Research Article
A Low-Complexity Discrete Gbest-guided Artificial Bee Colony Algorithm for Massive MIMO Detection
@INPROCEEDINGS{10.1007/978-3-319-90802-1_7, author={Boyang Zou and Weixiao Meng and Lin Li and Shuai Han}, title={A Low-Complexity Discrete Gbest-guided Artificial Bee Colony Algorithm for Massive MIMO Detection}, proceedings={Wireless Internet. 10th International Conference, WiCON 2017, Tianjin, China, December 16-17, 2017, Proceedings}, proceedings_a={WICON}, year={2018}, month={5}, keywords={Massive multiple input multiple output (MIMO) system Discrete gbest-guided artificial bee colony (DGABC) Computational complexity Detection algorithm Chaotic maps}, doi={10.1007/978-3-319-90802-1_7} }- Boyang Zou
Weixiao Meng
Lin Li
Shuai Han
Year: 2018
A Low-Complexity Discrete Gbest-guided Artificial Bee Colony Algorithm for Massive MIMO Detection
WICON
Springer
DOI: 10.1007/978-3-319-90802-1_7
Abstract
Massive multi-input multi-output (MIMO) technology is one of the most promising concepts in 5G wireless system. Grounded on the fact that the channel matrix in massive MIMO system is large dimensional, classical MIMO detection algorithms are not appropriate for large scaled antennas. In this paper, a low-complexity discrete gbest-guided artificial bee colony (DGABC) detection algorithm is proposed for massive MIMO uplink, chaotic maps for parameter adaptation is also proposed in order to improve the convergence characteristic of the DGABC algorithm and to prevent the algorithm from getting stuck in local solutions. Experiments show that the proposed DGABC detection algorithm outperforms both the original ABC algorithm and MMSE detection with a relatively low complexity.
