Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization

@article{Shafin2019SelfTuningSD,
  title={Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization},
  author={Rubayet Shafin and Hao Chen and Young Han Nam and Sooyoung Hur and Jeongho Park and Jianzhong Zhang and Jeffrey Reed and Lingjia Liu},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.06021}
}
Beamforming in multiple input multiple output (MIMO) systems is one of the key technologies for modern wireless communication. Creating appropriate sector-specific broadcast beams are essential for enhancing the coverage of cellular network and for improving the broadcast operation for control signals. However, in order to maximize the coverage, patterns for broadcast beams need to be adapted based on the users' distribution and movement over time. In this work, we present self-tuning… CONTINUE READING
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