In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each user's message is only routed to those that participate in the user's coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large.

Abstract-Capacity improvement from transmitter and receiver cooperation is investigated in a two-transmitter, two-receiver network with phase fading and full channel state information (CSI) available at all terminals. The transmitters cooperate by first exchanging messages over an orthogonal transmitter cooperation channel, then encoding jointly with dirty-paper coding. The receivers cooperate by using Wyner-Ziv compress-and-forward over an analogous orthogonal receiver cooperation channel. To account for the cost of cooperation, the allocation of network power and bandwidth among the data and cooperation channels is studied. It is shown that transmitter cooperation outperforms receiver cooperation and improves capacity over noncooperative transmission under most operating conditions when the cooperation channel is strong. However, a weak cooperation channel limits the transmitter cooperation rate; in this case, receiver cooperation is more advantageous. Transmitter-and-receiver cooperation offers sizable additional capacity gain over transmitter-only cooperation at low signal-to-noise ratio (SNR), whereas at high SNR transmitter cooperation alone captures most of the cooperative capacity improvement.Index Terms-Capacity, transmitter and receiver cooperation, dirtypaper coding, Wyner-Ziv compress-and-forward, power and bandwidth allocation, wireless ad hoc network.

A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of

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We compare the rates of one-shot and iterative con-the relative performance of iterative and one-shot cooperation. ferencing in a cooperative Gaussian relay channel. The relay and We show that one-shot cooperation is sufficient when the receiver cooperate via a conference, as introduced by Willems, in relay has a weak channel, but iterative cooperation can be which they exchange a series of communications over orthogonal links.~~~~~~~~~~~~~Ũne.n-htcneecn,dcd-n-owr D)i beneficial when the relay has a strong channel, provided that links. Under one-shot conferencing, decode-and-forward (DF) iS th ofrneln aaiyislre eas netgt capacity-achieving when the relay has a strong channel. On the the conference link capacity is large. We also investigate other hand, Wyner-Ziv compress-and-forward (CF) approaches conferencing rates in comparison to those of a full-duplex the cut-set bound when the conference link capacity is large. To relay channel. contrast with one-shot conferencing, we consider a two-round The rest of the paper is organized as follows. Section II iterative conference scheme; it comprises CF in the first round, defines the conferencing relay channel. The one-shot and and DF in the second. When the relay has a weak channel, the defive coperation res are Te inection and iterative scheme is disadvantageous. However, when the relay iterative cooperation strategies are presented in Section III. channel is strong, iterative cooperation, with optimal allocation Section IV contrasts the relative performance of one-shot and of conferencing resources, outperforms one-shot cooperation iterative cooperation, and Section V considers the iterative provided that the conference link capacity is large. When precise scheme with symmetric conference links. Then numerical allocation of conferencing resources is not possible, we consider iterative cooperation with symmetric conference links, and show examples of the cooperaion rates are illustrated in Secton VI, that the iterative scheme still surpasses one-shot cooperation, followed by conclusions in Section VII.albeit under more restricted conditions. II. SYSTEM MODEL