Distributed downlink beamforming with cooperative base stations

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.