Detection Techniques in Uplink Massive MIMO Systems

Abstract

Devising low-complexity data detection techniques is one of the fundamental challenges in the uplink of massive multiple-input multiple-output (MIMO) wireless systems. Linear detection techniques such as zero-forcing (ZF) and minimum mean square error (MMSE) are shown to achieve near-optimal bit-error-rate (BER) performance in such systems. However, ZF/MMSE technique requires inversion of large-dimensional matrices which makes them practically infeasible. This motivates the development of alternate low-complexity inversionless detection techniques which are capable of achieving BER performance close to that of the ZF/MMSE detectors with comparatively less computations. Recently, there is an upsurge in research toward solving this crucial issue in massive MIMO systems. In particular, several detection algorithms have been proposed in the literature, which provides a better trade-off between BER performance and computational complexity. This chapter discusses the fundamentals of massive MIMO detection and also provides an overview of some of the recent state-of-the-art detection techniques. Simulation results on BER performance and computational complexity of these algorithms are also compared to draw useful insights. Furthermore, research scopes in massive MIMO detection are also discussed to provide possible research directions in the field.