A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Hui Feng,Zhengquan Li,Song Xing,Xiaoqing Zhao

doi:10.3390/electronics8090980

Abstract

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

Highlights

With the development of the mobile Internet and the Internet of Things, much high data rate communication is required in the new generation of cellular networks like 5G [1]
Several typical detection algorithms were selected for comparison, which were introduced in Section 1 and listed as linear minimum mean squared error (LMMSE), alternating minimization (AltMin), and alternating direction method of multipliers (ADMM)
We first considered the number of iterations for the antenna configurations of Number of transmitting antennas (Nt) × Number of receiving antennas (Nr) = 16 × 128, 32 × 128 and 64 × 128