A novel low complexity data detection method for large scale MIMO systems

Massive multiple input multiple output (MIMO) is one of the most important techniques in fifth generation (5G) wireless communication systems and beyond where the main problem is how to deploy a very large number of antennas to serve a lot of users simultaneously using simple detection algorithms at the base station (BS). In this study, a novel, low-complexity matrix inversion method for signal detection is introduced. It is shown that the diagonal elements of the Gram matrix are much larger than the other elements with high probability. Next a sufficient condition for the convergence of this method is derived and an efficient algorithm is developed for symbol detection. Based on these results, and through extensive numerical experiments, it is demonstrated that the proposed algorithm outperforms the recently published ones in terms of performance and complexity.