The authors propose a concatenated scheme to reduce the peak-to-average power ratio (PAPR) in coded orthogonal frequency-division multiplexing (OFDM) systems. First, they employ a label-bits-inserted encoder of a random-like code to achieve selected mapping (SLM). Then they set a threshold at the selector to limit the number of candidate sequences. Both analytical and numerical results show that the complexity of the SLM implemented by the label-bit-inserted encoder can be significantly reduced by threshold limited selection. With the same complexity, the performance of PAPR reduction is improved. The proposed concatenated PAPR reduction scheme enjoys many advantages including low-complexity, small overhead, no side information transmission and no performance loss or additional complexity at the receiver.

We consider the sum-rate maximization via linear preceding in downlink MIMO-OFDM systems with quantized feedback. We address the preceding codebook design based on the capacity measure by introducing a new distance metric. We propose a codebook structure and its associated design algorithm that allows for significant reduction in the memory requirement and computational complexity in real-time system implementation. We then provide a system design approach comprising of four main ingredients: (i) a multi-rank beamforming (MRBF) scheme, (ii) an efficient CQI-based precoder selection algorithm, (iii) reduced feedback strategies, and (iv) novel channel quality indicator (CQI) combining. Our simulation results show that the proposed MRBF scheme can approach the precoding upper bounds with relatively few feedback bits. Moreover, with the same number of bits, the proposed scheme simultaneously achieves higher throughput and lower computational complexity in comparison to the other existing precoding schemes.

We treat the problem of designing low-density parity-check (LDPC) codes to approach the capacity of relay channels. We consider an efficient analysis framework that decouples the factor graph (FG) of aB-block transmission into successive partial FGs, each of which denotes a two-block transmission. We develop design methods to find the optimum code ensemble for the partial FG. In particular, we formulate the relay operations and the destination operations as equivalent virtual MISO and MIMO systems, and employ a binary symmetric channel (BSC) model for the relay node output. For AWGN channels, we further develop a Gaussian approximation for the detector output at the destination node. Jointly treating the relay and the destination, we analyze the performance of the LDPC-coded relay system using the extrinsic mutual information transfer(EXIT) chart technique. Furthermore, differential evolution is employed to search for the optimum code ensemble. Our results show that the optimized codes always outperform the regular LDPC codes with a significant gain; in the AWGN case, when Protocol-II is employed and the relay is close to the source, the optimized code performs within 0.1dB to the capacity bound.

We treat the problem of outage minimization via power control in MIMO systems with quantized feedback. We formulate the optimal quantized power control design for a general MIMO system and provide the numerical procedure for finding the optimal solution. Our results not only extend but also show the deficiency of the existing quantized power control schemes for MISO systems. We further propose a design based on the pre-evaluation of the packet error rate performance of practical MIMO systems employing short-length LDPC codes and QAM modulations and with possibly unreliable feedback links. It is demonstrated that with only a few bits of feedback, the resulting quantized power control strategy achieves considerable gain over a system without power control.

We consider an optimal resource allocation strategy for cooperative relaying-enabled OFDMA multi-hop wireless networks. A cross-layer optimization problem is formulated that maximizes the balanced end-to-end throughput under the routing and the PHY/MAC constraints. A dual method is employed to solve the problem efficiently and optimally. A cooperative relaying technique is incorporated into the framework by introducing virtual links and nodes. Half-duplex operation of the radios is assumed, and mutual interference between the links is explicitly modeled to allow maximal spatial reuse of the spectral resources. Numerical results are provided to demonstrate how the bottleneck phenomenon typical in multi-hop networks can be alleviated by the proposed technique to yield significant improvement in the throughput.

We treat the problem of quantization codebook design for MIMO precoding schemes. We propose a design criterion based on the capacity measure which is different from the maximum mutual-minimum-distance conventionally used to design the codebook. The latter criterion is derived from SNR maximization which is not necessarily the capacity- optimal quantization strategy. While the capacity expression does not directly define a valid distance metric for the design, a bound on the capacity expression can be used to formulate the quantization codebook design. We introduce a new distance metric on the Grassmanian manifold which is used to design the optimal precoder codebook. While the original formulation can be used for the (space) correlated channel model, we propose a differential codebook design in order to track changes in the channel statistics when the channel is correlated in time (or in frequency, e.g., across different tones in OFDM systems). Simulation results has shown considerable improvement through the proposed codebook design both for single user (SU-) and multiple user (MU-) MIMO systems.

