Low-Complexity Precoding for Sum Rate Maximization in Downlink Massive MIMO Systems

초록

We propose a precoding scheme to improve the downlink sum rate for a multicell massive multiple-input multiple-output( MIMO) system. We first present a low-complexity approach based on dirty paper coding and zero-forcing that combines a reduced form of QR decomposition and an orthogonal projection. We formulate a downlink sum rate optimization problem that takes both intracell and intercell interference into account, and then we use the convex conjugate to transform the problem into an unconstrained dual problem to find an optimal solution by applying a quasi-Newton algorithm with low complexity per iteration. We prove that the proposed algorithm exhibits faster convergence than other methods, and the numerical results verify that the proposed precoding design outperforms conventional precoding methods in multicell massive MIMO systems.

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