Research Article
Complexity Analysis of Massive MIMO Signal Detection Algorithms Based on Factor Graph
@INPROCEEDINGS{10.1007/978-3-319-72823-0_24, author={Zhichao Yao and Chao Dong and Kai Niu and Zhiqiang He}, title={Complexity Analysis of Massive MIMO Signal Detection Algorithms Based on Factor Graph}, proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings}, proceedings_a={5GWN}, year={2018}, month={1}, keywords={Massive MIMO Signal detection Factor graph Message passing Channel hardening Computation complexity}, doi={10.1007/978-3-319-72823-0_24} }- Zhichao Yao
Chao Dong
Kai Niu
Zhiqiang He
Year: 2018
Complexity Analysis of Massive MIMO Signal Detection Algorithms Based on Factor Graph
5GWN
Springer
DOI: 10.1007/978-3-319-72823-0_24
Abstract
Massive MIMO technology is one of the most promising concepts in 5G wireless system. In the uplink of a massive MIMO system, complexity and performance of signal detection are two key issues been concerned simultaneously. Many message passing algorithms based on factor graph have claimed to achieve nearly optimal performance at low complexity. A unified factor graph model is introduced to describe two typical message passing algorithm,approximate message passing (AMP) and message passing detection (MPD). By analyzing different message calculation methods in the two algorithms, their computational complexity and performance are given in detail. Simulation results have shown that MPD exceeds AMP in both complexity and performance.