An optimal resource allocation strategy for OFDMA multi-hop wireless backhaul networks is considered. A cross-layer optimization problem is formulated that maximizes the balanced end-to-end throughput under the routing and the PHY/MAC constraints. A dual method is employed to solve the problem efficiently and optimally by decoupling it into different layers as well as into different OFDM tones. A cooperative relaying technique is incorporated into the framework to improve the performance. Mutual interference between the links is explicitly modeled to allow maximal spatial reuse of the spectral resources, and half-duplex operation of the radios is assumed. The numerical results exhibit how the bottleneck phenomenon typical in multi-hop backhaul networks can be alleviated by the proposed techniques to yield significant improvement in the throughput.

We consider the use of linear constellation preceding and linear equalization in a multicarrier system to obtain improved performance over multipath fading channels at a low complexity. We split the full set of subcarriers into smaller groups and spread the data symbols assigned to each group via precoding matrices. To obtain diversity order gains at a given data rate, we derive the optimal split of the subcarriers (optimal grouping) and the optimal number of symbols assigned to each group (optimal loading) using a diversity-multiplexing tradeoff analysis. We also derive the necessary and sufficient optimality conditions for the precoder design and provide examples of such optimal precoders.

We consider the design of efficient anti-jamming coding techniques for secondary usage of spectrum in cognitive radio. Specifically, we consider two coding schemes, rateless coding and piecewise coding. Both coding schemes have small overhead, as well as low-complexity encoding and decoding. The proposed piecewise coding also enjoys the advantages of parallel decoding and fast response to packet loss. For piecewise coding, we propose two design methods to build short block codes with small number of parity checks by incorporating the jamming rate. We analyze the throughput performance of the secondary users systems employing either anti-jamming coding technique. The performance results demonstrate that both coding techniques provide reliable transmission with high throughput and small redundancy. The piecewise coding using the designed short codes provides better performance with smaller overhead if the jamming rate is not high.

In this study, we consider the design of LDPC codes for cooperative relay systems in half-duplex mode (namely, "cheap" relay) that are of practical interest. We transform the code design problem into the design of rate-compatible LDPC codes where the SNRs in different parts of one codeword are different. Due to the SNR variation, the conventional density evolution (DE) or extrinsic-mutual-information-transfer (EXIT) is not capable of accurately predicting the code performance. We develop a more refined definition of code ensembles and present a modified DE based algorithm related to the new relay code structure. Our results show that the proposed algorithm is more accurate than the conventional DE or EXIT in this case. We further employ the code optimization based on differential evolution. The optimized "cheap" relay code significantly outperforms existing codes.

We consider the problem of designing space-time- frequency linear dispersion (LD) codes in wideband multiple- input multiple-output (MIMO) antenna systems employing orthogonal-frequency-division-multiplexing (OFDM). Three design methods are presented and discussed, which involve: (1) minimizing the average block error rate, (2) maximizing the ergodic mutual information, and (3) a two-step procedure considering the optimization of the mutual information as well as the average block error rate, respectively. For any set of subcarriers, any number of OFDM symbol intervals, any number of transmit/receive antennas and any statistical fading channel model, the corresponding optimized LD code matrices are numerically computed via a stochastic gradient descent algorithm. Code design examples are provided and discussed for communication systems operating over a realistic 3GPP spatial channel model.

We consider space-time transceiver architectures for multiple access fading channels with K users, each equipped with multiple transmit antennas. Each user employs an orthogonal or a quasi-orthogonal design as an inner code. At the multi-antenna receiver, successive group interference suppression strategies based on the linear zero-forcing or linear MMSE filters are employed in some fixed or channel dependent order. These strategies exploit the specific structure of the inner codes to yield high diversity orders while preserving the decoupling property of the constituent inner codes thereby enabling the use of simple demodulators. Motivated by the special structure of the effective channel matrix induced by the inner codes, we obtain several new results on the QR and eigenvalue decompositions of certain structured random matrices. Using these random-matrix distribution results, we characterize the high-SNR performance limits of the transceiver architectures under consideration by obtaining their diversity-multiplexing tradeoff curves.

