作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2012, Vol. 38 ›› Issue (15): 90-92,96. doi: 10.3969/j.issn.1000-3428.2012.15.026

• 网络与通信 • 上一篇    下一篇

基于权值自适应优化的协作频谱认知算法

杨 健1,梁毅龙1,王永华1,王荣杰2,余松森3   

  1. (1. 广东工业大学自动化学院,广州 510006;2. 中山大学信息科学与技术学院,广州 510275; 3. 华南师范大学南海校区信息工程与技术系,广东 佛山 528225)
  • 收稿日期:2011-09-13 出版日期:2012-08-05 发布日期:2012-08-05
  • 作者简介:杨 健(1982-),男,讲师、博士,主研方向:认知无线网,RFID MAC协议;梁毅龙,工程师;王永华,讲师、博士;王荣杰,博士研究生;余松森,副教授、博士
  • 基金资助:
    国家自然科学基金资助项目(61102034, 61172156);广州市应用基础基金资助重点项目(11C42090780);广东工业大学博士启动基金资助项目(13002)

Cooperative Spectrum-sensing Algorithm Based on Weight Adaptive Optimization

YANG Jian   1, LIANG Yi-long    1, WANG Yong-hua    1, WANG Rong-jie    2, YU Song-sen   3   

  1. (1. Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China; 2. School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510275, China; 3. Department of Information Engineering and Technology, Nanhai Campus, South China Normal University, Foshan 528225, China)
  • Received:2011-09-13 Online:2012-08-05 Published:2012-08-05

摘要: 提出一种基于权值自适应优化的协作频谱认知算法。根据各协作认知节点的信噪比分配合适的权值向量,反映对检测统计量的贡献大小。基于最小均方误差原则,权值向量可根据实际的各节点信噪比向量进行自适应优化,从而提高认知网络中存在低信噪比节点时的检测性能。仿真结果表明,与传统协作算法相比,该算法无论在节点高信噪比或低信噪比条件下均有更优的检测性能,且收敛速度较快。

关键词: 认知无线电, 协作频谱认知, 最小均方误差, 权值自适应优化, 信噪比阈值, 收敛步长

Abstract: Based on weight adaptive optimization, a novel cooperative spectrum-sensing algorithm is proposed. According to the Signal to Noise Ratio(SNR) of each cooperative user, appropriate weight vector is chosen, reflecting each cooperative user’s contribution to the system detecting statistic. The weight vector has the ability of adaptive optimization on the principle of minimum mean square error, considering the actual SNR of each cooperative user, so that the detecting performance is improved on the condition of the low SNR users existence in cognitive network. Simulation results imply that the proposed algorithm has better detecting performance than traditional algorithm and agreeable convergence speed, on both condition of low SNR and high SNR of cooperative users.

Key words: Cognitive Radio(CR), cooperative spectrum-sensing, minimum mean square error, weight adaptive optimization, Signal to Noise Ratio(SNR) threshold value, convergence step

中图分类号: