Efficient and Low-Complexity Iterative Detectors for 5G Massive MIMO Systems

Abstract

The global bandwidth shortage in the wireless communication sector has motivated the study and exploration of sub-6 GHz wireless access technology known as massive Multiple-Input Multiple-Output (MIMO). Massive MIMO groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency. Although massive MIMO provides enormous benefits, it has to overcome some fundamental implementation issues before it can be implemented for 5G networks. One of the fundamental issues in Massive MIMO systems is uplink signal detection, which becomes inefficient and computationally complex with a larger number of antennas. In this paper, we propose three iterative algorithms to address the issues of uplink signal detection in massive MIMO systems. The simulation results, compared to the traditional detection algorithms, show that the proposed iterative massive MIMO uplink signal detection algorithms are computationally efficient and can achieve near-optimal Bit Error Rate (BER) performance. Additionally, we propose novel hardware architectures for the proposed detection algorithms to identify the required physical components and their interrelationships.