The problem of throughput maximisation in a wireless multiple-input multiple-output (MIMO) system using a quantised feedback, which is an appropriate model for practical systems with limited feedback capacity, is considered. Unlike the ergodic capacity that can be achieved through power control only, maximising the throughput in the block fading channels is based on appropriate rate control strategy. The optimal quantised rate control design for general MIMO systems is formulated and a gradient descent search algorithm to find the optimal solution is employed. It is seen that the proposed quantised rate control scheme with only a few bits of feedback considerably improves the throughput of a MIMO system. With the same amount of feedback overhead, the proposed quantised rate control with constant power is compared with the optimal quantised power control strategy with an optimised constant rate, and the result demonstrates the importance of rate control in throughput maximisation. The effect of quantised rate control in MIMO systems employing different automatic repeat request schemes is also investigated.

Multihop wireless backhual networks are emerging as a cost-effective solution to provide ubiquitous and broadband access to meet the rapidly increasing demands of multimedia applications. In this paper, we consider the joint optimal design of routing, medium access control (MAC) scheduling and physical layer resource allocation for such networks, where beamforming antenna arrays are equipped at the physical layer. The notion of transmission set (TS) is introduced to separate the physical layer operations from those at the upper layers; and a column generation approach is employed to efficiently identify the TSs. We then apply the dual decomposition method to decouple the routing and scheduling subproblems, which are performed at different layers and are coordinated by a pricing mechanism to achieve the optimal overall system objective. To efficiently support multimedia traffic, an admission control criterion is considered for the system objective. The performance of the proposed scheme is verified by simulation results, and the impact of the physical layer capabilities on the network performance is evaluated. We also discuss the implementation issues of the cross-layer scheme based on the IEEE 802.16 mesh mode.

We consider the design of efficient rate-compatible (RC) irregular repeat accumulate (IRA) codes over a wide code rate range. The goal is to provide a family of RC codes to achieve high throughput in hybrid automatic repeat request (ARQ) scheme for high-speed data packet wireless systems. As a subclass of low-density parity-check codes, IRA codes have an extremely simple encoder and a low-complexity decoder while providing capacity approaching performance. We focus on a hybrid design method which employs both puncturing and extending. We propose a simple puncturing method based on minimizing the maximal recoverable step of the punctured nodes. We also propose a new extending scheme for IRA codes by introducing the degree-1 parity bits for the lower rate codes and obtaining the optimal proportions of extended nodes through density evolution analysis. The throughput performance of the designed RC-IRA codes in hybrid ARQ is evaluated for both AWGN and block fading channels. Simulation results demonstrate that our designed RC codes offer good error correction performance over a wide rate range and provide high throughput, especially in the high and low signal-to-noise ratio regions.

A cross-layer design approach is considered for joint routing and resource allocation for the physical (PHY) and the medium access control (MAC) layers in multihop wireless backhaul networks. The access points (APs) are assumed to be equipped with multiple antennas capable of both transmit and receive beamforming. A nonlinear optimization problem is formulated, which maximizes the fair throughput of the APs in the network under the routing and the PHY/MAC constraints. Dual decomposition is employed to decouple the original problem into smaller subproblems in different layers, which are coordinated by the dual prices. The network layer subproblem can be solved in a distributed manner and the PHY layer subproblem in a semidistributed manner. To solve the PHY layer subproblem, an iterative minimum mean square error (IMMSE) algorithm is used with the target link signal-to-interference-and-noise-ratio (SINR) set dynamically based on the price generated from the upper layers. A scheduling heuristic is also developed, which improves the choice of the transmission sets over time. Simulation results illustrate the efficacy of the proposed cross-layer design.

Current downlink scheduling algorithms in the (enhanced) third-generation (3G) cellular packet systems exploit instantaneous channel status of multiple users, but most of them are blind to traffic information. To improve TCP users' perception of quality-of-services (QoSs), characterized by response delay, goodput, and always-on connectivity, we propose a cross-layer hierarchical scheduler with traffic awareness and channel dependence to properly prioritize buffer and radio resource allocation among different TCP classes. The scheduler has two tiers: at the IP layer, an intrauser scheduler enhances a common practice, i.e., the DiffServ-based buffer management, by dequeuing same-user TCP packets according to per-class specified and measured responsiveness; at the MAC layer, an interuser scheduler transmits the dequeued packets by considering the opportunistic channel states, mean throughput, and class ID of all users. Both tiers consider the online measured throughput, a cross-layer metric, to achieve resource and performance fairness and TCP classification. Experiments show that, compared with (variations of) proportional fairness (PF) and other schemes, our scheduler can notably speed up time-critical interactive TCP services (HTTP and TELNET) or TCP slow-starts with minor cost to bulk file transfer (FTP) or long-lived flows. It offers scalable and low-cost TCP performance enhancement over the emerging cellular systems

