DQN-based Joint Adaptive Beamwidth Control and Beam Tracking for mmWave Communications

  • Park, Hyunwoo
  • Jeon, Jong Hyun
  • Chung, Hyeonjin
  • Kim, Sunwoo
Citations

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4

초록

This paper presents a joint adaptive beamwidth control and beam tracking algorithm for mobile millimeter-wave (mmWave) communications based on deep Q-network (DQN). When the mobile station is highly dynamic, it may deviate from the beamwidth, thereby causing less robust beam tracking. Thus, the proposed algorithm aims to satisfy both robustness and high beam gain by adjusting the beamwidth proportional to the mobility. In the proposed algorithm, the possible actions that DQN can select encompass both beamwidth control and beam tracking. Among these actions, DQN selects the action that maximizes the received signal strength. Throughout simulations, we compare the proposed algorithm with the recent beam tracking algorithm without adaptive beamwidth control. The results confirm the effectiveness of the proposed algorithm for various mobile dynamics, especially in dynamic mobile environments.

키워드

beam trackingbeamwidth controldeep Q-networkdeep reinforcement learningmmWave communicationsOPTIMIZATION
제목
DQN-based Joint Adaptive Beamwidth Control and Beam Tracking for mmWave Communications
저자
Park, HyunwooJeon, Jong HyunChung, HyeonjinKim, Sunwoo
DOI
10.1109/SSP53291.2023.10208043
발행일
2023-07
유형
Proceedings Paper
저널명
2023 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP, SSP
2023-July
페이지
473 ~ 477