摘要
协作的频谱感知使认知无线电(CR)网络对主用户进行可靠的检测,并避免了对主用户通信的干扰。数据融合是协作的频谱感知的关键技术。对基于"与"准则、"或"准则、最大后验概率准则和贝叶斯准则的数据融合算法进行了研究,采用这4种融合方法在认知无线电网络中进行协作频谱感知,并比较了它们的频谱检测性能。仿真结果显示最大后验概率准则和贝叶斯准则在认知无线电的环境中有优越的感知性能。
Cooperative spectrum sensing enables a Cognitive Radio （CR） networks to reliably detect primary users and avoid causing interference to primary user＇s communications. The data fusion technique is a key component of cooperative spectrum sensing. Four data fusion methods have been investigated in this paper,including ＂AND＂ rule, ＂OR＂ rule, the largest posterior probability？ rule and Bayesian rule. We use them to sense spectrum cooperatively in CR networks and their spectrum detection performances were compared. Simulation results show that the largest posterior probability？ rule and Bayesian rule can approach ascendant sensing performances in the CR networks.
出处
《南京邮电大学学报（自然科学版）》
2009年第2期73-78,共6页
Journal of Nanjing University of Posts and Telecommunications：Natural Science Edition
基金
国家重点基础研究发展计划(973计划)(2007CB310607)
国家自然科学基金(60772062)
东南大学移动通信国家重点实验室开放研究基金(N200813)资助项目
