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In this paper, we study feedback optimization problems that maximize theusers' signal to interference plus noise ratio (SINR) in a two-cell MIMObroadcast channel. Assuming the users learn their direct and interferingchannels perfectly, they can feed back this information to the base stations(BSs) over the uplink channels. The BSs then use the channel information todesign their transmission scheme. Two types of feedback are considered: analogand digital. In the analog feedback case, the users send their unquantized anduncoded CSI over the uplink channels. In this context, given a user's fixedtransmit power, we investigate how he/she should optimally allocate it to feedback the direct and interfering (or cross) CSI for two types of base stationcooperation schemes, namely, Multi-Cell Processing (MCP) and CoordinatedBeamforming (CBf). In the digital feedback case, the direct and cross linkchannel vectors of each user are quantized separately, each using RVQ, withdifferent size codebooks. The users then send the index of the quantizationvector in the corresponding codebook to the BSs. Similar to the feedbackoptimization problem in the analog feedback, we investigate the optimal bitpartitioning for the direct and interfering link for both types of cooperation.We focus on regularized channel inversion precoding structures and perform ouranalysis in the large system limit in which the number of users per cell ($K$)and the number of antennas per BS ($N$) tend to infinity with their ratio$\beta=\frac{K}{N}$ held fixed.

Base Station Cooperation with Feedback Optimization: A Large System Analysis