best SNR performance compared with other detection schemes such as LMMSE and SIC (successive interference cancellation) based ones. However, the complexity of MLD increases exponentially in the number of users and constellation size. In this paper, a new multi-stage low complexity MLD scheme using the sensitive bits algorithm (SB-MLD) is proposed. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared with the exhaustive MLD scheme.

Space-time coded OFDM is a promising scheme for future wideband multimedia wireless communication systems. The combination of space-time coding (STC) and OFDM modulation promises an enhanced performance in terms of power and spectral efficiency. However, STC transmit diversity impairs the system's interference suppression ability because each transmitter generates multiple signals that appear independent to the receiver antenna arrays. In this paper, we propose a novel CCI cancellation method employing angle diversity based on beamforming. It is shown that the proposed method can effectively mitigate CCI while preserving the space-time structure, thereby, significantly improving the system's interference suppression ability without significant performance degradation.

In this paper we refer to the combination of BLAST and space-time coding (STC) for multi-input multi-output systems as generalized layered space-time coding (GLST). Post-ordered decoding algorithm is introduced based on the generalization of the original BLAST ordering detection algorithm. The performance is analyzed through comparison to that of pre-ordered decoding with and without power allocation. Interleavered GLST with a new iterative process is also proposed. It can efficiently exploit full receive antenna diversity and thus significantly improve the system overall performance. Due to hard interference cancellation (IC) and ML decoder in the iterations, the new iterative decoding is much less complex than conventional turbo processing where soft IC and MAP decoder were applied.

We develop a novel multistage semiblind multiuser detection technique for the reverse link in direct sequence (DS) code-division multiple access (CDMA) systems. This approach fully utilizes all known users' information, performs interference cancellation (IC) to suppress the interferers within the cell, and exploits a blind adaptive decision-directed (DD) MMSE detector to suppress the inter-cell interference. This process can be made iterative and in the multistage process, the tentative decision bits from DD-MMSE detectors can be fed back to the IC part to make interference regeneration more accurate. A simplified adaptive algorithm for this multistage semi-blind detectors is designed. Two upper bounds for the signal-to-noise-interference ratio (SIR) of the multistage semiblind detector are derived. It is shown that the proposed detector has a significant performance gain over that of the pure blind detectors and the non-blind detectors. The tracking capability of the proposed semi-blind detector in a dynamic environment is examined with simulations.

Several smart antenna systems have been proposed and demonstrated at the base station (BS) of wireless communications systems, and these have shown that significant system performance improvement is possible. We consider the use of adaptive antennas at the BS and mobile stations (MS), operating jointly, in combination with orthogonal frequency-division multiplexing. The advantages of the proposed system includes reductions in average error probability and increases in capacity compared to conventional systems. Multiuser access, in space, time, and through subcarriers, is also possible and expressions for the exact joint optimal antenna weights at the BS and MS under cochannel interference conditions for fading channels are derived. To demonstrate the potential of our proposed system, analytical along with Monte Carlo simulation results are provided.

We present an improved channel estimation algorithm for orthogonal frequency-division multiplexing mobile communication systems using pilot subcarriers. This algorithm is based on a parametric channel model where the channel frequency response is estimated using an L-path channel model. In the algorithm, we employ the ESPRIT (estimation of signal parameters by rotational invariance techniques) method to do the initial multipath time delays acquisition and propose an interpath interference cancellation delay locked loop to track the channel multipath time delays. With the multipath time delays information, a minimum mean square error estimator is derived to estimate the channel frequency response. It is demonstrated that the use of the parametric channel model can effectively reduce the signal subspace dimension of the channel correlation matrix for the sparse multipath fading channels and, consequently, improve the channel estimation performance.

Turbo-code becomes popular for the next generation wireless communication systems because of its remarkable coding performance. One of the problems for decoding turbo-code in the receiver is the complexity and the high power consumption since multiple iterations of Soft Output Viterbi Algorithm (SOVA) or Maximum a posteriori (MAP) decoding have to be carried out to decode a data frame. To reduce the complexity of the turbo-code decoder, adaptive iteration based on cyclic redundancy checking (CRC) and output convergence approaches has been proposed to reduce the average number of iterations required for decoding a data frame. This results in a system that has variable workload since the amount of computation required for decoding each data frame is different. In this work, we propose a dynamic voltage scaling approach to further reduce the power consumption. Different from other variable workload systems, the workload here is not known at the time when the data is being decoded. Thus, optimum voltage assignment is not feasible. We propose several heuristic algorithms to assign supply voltage for different decoding iterations. Simulation results show that significant reduction of power consumption is achieved comparing with the system using fixed supply voltage.

No abstract available.

