Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks

Abstract

We study the downlink linear precoder design problem in a multi-cell dense heterogeneous network (HetNet). The problem is formulated as a general sum-utility maximization (SUM) problem, which includes as special cases many practical precoder design problems such as multi-cell coordinated linear precoding, full and partial per-cell coordinated multi-point transmission, zero-forcing precoding and joint BS clustering and beamforming/precoding. The SUM problem is difficult due to its non-convexity and the tight coupling of the users' precoders. In this paper we propose a novel convex approximation technique to approximate the original problem by a series of convex subproblems, each of which decomposes across all the cells. The convexity of the subproblems allows for efficient computation, while their decomposability leads to distributed implementation. {Our approach hinges upon the identification of certain key convexity properties of the sum-utility objective, which allows us to transform the problem into a form that can be solved using a popular algorithmic framework called BSUM (Block Successive Upper-Bound Minimization).} Simulation experiments show that the proposed framework is effective for solving interference management problems in large HetNet.

Accepted by IEEE Transactions on Wireless Communication

References in corpus (3)

• Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems
• Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks
• Improved Dual Decomposition Based Optimization for DSL Dynamic Spectrum Management

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