Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogenous Networks

Abstract

We consider the interference management problem in a multicell MIMO heterogenous network. Within each cell there are a large number of distributed micro/pico base stations (BSs) that can be potentially coordinated for joint transmission. To reduce coordination overhead, we consider user-centric BS clustering so that each user is served by only a small number of (potentially overlapping) BSs. Thus, given the channel state information, our objective is to jointly design the BS clustering and the linear beamformers for all BSs in the network. In this paper, we formulate this problem from a {sparse optimization} perspective, and propose an efficient algorithm that is based on iteratively solving a sequence of group LASSO problems. A novel feature of the proposed algorithm is that it performs BS clustering and beamformer design jointly rather than separately as is done in the existing approaches for partial coordinated transmission. Moreover, the cluster size can be controlled by adjusting a single penalty parameter in the nonsmooth regularized utility function. The convergence of the proposed algorithm (to a local optimal solution) is guaranteed, and its effectiveness is demonstrated via extensive simulation.

Accepted by IEEE Journal on Selected Areas in Communications, special issues on Large-Scale multiple-antenna systems

References in corpus (4)

• Consistency of the group Lasso and multiple kernel learning
• Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters
• Group-Lasso on Splines for Spectrum Cartography
• Lower Bounds Optimization for Coordinated Linear Transmission Beamformer Design in Multicell Network Downlink

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