We consider the design of a space-time code for a system with large number of antennas using a serial turbo code structure with a parity cheek code as the outer code under a quasistatic and independent Rayleigh fading environment. By studying the case with a large number of receive antennas, we have proven that interference between different transmit antennas vanishes as the number of receive antennas approaches infinity. The design of a code can then be largely simplified by dividing the antennas into groups, using a small space-time code on each group. An outer code is added to allow each information bit to fully utilize the full range of antenna diversity and to be benefited from all the space-time codes. Dividing the overall system into groups enables a trade off between complexity and performance. This scheme has been investigated for systems with 5 receive antennas and 2 or 4 transmit antennas. Simulation results showed that the system performance in terms of the frame error rate degrades only slightly when both the data rate and the number of transmit antennas are doubled while keeping the received energy per bit at the receiver constant.

Complexity and detection delay are major issues for applying interference cancellation to practical CDMA systems. We introduce a new interference cancellation approach for multiuser detection. This detector combines both parallel interference cancellation (PIC) and successive interference cancellation (SIC) techniques. It has a short detection delay as in PIC and low computation complexity as in SIC.

We consider a wireless multirate CDMA system with perfect successive interference cancellation (IC). Different services have different rates, quality of service (QoS) requirements. We formulate the problem as a constrained optimization problem with the objective of minimizing the total transmission power. An optimal power control strategy is derived. We find that ranking users in descending order of channel gain can minimize the total transmission power of the users, regardless of the users' data rate and QoS requirements.

In this paper, we propose a reduced complexity implementation scheme of the Log-Map algorithm for turbo-codes decoding. By re-arranging the structure of the computation and using adaptive approximation, the computation in the Log-Map algorithm such as the state metric and the log-likelihood ratio calculation could be simplified or reduced adaptively. Simulation results show that more than 45% of the computation can be reduced with almost no performance degradation.

The blind multiuser detection techniques in DS-CDMA systems mainly deal with the demodulation of a desired user's data with the prior knowledge of only the signature sequence of that user. However, in the CDMA reverse link, the base station knows the signature sequences of users in its cell, but has no knowledge of interfering users from other cells. In this paper, we develop a class of novel semi-blind technique for multiuser detection in such a scenario. This approach fully utilizes all known users' information, performs multistage parallel or serial interference cancellation to suppress the interferers within the cell, and exploits a blind adaptive decision-feedback MMSE detector to suppress the inter-cell interference. The performance of the proposed detector is found to have significantly better performance than that of the purely blind detectors and the non-blind detectors.

In this paper, we propose a low power VLSI architecture of Soft-Output-Viterbi-Algorithm (SOVA) based turbo-code decoder using a scarce state transition scheme (SST). A register exchange survival memory unit (RE-SMU) and systolic block are used in the implementation of SOVA for high throughput and low latency. SST is used to reduce the power consumption. Simulation results show that the power consumption of RE-SMU and the systolic block is reduced significantly. The power consumption of the add-compare-select (ACS) block is also reduced by as much as 20% after 4 iterations of turbo-code decoding.

The performance of wideband code division multiple access (WCDMA) can be severely degraded as the number of users increases due to the increase in interference. Multi-user detection is a scheme, which can cancel the interference generated by other users and hence can improve the system capacity. Recently a joint successive interference cancellation with interleaving (JSICI) scheme has been proposed for multi-user detection. However the complexity of the scheme is very high. In this paper, we propose a low complexity architecture which can implement this JSICI scheme efficiently in VLSI. Also low power features are proposed.

It is well-known that the capacity of a direct sequence CDMA system is multiple access interference limited. Adaptive antenna arrays and interference cancellation can significantly reduce the multiple access interference and can greatly enhance the system performance. This paper investigates the performance improvement that can be achieved by integrating adaptive antenna array processing and interference cancellation, where the receiver steers the beams of the adaptive antenna towards not only the desired user but the interferers as well to facilitate the interference cancellation process. We analyze how the use of an FFT beamformer preceding the 2-D RAKE receiver reduces the complexity of the receiver without severe degradation in the overall system performance.

With the advances in 3G mobile communications, wireless multimedia communications have received increased attention. One of the most serious problems in the wireless transmission of images is the loss of macroblock (MB) synchronization. In 1995, the error resilient entropy code (EREC) was proposed to solve the MB synchronization problem. However, EREC leads to two new error propagation issues: AC error propagation and DC error propagation. In this paper, we propose a DC error correction technique to tackle the DC error propagation problem. This technique requires no changes in the source encoder and decoder, and can make full use of the inserted DC values and the neighboring DC values to limit the effect of the DC error propagation. Various simulation results are presented and they demonstrate that the proposed technique improves the image quality significantly.

