Reinforcement Learning Assisted Beamforming for Inter-cell Interference Mitigation in 5G Massive MIMO Networks

• URL: http://arxiv.org/abs/2103.11782v2
• Date: Fri, 2 Jul 2021 02:13:52 GMT
• Title: Reinforcement Learning Assisted Beamforming for Inter-cell Interference Mitigation in 5G Massive MIMO Networks
• Authors: Aidong Yang, Xinlang Yue, Ye Ouyang
• Abstract summary: Beamforming is an essential technology in the 5G massive multiple-input-multiple-output (MMIMO) communications. The inter-cell interference (ICI) is one of the main impairments faced by 5G communications due to frequency-reuse technologies. We propose a reinforcement learning (RL) assisted full dynamic beamforming for ICI mitigation in 5G downlink.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Beamforming is an essential technology in the 5G massive multiple-input-multiple-output (MMIMO) communications, which are subject to many impairments due to the nature of wireless transmission channel, i.e. the air. The inter-cell interference (ICI) is one of the main impairments faced by 5G communications due to frequency-reuse technologies. In this paper, we propose a reinforcement learning (RL) assisted full dynamic beamforming for ICI mitigation in 5G downlink. The proposed algorithm is a joint of beamforming and full dynamic Q-learning technology to minimize the ICI, and results in a low-complexity method without channel estimation. Performance analysis shows the quality of service improvement in terms of signal-to-interference-plus-noise-ratio (SINR) and computational complexity compared to other algorithms.

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