High Precision Low Complexity Matrix Inversion Based on Newton Iteration for Data Detection in the Massive MIMO

摘要

Currently, massive multiple-input multiple-output (MIMO) is one of the most promising wireless transmission technologies for 5G. Massive MIMO requires handling with large-scale matrix computation, especially for matrix inversion. In this letter, we find that matrix inversion based on Newton iteration (NI) is suitable for data detection in massive MIMO system. In contrast with recently proposed polynomial expansion (PE) method for matrix inversion, we analyze both the algorithm complexity and precision in detail, and propose a diagonal band Newton iteration (DBNI) method, which is an approximate method for NI. Compared with PE method, DBNI can obtain higher precision and approximately equal complexity, and we give an explanation of how to select the bandwidth of DBNI.