Distributed compression for MIMO coordinated networks with a backhaul constraint

We consider the uplink of a backhaul-constrained, MIMO coordinated network. That is, a single-frequency network with N + 1 multi-antenna base stations (BSs) that cooperate in order to decode the users' data, and that are linked by means of a common lossless backhaul, of limited capacity R. To implement the receive cooperation, we propose distributed compression: N BSs, upon receiving their signals, compress them using a multi-source lossy compression code. Then, they send the compressed vectors to a central BS, which performs users' decoding. Distributed Wyner-Ziv coding is proposed to be used, and is designed in this work. The first part of the paper is devoted to a network with a unique multi-antenna user, that transmits a predefined Gaussian space-time codeword. For such a scenario, the "compression noise" covariance at the BSs is optimized, considering the user's achievable rate as the performance metric. In particular, for N = 1 the optimum covariance is derived in closed form, while for N > 1 an iterative algorithm is devised. The second part of the contribution focusses on the multi-user scenario. For it, the achievable rate region is obtained by means of the optimum "compression noise" covariances for sum-rate and weighted sum-rate, respectively.