An Improved Newton-Schulz Iterative Algorithm for Massive MIMO Detection
- Resource Type
- Conference
- Authors
- Yang, Kuncheng; Tan, Xiaosi; Qian, Qikang; Zhang, Zaichen; You, Xiaohu; Zhang, Chuan
- Source
- 2023 International Conference on Wireless Communications and Signal Processing (WCSP) Wireless Communications and Signal Processing (WCSP), 2023 International Conference on. :984-989 Nov, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Wireless communication
Simulation
Signal processing algorithms
Detectors
Massive MIMO
Iterative algorithms
Signal to noise ratio
MMSE detector
Newton-Schulz Algorithm
matrix inversion
- Language
The exact matrix inversion required by the conventional minimum mean square error (MMSE) detector for massive multiple-input multiple-output (MIMO) brings unaffordable computational burden that hinders efficient implementation. In this paper, a linear iterative detector based on Newton-Schulz algorithm is proposed to avoid the inversion of MMSE. An initialization scheme and a successive-update schedule is proposed to enhance the convergence rate and accuracy of the Newton-Schulz detector. Simulation results are illustrated to show that the proposed detector can approach the bit-error-rate (BER) performance of MMSE with reduced complexity. Moreover, it can outperform state-of-the-art (SOA) linear detection methods under various MIMO scenarios.