A Low Complexity Signal Detection Scheme Based on Improved Newton Iteration for Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) systems need to handle a large number of matrix inversion operations during the signal detection process. Several methods have been proposed to avoid exact matrix inversion in massive MIMO systems, which can be roughly divided into approximation methods and iterative methods. In this letter, we first introduce the relationship between the two types of signal detection methods. Then, an improved Newton iteration method is proposed on the basis of the relationship. And by converting the matrix-matrix product into the matrix-vector product, the computational complexity is substantially reduced. Finally, numerical simulations further verify that the proposed Newton method outperforms Neumann series expansion and the existing Newton method, and can approach the performance of minimum mean square error (MMSE) method within a few iterations, regardless of whether the base station can obtain perfect channel state information or not.