一个基于深度强化学习的跳跃频谱传感方案,用于转换域通信系统
Ce Li1, Yanhua Wu2, Rangang Zhu3
1College of Electronic Engineering, National University of Defense Technology, Hefei, 230000, China. lice22@nudt.edu.cn.
Scientific reports
|December 29, 2024
概括
本研究介绍了转换域通信系统 (TDCS) 的新方法,以提高频谱传感效率. 该方法通过平衡传感成本和频谱利用来提高适应性和性能.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 频谱传感对于转换域通信系统 (TDCS) 是至关重要的.
- 传统的固定子频段选择和TDCS中的周期感应导致性能下降和效率低下.
- 现有的模型往往过于简化了动态频谱环境.
研究的目的:
- 为 TDCS 开发一种适应性频谱传感策略,解决传统方法的局限性.
- 将频谱传感问题建模为一个部分可观测的马尔科夫决策过程 (POMDP),考虑不完整的频谱状态信息.
- 为了提高TDCS传输效率并减少传感上的开销.
主要方法:
- 模拟频谱传感作为部分可观测的马尔科夫决策过程 (POMDP).
- 开发一个DDRQN-BandShift战略,结合双深Q网络 (DDQN) 和深度循环Q网络 (DRQN),以解决Q值的高估.
- 为子频段选择和跳过的时间段纳入不同的终止条件.
- 分配权重,以平衡传感开销和频谱利用.
主要成果:
- 拟议的POMDP模型准确地反映了TDCS设备有限的观测能力.
- DDRQN-BandShift策略有效地减轻了Q值高估问题.
- 观察到TDCS传输效率的显著改善.
- 实现了频谱传感成本的大幅降低.
结论:
- 基于POMDP的新方法和DDRQN-BandShift策略为TDCS的频谱传感提供了更现实的和有效的解决方案.
- 拟议的方法通过优化传感头部和频谱利用之间的权衡来提高系统的适应性和性能.
- 这项研究有助于更高效,更可靠的无线通信系统.
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