The V-BLAST architecture has been proposed as an extremely spectral efficient tool for wireless communications. However, owing to the intensive computation involved, it may be difficult to implement this architecture for high data rate communication system. We propose the replacement of the optimal decoding order by a suboptimal one and the utilization of the Gram-Schmitt orthogonalization (GSO) to substitute the computation of the pseudo-inverse in finding the weight vectors. These modifications significantly reduce the total number of arithmetic operations required to obtain the weight vectors and the decoding order in V-BLAST with virtually no performance degradation. In slowly time-varying fading channels, the proposed method can further reduce the amount of computation required by exploiting the time correlation between the channel gains.

Over the years, several smart antenna systems have been proposed and demonstrated in wireless communications systems, and these have shown that significant system performance improvement is possible. In this paper, we consider the maximization of the spectral efficiency of a multiuser MIMO system for downlink communications (one base to many mobiles) in both frequency flat and selective fading channels. Each mobile (user) in the system incorporates an array of n/sub R/ antennas and in general transmits K/sub m//spl ges/1 space-time subchannels, in the same frequency spectrum and time slot. Our objective is to jointly find the antenna weights for all the users, under the constraint of fixed transmit power, so that the spectral efficiency of the system (or the average spectral efficiency per user) is maximized. An iterative procedure that successively nulls out all the broadcast interference is proposed, and simulation results show that multiuser MIMO optimization significantly outperforms single-user MIMO optimization. In addition, spectral efficiency close to an upper bound can be achieved.

Orthogonal frequency division multiplexing (OFDM) is an effective modulation technique for high-rate and high-speed transmission over frequency selective fading channels. However, OFDM systems can be extremely sensitive and vulnerable to synchronization errors. In this paper, we present a scheme for performing timing recovery that includes symbol synchronization and sampling clock synchronization in OFDM systems. The scheme is based on pilot subcarriers. In the scheme, we use a path time delay estimation method to improve the accuracy of the correlation-based symbol synchronization methods, and use a delay-locked loop (DLL) to do the sampling clock synchronization. It is shown that by using this scheme, the mean square values of the symbol timing estimation error can be decreased by several orders of magnitude compared to the common correlation methods in both the AWGN and multipath fading channels. In addition, the scheme can track the symbol timing drift caused by the sampling clock frequency offsets.

Turbo code becomes popular for the next generation wireless communication systems because of its remarkable coding performance. One of the problems for decoding turbo code in the receiver is the complexity and the high power consumption since multiple iterations of Soft Output Viterbi Algorithm (SOVA) have to be carried out to decode a data frame. In this paper, we address the issues of reducing the complexity and power consumption of the turbo code decoder. An approach using cyclic redundancy checking (CRC) to adaptively terminate the SOVA iteration of each frame is presented. This results in system that has variable workload of which the amount of computation required for each data frame is different. Dynamic voltage scaling is then used to further reduce the power consumption. However, since the workload is not yet known at the time when the data is being decoded, optimum voltage assignment is not feasible. In this work, we propose two heuristic algorithms to assign supply voltage for different decoding iterations. Simulation results show that significant reduction of power consumption is achieved comparing with system using fixed supply voltage.

This paper introduces a combining algorithm for WCDMA handsets using a single front-end circuitry to enhance signal-to-interference-and-noise ratio (SINR). The proposed algorithm can have a gain of about 6 dB over selection diversity, the conventional design for multiple antenna system for handsets. Analytical equations based on a multipath channel model are derived and simulation results and performance evaluation comparing several diversity receivers are also presented.

This paper presents an adaptive tracking algorithm for adaptively updating the bit and power allocation for OFDM transmission in a time-varying channel. The proposed algorithm utilities the previous bit allocation information for initialization, and then iteratively refines the allocation until it reaches the optimal solution. We prove a theorem which guarantees the convergence of the algorithm to the optimal solution. Through simulation, we find that the proposed algorithm converges quickly in just a few iterations when the variation in the channel is small. When the channel changes rapidly the adaptive tracking algorithm is still computationally much more efficient than existing algorithms which solve the problem from scratch.

Interference cancellation and turbo code are two very promising techniques for performance improvement in CDMA systems. The former significantly reduces most of the multiple access interference (MAI) while the latter provides very strong error correcting capability against residual interference and background noise. As both interference cancellation and turbo decoding are iterative multi-stage algorithms, we combine the two multi-stage algorithms into an integrated interference cancellation and decoding algorithm in which each stage consists of a interference cancellation iteration and a turbo decoding iteration. The performance of this integrated approach is compared to the usual concatenation approach where all the multi-stage interference cancellation iterations are completed first before starting the turbo decoding iterations. Even though both approaches have the same amount of complexity, we find that significant performance gain is achieved when the iterations are integrated and this performance gain increases with the number of users.

In this paper, we present a delay-locked loop (DLL) technique for performing a combined symbol and sampling clock synchronization in orthogonal frequency division multiplexing (OFDM) systems. In addition, we propose a symbol timing acquisition algorithm for the DLL. It is shown that by using this combined scheme, we can achieve symbol timing recovery and sampling clock adjustment simultaneously. In particular, the symbol timing estimation error variance can be decreased by several orders of magnitude compared with the common correlation methods in both the AWGN and multipath fading channels.

Multiuser orthogonal frequency division multiplexing (OFDM) with adaptive multiuser subcarrier allocation and adaptive modulation is considered. Assuming knowledge of the instantaneous channel gains for all users, we propose a multiuser OFDM subcarrier, bit, and power allocation algorithm to minimize the total transmit power. This is done by assigning each user a set of subcarriers and by determining the number of bits and the transmit power level for each subcarrier. We obtain the performance of our proposed algorithm in a multiuser frequency selective fading environment for various time delay spread values and various numbers of users. The results show that our proposed algorithm outperforms multiuser OFDM systems with static time-division multiple access (TDMA) or frequency-division multiple access (FDMA) techniques which employ fixed and predetermined time-slot or subcarrier allocation schemes. We have also quantified the improvement in terms of the overall required transmit power, the bit-error rate (BER), or the area of coverage for a given outage probability.

In this paper, we propose two modifications to soft output Viterbi algorithm (SOVA) for turbo code decoding. One is to limit the reliability values to a small range to compensate for the defect brought by overestimating those values in the original SOVA. The other is to employ a new block interleaver to combat the tail effect of SOVA-based turbo code decoding. The simulation results show that the new SOVA with both modifications is able to obtain a similar result to that achieved by a maximum a posteriori (MAPI) algorithm with a random interleaver. In this paper, we also provide the results of the SOVA with the Battail's updating rule and compare them to those of the SOVA with the updating rule proposed by Hagenauer.

We consider the symbol-synchronous Gaussian L-out-of-K code-division multiaccess channel, and obtain the capacity region and the upper and lower bounds to the symmetric capacity. The capacity region is found to be the same with or without frame synchronism. The lower bound depends on the signature waveforms through the eigenvalues of the SNR-weighted crosscorrelation matrix. We find a sufficient condition for the signature waveform set to maximize this lower bound and give an algorithm to construct a set of signature waveforms satisfying the sufficient condition.>

The capacity region of a two-user Gaussian multiaccess channel with intersymbol interference (ISI) in which the inputs pass through respective linear systems and are superimposed before being corrupted by an additive Gaussian noise process is discussed. A geometrical method for obtaining the optimal input power spectral densities and the capacity region is presented. This method can be viewed as a nontrivial generalization of the single-user water-filling argument. It is shown that, as in the traditional memoryless multiaccess channel, frequency-division multiaccess (FDMA) with optimally selected frequency bands for each user achieves the total capacity of the multiuser Gaussian multiaccess channel with ISI. However, the capacity region of the two-user channel with memory is, in general, not a pentagon unless the channel transfer functions for both users are identical.>

The restriction to Gaussian inputs in the limiting expression for the capacity regions of memoryless Gaussian interference and multiple-access channels is shown to fall short of achieving capacity even if the inputs are allowed to be dependent and nonstationary. In addition, the equality between the limiting and the single-letter characterizations of memoryless multiple-access channel capacity is established directly, without recourse to independent coding theorems.>

The degradation due to complete asynchronism (at the codeword and symbol levels) in the total capacity, maximum rate-sum, of white Gaussian multiple-access channels is investigated. It is shown that asynchronism reduces the total capacity of a K-user channel by at most a factor of K. Moreover, this bound is achieved, in asymptotically high signal-to-noise ratios, by the TDMA signaling strategy. When the signaling strategies are optimally designed to maximize the asynchronous total capacity under bandwidth constraints, the authors find that in a two-user channel: (1) for a certain set of signal-to-noise ratios there is no degradation due to asynchronism, (2) for any bandwidth and signal-to-noise ratios the asynchronous total capacity is at least 88% of the synchronous total capacity, and (3) asynchronism has a vanishing small effect on total capacity for both low and high signal-to-noise ratios.>

Continuous-time additive white Gaussian noise channels with strictly time-limited and root-mean-square (RMS)-bandlimited inputs are studied. The capacity of the single-user and two-user RMS-bandlimited channels are found in easy-to-compute parametric forms and are compared to the classical formulas for the capacity of strictly bandlimited channels. In addition, channels are considered where the inputs are further constrained to be pulse-amplitude-modulated waveforms. The capacity of the single-user RMS-bandlimited PAM channel is shown to coincide with Shannon's capacity formula for the strictly bandlimited channel. This shows that the laxer bandwidth constraints precisely offsets the PAM structural constraint and illustrates a tradeoff between the time-domain and frequency-domain constraints. In the synchronous two-user channel, the pair of pulses that achieves the boundary of the capacity region is derived, and it is shown that the shapes of the optimal pulses depend not only on the bandwidth but also on the respective signal-to-noise ratios.>