| 噪声功率不确定模型下基于CFAR准则的能量检测门限优化算法 |
| |
| 引用本文： | 孙有铭,王金龙,张剑,胡小峰,刘洛琨.噪声功率不确定模型下基于CFAR准则的能量检测门限优化算法[J].四川大学学报(工程科学版),2014,46(6):122-127. |
| |
| 作者姓名： | 孙有铭 王金龙 张剑 胡小峰 刘洛琨 |
| |
| 作者单位： | 解放军理工大学,解放军理工大学,解放军信息工程大学,重庆邮电大学个人通信研究所,解放军信息工程大学 |
| |
| 基金项目： | 1：国家自然科学基金“异构频谱环境下基于联盟的分布式频谱接入”(61172062), 2： 国家自然科学基金”无线频谱环境认知理论与技术”(60932002), 3:国家973项目“认知无线网络基础理论与关键技术研究”(2009CB320400), 4:江苏省自然科学基金“基于不完全信息的博弈学习技术研究”(SBK201122196) |
| |
| 摘 要： | 针对频谱感知中能量检测器在噪声功率不确定模型下存在门限失配问题，该文提出了一种基于CFAR准则的能量检测门限优化算法(TO-ED)，首先证明存在唯一最优的修正因子可以优化稳健统计方案(RSA)的判决门限；然后基于RSA的平均虚警概率是关于修正因子的单调函数，利用牛顿二分法实现该参数的快速迭代求解并修正RSA的判决门限。仿真表明：TO-ED算法满足CFAR意义下最优，其理论性能和仿真结果一致；实现鲁棒检测所需信噪比较RSA更低。
|
| 关 键 词： | 能量检测 稳健统计方案(RSA) 门限优化 恒虚警 (CFAR) 噪声功率不确定 |
| 收稿时间： | 4/9/2014 12:00:00 AM |
| 修稿时间： | 2014/9/12 0:00:00 |
A CFAR Based Threshold Optimization Algorithm for Energy Detection under Noise Power Uncertainty |
| |
| Sun Youming,Wang Jinlong,Zhang Jian,Hu Xiaofeng and Liu Luokun.A CFAR Based Threshold Optimization Algorithm for Energy Detection under Noise Power Uncertainty[J].Journal of Sichuan University (Engineering Science Edition),2014,46(6):122-127. |
| |
| Authors: | Sun Youming Wang Jinlong Zhang Jian Hu Xiaofeng and Liu Luokun |
| |
| Abstract: | Threshold mismatch of Energy Detection (ED) under Noise Power Uncertainty (NPU) model was investigated. A threshold optimization algorithm of ED (TO-ED) was proposed based on Constant False Alarm Ratio (CFAR) criterion. Firstly, for optimizing the threshold of Robust Statistics Approach (RSA) under the condition of CFAR, the unique existence of optimal modified factor was proved. Secondly, since the average false alarm probability of RSA is a monotonic function of modified factor, Newton Dichotomy was applied to quick search of this optimal factor. Simulations showed that the performance of TO-ED was consistent with theoretical analysis and its robust detection was realized with a lower Signal-to-Noise Ratio(SNR) comparing with RSA. |
| |
| Keywords: | |
|
| 点击此处可从《四川大学学报(工程科学版)》浏览原始摘要信息 |
|
点击此处可从《四川大学学报(工程科学版)》下载全文 |
