Distributed Filter Design and Power Allocation for Small-Cell MIMO Networks

A primary challenge for deploying dense small-cell networks comes from the lack of practical techniques that efficiently handle the increased network interference at a low cost. This has aroused considerable interest in the design of distributed precoder/combiner coordination techniques that leverage channel reciprocity, while relying on the local channel state information (CSI) available at each communication end. We present, in this paper, a power-efficient distributed coordination technique for dense small-cell multiple-input multiple-output (MIMO) networks. We optimize the linear filters by minimizing the transmit power subject to target signal-to- interference-plus-noise ratios (SINRs). Although this strategy enhances the power efficiency, the considered optimization problem is non-convex and not directly solvable even under centralized coordination. To address this difficulty, we propose distributed filter adaptation and power allocation techniques that are based on the primal and its dual problem formulations. Under this construction, the two sub-problems, i.e., the linear filter design and power allocation problems, are separable. To solve them, we devise the distributed Jacobi-type power allocation and maximum SINR filter design techniques. Improved power efficiency of the proposed technique as compared to other existing distributed techniques is evidenced.