Yifei Wei1, *, Yinxiang Qu1, Min Zhao1, Lianping Zhang2, F. Richard Yu3
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1515-1532, 2020, DOI:10.32604/cmc.2020.09130
Abstract Device-to-Device (D2D) communication is a promising technology that can
reduce the burden on cellular networks while increasing network capacity. In this paper, we
focus on the channel resource allocation and power control to improve the system resource
utilization and network throughput. Firstly, we treat each D2D pair as an independent agent.
Each agent makes decisions based on the local channel states information observed by itself.
The multi-agent Reinforcement Learning (RL) algorithm is proposed for our multi-user
system. We assume that the D2D pair do not possess any information on the availability
and quality of the resource block to be selected,… More >
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