Least Square Regressor Selection Based Detection for Uplink 5G Massive MIMO Systems

Abstract

Massive multiple-input multiple-output (MIMO) is a core component of next-generation 5G networks which groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency. However, uplink signal detection in massive MIMO system becomes inefficient and computationally complex with a larger number of antennas. In this paper, we propose an algorithm for the uplink detection based upon least square regressor selection problem. The results through simulations show that the proposed algorithm is computationally efficient and achieves near-optimal bit error rate (BER) performance in comparison to the conventional uplink detection algorithms. The proposed algorithm can provide a good tradeoff between BER and computational complexity and is suitable for uplink detection in massive MIMO systems.