Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

作     者：Zhang Zhenyu Zhang Yong Yuan Siyu Cheng Zhenjie Zhang Zhenyu;Zhang Yong;Yuan Siyu;Cheng Zhenjie

作者机构：School of Electronic EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Work Safety Intelligent Monitoring(Beijing University of Posts and Telecommunications)Beijing 100876China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2024年第21卷第6期

页      面：53-68页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081104[工学-模式识别与智能系统] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.61971057). 

主　　题：cognitive radio deep reinforcement learning network slicing power-domain non-orthogonal multiple access resource allocation 

摘      要：In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.