Compressive sensing for feedback reduction in MIMO broadcast channels

We propose a generic feedback channel model, and compressive sensing based opportunistic feedback protocol for feedback resource (channels) reduction in MIMO Broadcast Channels under the assumption that both feedback and downlink channels are noisy and undergo block Rayleigh fading. The feedback resources are shared and are opportunistically accessed by users who are strong (users above a certain fixed threshold). Strong users send same feedback information on all shared channels. They are identified by the base station via compressive sensing. The proposed protocol is shown to achieve the same sum-rate throughput as that achieved by dedicated feedback schemes, but with feedback channels growing only logarithmically with number of users.