Restricted Search Space Exploration With Refinement for Symbol Detection in Uplink Massive MIMO

Massive multiple-input multiple-output (MIMO) is a promising technique to overcome the explosive increase in the demand for high-speed data, quality of service and energy efficiency for fifth generation (5G) and beyond wireless systems. Low-complexity symbol detection in massive MIMO is one of the challenging issues for their practical realization. The existing approximate matrix inversion based and matrix inversion less iterative symbol detection techniques suffer significant performance loss when the number of users increases in the system. Therefore, this article proposes a low-complexity restricted search space exploration based ordered iterative detection (REOD) technique to achieve superior performance in large user massive MIMO systems. The proposed low-complexity REOD technique iteratively prunes the discrepancy term associated with the previous estimation and further explores an improved estimate confined to a predefined search space. Convergence of the proposed REOD technique is analytically justified. An analytical expression for the approximate upper bound on the bit error rate is derived and corroborated by simulations. The obtained results prove the viability of the proposed REOD technique compared to the several existing state-of-the-art uplink massive MIMO detection techniques, both in terms of error performance and computational complexity.