Linear Massive MIMO Detection Algorithm

Abstract

Massive MIMO signal detection is the key technology of next generation wireless communication (such as 5G). In massive MIMO signal detection, there are many algorithms that can implement the signal detection. Generally, these algorithms can be divided into linear detection algorithm and nonlinear detection algorithm according to different calculation methods. Although the linear detection algorithm is less accurate than the nonlinear detection algorithm, it is still an effective signal detection method of massive MIMO system in some cases due to its low complexity. This chapter introduces several typical linear iterative algorithms for massive MIMO signal detection. By these algorithms, the iterations between vectors or matrices can be effectively used to avoid direct inversion of large-scale matrices and reduce complexity of the linear detection algorithm. In the following sections, we will introduce Neumann series approximation (NSA) algorithm, the Chebyshev iteration algorithm, the Jacobi iteration algorithm and the Conjugate gradient (CG) algorithm respectively. And the optimization methods of the Chebyshev iteration algorithm, the Jacobi iteration algorithm and the Conjugate gradient algorithm are also introduced for better linear detection algorithms. In addition, this chapter also compares the complexity and accuracy of these algorithms with other massive MIMO signal detection algorithms.