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.
This work is supported by National Natural Science Foundation of China (61471143) and the Provincial Natural Science Foundation of Heilongjiang, China (No. ZD2017013).
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Zou, B., Meng, W., Li, L., Han, S. (2018). A Low-Complexity Discrete Gbest-guided Artificial Bee Colony Algorithm for Massive MIMO Detection. In: Li, C., Mao, S. (eds) Wireless Internet. WiCON 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-319-90802-1_7
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DOI: https://doi.org/10.1007/978-3-319-90802-1_7
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