4.6 Article

D2D Cooperative Communication Network Resource Allocation Algorithm Based on Improved Monte Carlo Tree Search

Journal

IEEE ACCESS
Volume 11, Issue -, Pages 72689-72703

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2023.3280604

Keywords

D2D cooperative communication network; Monte Carlo tree search; double chain parallel neural network; resource allocation; interference management

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In recent years, D2D cooperative communication networks have become a major component of future communication networks, greatly improving spectrum efficiency and user communication quality. However, existing resource allocation schemes for D2D networks face challenges such as weak dynamic allocation capability and low communication quality. This paper proposes a resource allocation algorithm based on improved Monte Carlo tree search. Simulation results show that the proposed algorithm outperforms existing methods in terms of system throughput and outage probability.
In recent years, with the rapid development of mobile communication, D2D (Device-to-Device, D2D) cooperative communication network has become the main component of future communication network, which greatly improves the spectrum efficiency of the network and the quality of user communication. However, the existing D2D network resource allocation schemes have some problems, such as weak dynamic resource allocation capability and low user communication quality. In view of this challenge, this paper proposes a resource allocation algorithm for D2D cooperative communication networks based on improved Monte Carlo tree search. First, a double-chain deep deciduous Monte Carlo tree search (Dcdd-MCTS) resource allocation model is established, Then, the loss function composed of deciduous MCTS and parallel convolution network is used to update the parameters of the deep neural network model of Dcdd-MCTS. Then, the theory of optimal classification is used to solve the user's transmit power. Finally, the optimal scheme of dynamic output resource allocation is output. The simulation results show that Dcdd-MCTS has good convergence. In the research on the distance between devices, compared with single-chain deep MCTS and joint optimization algorithm, the proposed algorithm in this paper increases the system throughput by 5%, 2%, respectively, and reduces the outage probability by 33%,18%.

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