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In this paper, we consider multicell processing on the downlink of a cellular network to accomplish "macrodiversity" transmit beamforming.. The particular downlink beamformer structure we consider allows a recasting of the downlink beamforming problem as a virtual linear mean square error (LMMSE) estimation problem. We exploit the structure of the channel and develop distributed beamforming algorithms using local message passing between neighboring base stations. For 1-D networks, we use the Kalman smoothing framework to obtain a forward-backward beamforming algorithm. We also propose a limited extent version of this algorithm that shows that the delay need not grow with the size of the network in practice. For 2-D cellular networks, we remodel the network as a factor graph and present a distributed beamforming algorithm based on the sum-product algorithm. Despite the presence of loops in the factor graph, the algorithm produces optimal results if convergence occurs. Index Terms--Cooperative base stations, distributed algorithm, downlink beamforming, Kalman smoothing, linear mean square error (LMMSE), localized interference, message passing, multicell processing, multiple-input-multiple-output (MIMO), sum--product algorithm.

Sealing results for the sum capacity of the multiple access, uplink channel are provided for a flat-fading environment, with multiple-input--multiple-output (MIMO) links, when there is interference from other cells. The classical MIMO scaling regime is considered in which the number of antennas per user and per base station grow large together. Utilizing the known characterizations of the limiting eigenvalue distributions of large random matrices, the asymptotic behavior of the sum capacity of the system is characterized for an architecture in which the base stations cooperate in the joint decoding process of all users (macrodiversity). This asymptotic sum capacity is compared with that of the conventional scenario in which the base stations only decode the users in their cells. For the case of base station cooperation, an interesting "resource pooling" phenomenon is observed: in some cases, the limiting performance of a macrodiversity multiuser network has the same asymptotic behavior as that of a single-user MIMO link with an equivalent amount of pooled received power. This resource pooling phenomenon allows us to derive an elegant closed-form expression for the sum capacity of a new version of Wyner's classical model of a cellular network, in which MIMO links are incorporated into the model. Index Terms--Asymptotic sum capacity, base station cooperation, large system analysis, multiple-access channel (MAC), multiple-input--multiple-output (MIMO) channel, random matrices.

The design of space--time signals for noncoherent block-fading channels where the channel state information is not known a priori at the transmitter and the receiver is considered. In particular, a new algebraic formulation for the diversity advantage design criterion is developed. The new criterion encompasses, as a special case, the well-known diversity advantage for unitary space--time signals and, more importantly, applies to arbitrary signaling schemes and arbitrary channel distributions. This criterion is used to establish the optimal diversity-versus-rate tradeoff for training based schemes in block-fading channels. Our results are then specialized to the class of affine space--time signals which allows for a low complexity decoder. Within this class, space--time constellations based on the threaded algebraic space--time (TAST) architecture are considered. These constellations achieve the optimal diversity-versus-rate tradeoff over noncoherent block-fading channels and outperform previously proposed codes in the considered scenarios as demonstrated by the numerical results. Using the analytical and numerical results developed in this paper, nonunitary space--time codes are argued to offer certain advantages in block-fading channels where the appropriate use of coherent space--time codes is shown to offer a very efficient solution to the noncoherent space--time communication paradigm. Index Terms--Diversity-versus-rate tradeoff, generalized likelihood ratio test (GLRT) receivers, noncoherent channels, space--time coding.

In this correspondence, we propose an algorithm for computing the distance spectrum of a space-time trellis code achieving maximal diversity gain in quasi-static fading channels. We further present a state reduction technique for trellis codes that can reduce the complexity of the distance spectrum computation. We provide numerical results supporting the empirical evidence that a truncated union bound obtained from the distance spectrum provides an accurate characterization of the relative performance ordering of different space-time trellis codes and, therefore, it offers a tool for better space-time trellis code design. Index Terms--Distance spectrum, performance analysis, space-time coding, state reduction, union bound.

In this letter, we present a simple generalization of the maximum ratio combining principle for space-time coded systems. This result leads to a maximum-likelihood decoder implementation that does not depend on the number of receive antennas and avoids the loss in performance incurred in the decoders proposed by Tarokh and Lo and Biglieri et al. The insights offered by this decoding rule allow for a simple and elegant proof for the space--time code design criterion in systems with large number of receive antennas. We further present an upper bound on probability of error that captures the dependence of space-time code design on the number of receive antennas. Finally, we present a computationally efficient approach for constructing space-time trellis codes that exhibit satisfactory performance in systems with variable number of receive antennas. Index Terms--Code design, maximum ratio combining (MRC), multiple-input multiple-output (MIMO) systems, space-time coding.