MIMO and cloud radio access network (C-RAN) are promising techniques for implementing future wireless communication systems, where a large number of antennas are deployed either being co-located at the base station or totally distributed at separate sites called remote radio heads (RRHs), both to achieve enormous spectrum efficiency and energy efficiency gains. Here, we consider a general antenna deployment method for wireless networks, termed multi-antenna C-RAN, where a flexible number of antennas can be equipped at each RRH to more effectively balance the performance and fronthaul complexity tradeoff beyond the conventional massive MIMO and single-antenna C-RAN. To coordinate and control the fronthaul traffic over multi-antenna RRHs, under the uplink communication setup, we propose a new “spatial-compression-and-forward (SCF)” scheme, where each RRH first performs a linear spatial filtering to denoise and maximally compress its received signals from multiple users to a reduced number of dimensions, then conducts uniform scalar quantization over each of the resulting dimensions in parallel, and finally sends the total quantized bits via a finite-rate fronthaul link to the baseband unit (BBU) for joint information decoding. Under this scheme, we maximize the minimum SINR of all users at the BBU by a joint resource allocation over the wireless transmission and fronthaul links. Specifically, each RRH determines its own spatial filtering solution in a distributed manner to reduce the signaling overhead with the BBU, while the BBU jointly optimizes the users' transmit power, the RRHs' fronthaul bits allocation, and the BBU's receive beamforming with fixed spatial filters at individual RRHs. Numerical results show that, given a total number of antennas to be deployed, multi-antenna C-RAN with the proposed SCF and joint optimization significantly outperforms both massive MIMO and single-antenna C-RAN under practical fronthaul capacity constraints.
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