电子器件2024，Vol.47Issue(2)：458-463,6.DOI:10.3969/j.issn.1005-9490.2024.02.025
基于增强学习的D2D用户和蜂窝用户传输功率的联合优化
Deep Reinforcement Learning-Based Joint Optimization for Transmitted Power of D2D User and Cellular User
摘要
Abstract
Targeting at the interference between D2D user and cellular user in D2D communication underlay cellular network system,deep enhancement learning-based transmission power optimization(DTPO)algorithm is proposed.The interference is mitigated by opti-mizing the transmit power of the devices.The power allocation problem is generally modeled as a NP-hard combinatorial optimization problem with linear constraint.Then deep reinforcement learning(DRL)algorithm is used to optimize the transmit power for both D2D users and cellular users,and the sum-rate is maximized.Simulation results show that DTPO algorithm affords similar performance with exhaustive search algorithm.关键词
支持D2D通信的蜂窝通信系统/干扰/传输功率/深度增强学习/和速率Key words
D2D communication underlay cellular network system/interference/transmitted power/deep reinforcement learning/sum-rate分类
信息技术与安全科学引用本文复制引用
徐义晗..基于增强学习的D2D用户和蜂窝用户传输功率的联合优化[J].电子器件,2024,47(2):458-463,6.基金项目
淮安市创新服务能力建设计划项目-淮安市软件测试技术重点实验室(HAP201904) （HAP201904）
