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Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness

By Yongming Huang, Gan Zheng, Mats Bengtsson, Kai-Kit Wong, Luxi Yang and Bjorn Ottersten


This paper addresses coordinated downlink beamforming optimization in multicell time-division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on the Pareto boundary with max-min rate fairness, we first develop a two-step centralized optimization algorithm to design the joint beamforming vectors. This algorithm can achieve a further sum-rate improvement over the max-min optimal performance, and is shown to guarantee max-min Pareto optimality for scenarios with two base stations (BSs) each serving a single user. To realize a distributed solution with limited intercell communication, we then propose an iterative algorithm by exploiting an approximate uplink-downlink duality, in which only a small number of positive scalars are shared between cells in each iteration. Simulation results show that the proposed distributed solution achieves a fairness rate performance close to the centralized algorithm while it has a better sum-rate performance, and demonstrates a better tradeoff between sum-rate and fairness than the Nash Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201

Topics: Computer Science - Information Theory
Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
Year: 2012
DOI identifier: 10.1109/TWC.2012.061912.111751
OAI identifier:

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