Feedback Reduction and Efficient Antenna Selection for Massive MIMO System

This paper considers the problem of acquiring the channel state information (CSI) at the base station in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, acquiring the CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna at the base station. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a massive MIMO system in the broadcast channel. The proposed strategy has to reduce both the CSI feedback and the computational complexity, and also to improve the system sum-rate. Contrary to what is generally proposed in the literature, the decision in our strategy is performed in a distributed fashion at the users. Named Successive Removal for Antenna Selection, the strategy proposed in this work can be implemented with three proposed schemes, which aims to solve differently the tradeoff between the computational complexity and sum-rate performance. Computer simulations show that the proposed algorithms are able to achieve good performances while a significant reduction in both CSI feedback overhead and computational complexity is observed.