认知无线电加权联合频谱感知优化算法

为了提高认知无线电联合频谱感知的性能,对加权联合频谱感知算法进行了研究,并对权重和观测时间2个感知参数进行了优化.算法基于给定的检测概率,通过选择最优的权重使认知无线电获得最小的虚警概率；还提出了二分算法,通过该算法,认知无线电能够获得最优的观测时间.仿真结果表明:相比未加权的联合频谱感知算法,提出的算法能够获得更低的虚警概率和更高的频谱利用率,并且相比穷举算法,二分算法的计算量要更低.提出的算法能够使认知无线电在授权用户的干扰容限内获得最大的频谱利用率.

Optimization Algorithm of Weighed Cooperative Spectrum Sensing in Cognitive Radio

In order to improve the detection performance of cooperative spectrum sensing for cognitive radio (CR), the weighed algorithm of cooperative spectrum sensing is investigated, and the two sensing parameters which include weighed factors and observed time are optimized in the proposed algorithm. The sensing algorithm seeks to obtain the minimum probability of false alarm by choosing the optimal weighed factors under the given probability of detection. The dimidiate algorithm which seeks to search the optimal observed time is proposed in order to obtain the maximal spectrum utilization of CR within the interference limit of primary user. The simulation shows that compared to the traditional un-weighed algorithm of cooperative spectrum sensing, the proposed algorithm can achieve lower probability of false alarm and higher spectrum utilization, and compared to the exhaustive search, the proposed dimidiate algorithm can achieve lower computational complexity.