Abstract

In a multi-user MIMO (MU-MIMO) network, an AP with M antennas can only serve up to M users out of a large user population. The M users' rates are inter-coupled and depend on their channel orthogonality. Substantial theoretical studies focused on selecting users to maximize capacity, but they require feedback of channel state information (CSI) from all users. The resulting overhead can easily overwhelm useful data in large scale networks. In this paper, we propose a scalable user selection mechanism called orthogonality probing based user selection (OPUS). OPUS only requires up to M rounds of CSI feedback. In each round, it employs a novel probing mechanism that enables a user to evaluate its orthogonality with existing users, and a distributed contention mechanism that singles out the best user to feedback its CSI. Software-radio based implementation and experimentation shows that OPUS significantly outperforms traditional user selection schemes in both throughput and fairness.

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