A distributed joint routing and medium access control (MAC) algorithm is proposed for lifetime maximization of wireless sensor networks. By adopting the flow contention graph model and the resulting MAC constraints, the problem can be formulated into a linear programming problem, which can be solved distributively using dual decomposition. However, the message passing overhead of such a solution is high, since the information exchange must occur among the interfering links as well as the communicating links. In this work, the MAC layer constraints are relaxed in the form of a penalty function, which facilitates distributed optimization using only the collision statistic that each node can accumulate essentially at no extra cost. The resulting algorithm solves a convex optimization problem by a distributed primal-dual approach, where the network layer problem is solved in the dual domain, and the MAC layer problem is solved in the primal domain.

We propose a call (user) admission control (CAC) algorithm and a scheduling framework for real-time services in the enhanced third-generation (3G) cellular systems, e.g., WCDMA HSDPA or cdma2000 HDR systems, where multiple IP users share a time-slotted downlink packet channel in each cell. At the user or flow level, the CAC algorithm maximizes user accommodations under the QoS constraint, e.g., per-user expectation of profile rate, and the constraint of location-dependent resource availability. At the packet level, our scheduling framework, named maximum cost deduction (MCD), derives two algorithms - both are QoS-aware and channel-dependent: One is called real-time MCD (rt-MCD), which minimizes a delay-derived cost function of backlogged packets at the smallest timescale; the other is called non-real-time MCD (nrt-MCD), which balances between the real-time delay deduction and the non-real-time (i.e., large-timescale) per-user fairness. The cross-layer designed CAC and MCD algorithms exploit multi-user diversity based on online measured radio resource allocation. Together they provide high system efficiency and a balance between flow-level QoS (e.g. the aggregate goodput and the blocking rate of newly arrived users) and packet-level QoS (e.g., the packet queueing delay or loss). Extensive simulations and comparisons with the prior art show that our algorithms can deliver efficient real-time services and remain robust to different load scenarios that vary according to system dynamics and/or user mobility

We consider the multiplexed coding design for cooperative communications. The ideal multiplexed coding, which outperforms the superposition coding in theory, is difficult to implement with practical error-correction codes. We therefore introduce a partially multiplexed (PMP) coding scheme to approach the performance of fully multiplexed coding scheme. We then design the PMP coding using irregular repeat accumulate (IRA) codes. We also present a practical superposition coding scheme with two decoding methods. The outage analysis shows that all these schemes perform very close to lower cooperation bound. The simulation results demonstrate that both PMP and practical superposition block Markov coding for two-user cooperation provide significant gain over the non-cooperative system.

A joint routing and medium access control (MAC) algorithm is proposed for lifetime maximization of distributed wireless sensor networks. By adopting the flow contention graph model and the resulting MAC constraints, the problem can be formulated into a linear program (LP) with separable structure, which can be solved distributively using dual decomposition. However, the message passing overhead of such a solution is still high, since the information exchange must occur among the interfering links as well as the communicating links. In this work, the MAC layer constraints are relaxed in the form of a penalty function, which facilitates distributed optimization using only the collision statistic that each node can accumulate essentially at no extra cost. The resulting algorithm solves a convex optimization problem by a distributed primal-dual approach, where the network layer problem is solved in the dual domain, and the MAC layer problem is solved in the primal domain.

In this paper we propose a systematic procedure for designing optimal lattice (space-time) codes. By employing stochastic optimization techniques we design lattice codes with minimum error rates when lattice decoders are employed at the receiver. Our design methodology can be tailored to obtain optimal lattice (space-time) codes for any fading statistics and SNR of interest. Further, we obtain fundamental lower bounds on the error probabilities yielded by lattice decoders and characterize their asymptotic behavior

We consider the design of efficient rate-compatible (RC) irregular repeat accumulate (IRA) codes, a subclass of LDPC codes, over a wide code rate range. The goal is to provide a family of RC codes to achieve high throughput in hybrid automatic repeat request (ARQ) scheme for high-speed data packet wireless systems. We focus on a hybrid design method which employs both puncturing and extending. We propose a simple puncturing method based on minimizing the maximal recoverable step of the punctured nodes and a new extending scheme by introducing the degree-1 parity bits for the lower rate codes and obtaining the optimal proportions of extended nodes through density evolution analysis. Simulation results show that our designed RC codes offer good error correction performance over a wide rate range and provide high throughput, especially in the high and low SNR regions

