Attention Enhanced Multi-Agent Reinforcement Learning for Cooperative Spectrum Sensing in Cognitive Radio Networks

认知无线电 强化学习 钢筋 计算机科学 光谱(功能分析) 认知 人工智能 计算机网络 无线 工程类 电信 物理 心理学 神经科学 结构工程 量子力学
作者
Ang Gao,Qinyu Wang,Yongze Wang,Chengyuan Du,Yansu Hu,Wei Liang,Soon Xin Ng
出处
期刊:IEEE Transactions on Vehicular Technology [Institute of Electrical and Electronics Engineers]
卷期号:73 (7): 10464-10477 被引量:1
标识
DOI:10.1109/tvt.2024.3384393
摘要

Cooperative spectrum sensing (CSS) technology has been widely studied to enhance the spectrum sharing efficiency spatially and temporally in cognitive radio networks (CRNs), where the secondary users (SUs) can opportunistically reuse the channels already licensed to the primary users (PUs) for transmission by sensing spectrum holes. SUs are endowed with the global awareness of channels state by cooperating with each other without sweeping across the whole frequency bands. Since the channels occupation of PUs changes dynamically, the accurate sensing and swift information sharing are crucial for CRNs. The paper proposes a multi-agent deep reinforcement learning (DRL) based CSS method to help SUs efficiently finding a vacant channel by the cooperation with their partners. 1 Two partner selection algorithms are proposed named as Reliable Partner CSS and Adaptive Partner CSS, respectively. For the former, the partner selection is facilitated based on the historical sensing accuracy of SUs. While the latter takes the comprehensive consideration of both the reliability and geographical distribution of SUs to further improve the sensing accuracy. 2 Multi-agent deep deterministic policy gradient (MADDPG) is adopted to resist the dynamically varying channels condition as well as the high-dimension solution space. With the feature of 'centralized training and decentralized execution', each SU learns to interact with the environment and select a vacant channel for transmission by its partial observation, which greatly reduces the communication overhead caused by the cooperative spectrum sensing. 3 Numerical simulation demonstrates the convergence and availability of the proposed algorithms. No matter Reliable Partner CSS or Adaptive Partner CSS, the sensing accuracy can be greatly enhanced comparing with other non-cooperative or centralized learning approaches. Besides, the attention mechanism is introduced to MADDPG for Adaptive Partner CSS to reveal the behavior of SUs by the visualization of attention weight, which helps to partially interpret the 'black box' issue of DRL.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
1秒前
1秒前
完美世界应助zlttt采纳,获得10
3秒前
momo发布了新的文献求助10
5秒前
漫山完成签到,获得积分10
5秒前
量子星尘发布了新的文献求助10
5秒前
6秒前
7秒前
8秒前
阿斗发布了新的文献求助10
9秒前
9秒前
踏实的火龙果完成签到 ,获得积分20
9秒前
健忘白完成签到,获得积分10
11秒前
ding应助liang采纳,获得30
12秒前
厉害tt完成签到,获得积分10
12秒前
12秒前
ding应助momo采纳,获得10
12秒前
在水一方应助吧啦吧啦采纳,获得10
12秒前
踏实的火龙果关注了科研通微信公众号
13秒前
维尼发布了新的文献求助20
14秒前
文档发布了新的文献求助10
14秒前
Rondab应助千余采纳,获得10
18秒前
18秒前
taowang发布了新的文献求助30
18秒前
一支笔画天下完成签到 ,获得积分10
18秒前
19秒前
CL完成签到 ,获得积分10
20秒前
hnlgdx完成签到,获得积分20
20秒前
Dotson发布了新的文献求助20
20秒前
出门见喜发布了新的文献求助10
22秒前
丁老三完成签到 ,获得积分10
23秒前
gky完成签到,获得积分10
24秒前
26秒前
嘻哈完成签到,获得积分10
27秒前
火力全开发布了新的文献求助10
28秒前
taowang完成签到,获得积分10
32秒前
地表飞猪应助科研通管家采纳,获得10
32秒前
研友_VZG7GZ应助科研通管家采纳,获得10
32秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989297
求助须知:如何正确求助?哪些是违规求助? 3531418
关于积分的说明 11253893
捐赠科研通 3270097
什么是DOI,文献DOI怎么找? 1804884
邀请新用户注册赠送积分活动 882087
科研通“疑难数据库(出版商)”最低求助积分说明 809158