Deep Q-Learning Framework for Improving Spectral Efficiency in D2D Communication

Lucas Baião Pires, Paulo Henrique Portela de Carvalho

DOI: 10.14209/SBRT.2020.1570649648

Evento: XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2020)

Keywords: Device-to-device (D2D) 5-th generation (5G) deep reinforcement learning artificial intelligence

Abstract

Device-to-device (D2D) communication is expected to play a big role in 5G, in order to enable new applications in the mobile system such as vehicular-communications (V2X) and internet of things (IoT). This should increase the bandwidth demand, which makes higher spectral efficiency ever more desirable. This paper proposes a Deep Q-Learning power allocation framework for maximizing spectral efficiency in D2D communication, in underlay mode, while satisfying the mobile user's quality of service (QoS) requirements.

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