We propose a call (user) admission control (CAC) algorithm and a scheduling framework for real-time services in the third-generation (3G) and beyond cellular systems, where multiple users share a downlink packet channel in each cell. At the user or flow level, the CAC algorithm maximizes user accommodations under the QoS constraint, e.g., per-user expectation of profile rate, and the constraint of location-dependent resource availability. At the packet level, our scheduling framework, named maximum cost deduction (MCD), derives QoS-aware and channel-dependent algorithms (rt-MCD and nrt-MCD), which minimize a delay -derived cost function of backlogged packets at different timescales. The cross-layer designed CAC and MCD algorithms exploit multi-user diversity based on online measured radio resource allocation. Together they provide high system efficiency and balance between flow-level QoS, e.g. aggregate goodput and the blocking rate of newly arrived users, and packet- level QoS, e.g., the packet queueing delay or loss.

Fast downlink scheduling algorithms play a central role in determining the overall performance of high-speed cellular data systems, characterized by high throughput and fair resource allocation among multiple users. We propose a flexible channel-dependent downlink scheduling scheme, named the (weighted) alpha-rule, based on the system utility maximization that arises from the Internet economy of long-term bandwidth sharing among elastic-service users. We show that the utility as a function of per-user mean throughput naturally derives the alpha-rule scheme and a whole set of channel-dependent instantaneous scheduling schemes following different fairness criteria. We evaluate the alpha-rule in a multiuser CDMA high data rate (HDR) system with space-time block coding (STBC) or Bell Labs layered space-time (BLAST) multiple-input multiple-output (MIMO) channel. Our evaluation shows that it works efficiently by enabling flexible tradeoff between aggregate throughput, per-user throughput, and per-user resource allocation through a single control parameter. In other words the Alpha-rule effectively fills the performance gap between existing scheduling schemes, such as max-C/I and proportional fairness (PF), and provides an important control knob at the media-access-control (MAC) layer to balance between multiuser diversity gain and location-specific per-user performance.

In this paper we propose a systematic procedure for designing minimum-error-rate lattice (space-time) codes. By employing stochastic optimization techniques we design lattice (space-time) codes with minimum error rate when maximum likelihood (ML) detection is employed. Our design methodology can be tailored to optimize lattice (space-time) codes for any fading statistics and SNR of interest

The Cayley differential (CD) codes constitute a systematic way to construct differential unitary space-time modulations for noncoherent communication in multiple-antenna systems. The original CD codes are designed based on the criterion of maximizing the expected distance between codeword pairs. However, in practical systems, it is more sensible to design the codes according to the minimum error rate criterion. The main difficulty in such a design is that the error probability does not admit a closed-form expression and, thus, conventional optimization methods cannot be applied. In this paper, we formulate the minimum error-rate CD code design as an unconstrained stochastic optimization problem, and employ the stochastic approximation technique with gradient estimation to solve it. Simulation results show that codes generated by the proposed design procedure generally outperform the CD codes designed by maximizing the expected distance between codeword pairs and the Cayley threaded algebraic space-time codes that satisfy the full rank criterion. The new CD codes also enjoy better or comparable performance over other group based or nongroup designs.

In this paper, we propose to design linear-dispersion (LD) codes by minimizing the union bound based on the exact pairwise error probability (PEP). We find that the original programming is not convex, and we present a convex relaxation to the optimization problem. We employ the gradient descent methods to numerically search the optimum dispersion matrices. Simulation results show that codes optimized by the new criterion generally outperform the codes designed based on algebraic number theory. When the knowledge of spatial-fading correlation is available in advance for the design, significant gain relative to the codes designed without knowledge of channel correlation can be achieved by taking into account the correlation structure while performing the optimization. We demonstrate how to exploit knowledge of transmit and receive correlation in designing the LD codes. Numerical and simulation examples show that knowledge of transmit correlation has a large impact on the optimum performance of the LD codes. Furthermore, additional gain can be achieved from the knowledge of receive correlation.

Handoff and cell site selection schemes in multi-cell cellular systems are traditionally developed for mobile stations (MS) of dedicated (circuit-switched) channels to/from base stations (BS). The schemes usually only consider physical-layer signal quality in decision making. In high-speed packet access systems, where a downlink channel is being shared by multiple users within each cell, those schemes are subject to local congestion and asymmetric packet call blocking across multiple cells. A way to reduce the hot-spots and alleviate asymmetry loading in such systems is the target of our study. To do so, we formulate the handoff and cell site selection procedures into a problem of iterative optimal channel assignment in multiple cells, and approximately solve the issue by incorporating a distributed load-awareness scheme into the procedures in order to keep the complexity low but practicality high. Extensive experiments show the effectiveness of our scheme and its advantages over the legacy schemes in load balancing and congestion reduction. With our scheme, a multi-cell wireless system in support of high-speed packet data access can accommodate more satisfied users and be more robust to asymmetric load dynamics across the whole system.

