User selection and dynamic power allocation in the SWIPT-NOMA relay system
Autor: | Min Li, Hong Tang, Zhaoyuan Shi, Xianzhong Xie, Qian Huang |
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Rok vydání: | 2021 |
Předmět: |
TK7800-8360
Computer Networks and Communications Computer science User selection and power allocation TK5101-6720 02 engineering and technology law.invention 0203 mechanical engineering Relay law Telecommunications link 0202 electrical engineering electronic engineering information engineering Maximum power transfer theorem Reinforcement learning Wireless Artificial neural network business.industry Quality of service Simultaneous wireless information and power transfer (SWIPT) Deep neural network (DNN) 020302 automobile design & engineering 020206 networking & telecommunications Computer Science Applications Non-orthogonal multiple access (NOMA) Deep reinforcement learning (DRL) Signal Processing Dynamic demand Telecommunication Electronics business Computer network |
Zdroj: | EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-19 (2021) |
ISSN: | 1687-1499 |
DOI: | 10.1186/s13638-021-01998-0 |
Popis: | Non-orthogonal multiple access (NOMA) technology provides an effective solution to massive access with a high data rate demand in new-generation mobile networks. The paper combinations with NOMA and simultaneous wireless information and power transfer (SWIPT) relay to maximize the sum rate in the downlink system. To that end, it is critical how to select effectively users access system and power allocation for the access user. This paper proposes a user selection and dynamic power allocation (USDPA) scheme in the NOMA-SWIPT relay system based on neural network because traditional optimization methods have difficulty solving nonlinear and non-convex problems. We establish a user selection network utilizing a deep neural network (DNN) and propose a power allocation network using deep reinforcement learning. The simulation results show that the proposed scheme achieves better performance than other related schemes, especially for high quality of service requirements. |
Databáze: | OpenAIRE |
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