An Efficient Feedback Scheme Using Compressive Sensing for MIMO Broadcast Channel with Random Beamforming

In this paper we proposes an efficient feedback scheme using compressive sensing (CS) for MIMO broadcast channel(BC) with random beamforming(RBF). Feedback resources are opportunististically accessed by strong users whose SINR is larger than threshold. Strong users transmit same feedback information on feedback channel and they are indentified by BS using CS. There is reduction of the feedback overhead via CS. Besides, we can achieve sum-rate throughput as full feedback. To exploit CS, feedback signal must be sparse. However, because there exist a trade-off between the sparsity and multiplexing gain, we must know how to decide K-sparsity and threshold. Therefore, we drive relation between K-spasity and threshold. These are suitable to ` actual' BC feedback channel with CS.