High-speed cellular data systems demand fast downlink scheduling algorithms and multiple-input multiple-output (MIMO) techniques. The associated multiuser diversity and antenna diversity play a central role in achieving high system throughput and fair resource allocation among multiple users. For such systems we evaluate the cross-layer interactions between channel-dependent scheduling schemes and MIMO techniques, such as space-time block coding (STBC) or Bell Laboratories Layered Space-Time (BLAST), and propose a new scheduling algorithm named the alpha-rule. The evaluation shows that the STBC/MIMO provides a reliable channel but at a certain cost of spectral efficiency. Comparatively BLAST/MIMO provides larger capacity and enables higher scheduling throughput. Thus BLAST/MIMO may be a more suitable technique for high-rate packet data transmission at the physical layer. At the medium access control (MAC)-layer, the alpha-rule is shown to be more flexible or efficient to exploit the diversity gains than the exiting max-C/I or proportionally fair (PF) scheduling schemes. It enables online tradeoff between aggregate throughput, per-user throughput, and per-user resource allocation.

We investigate a wireless system of multiple cells, each having a downlink shared channel in support of high-speed packet data services. In practice, such a system consists of hierarchically organized entities including a central server, Base Stations (BSs), and Mobile Stations (MSs). Our goal is to improve global resource utilization and reduce regional congestion given asymmetric arrivals and departures of mobile users. For this purpose, we propose a scalable cross-layer framework to coordinate packet-level scheduling, call-level cell-site selection and handoff, and system-level loading balancing based on load, throughput, and channel measurements at different layers. In this framework, an opportunistic scheduling algorithm---the weighted Alpha-Rule---exploits multiuser diversity gain in each cell independently, trading aggregate (mean) downlink throughput for fairness and minimum rate guarantees among MSs. Each MS adapts to its channel dynamics and the load fluctuations in neighboring cells, in accordance with MSs' mobility and their arrivals or departures, by initiating load-aware handoff and cell-site selection. The central server adjusts the scheduling parameters of each cell to coordinate cells' coverage, or cell breathing, by prompting distributed MS handoffs. Across the whole system, BSs and MSs constantly monitor their load, throughput, or channel quality in order to facilitate the overall system coordination.Our specific contributions in such a framework are highlighted by the minimum-rate guaranteed Weighted Alpha-Rule scheduling, the load-aware MS handoff/cell-site selection, and the Media Access Control (MAC)-layer cell breathing. Our evaluations show that the proposed framework can improve the global resource utilization and load balancing, which translates into a smaller blocking rate of MS arrivals without extra resources, while the aggregate throughput remains roughly the same or improved around the hot-spots. Our tests also show that the coordinated system is robust to dynamic load fluctuations and is scalable to both system size and MS population.

Abstract We consider dynamic channel management (DCM), more specifically power control and channel allocation, in multi‐carrier multi‐antenna wireless cellular systems. A quasi‐static channel model is assumed such that the channels remain approximately time‐invariant within each packet. On a packet‐by‐packet basis, the mobile station (MS) receivers feed back the DCM parameters to the corresponding base station (BS) transmitters in order to minimize the transmission power and strive to satisfy every individual user's data‐rate request. While optimum, centralized DCM for all active cells typically requires solution of a non‐convex optimization problem (which is subject to local minima) and requires intense channel feedback to a central controller. We instead consider sub‐optimal distributed DCM, where each individual cell locally optimizes its own performance based on the local channel information. In particular, we compare three distributed DCM schemes, namely the two‐dimensional DCM, which jointly adjusts both spatial and frequency sub‐channels of each BS–MS link, the one‐dimensional DCM, which adjusts only the frequency sub‐channels and the scalar DCM, which adjusts each BS–MS link by one scalar power coefficient. These DCM schemes are investigated in multi‐cell environments with realistic parameters; and it is seen that due to the multiple antennas, the maximum supportable rate (i.e. the rate supported by practically finite transmission power) is significantly increased, for example by a factor of two for users using four antennas and close to cell boundary. Copyright © 2004 John Wiley & Sons, Ltd.