认知无线电加权软合并联合频谱感知算法

摘要

To improve the spectrum sensing performance, this paper proposes cooperative spectrum sensing that fuses the sensing information from every cognitive radio with soft fusion based on weighting. To reduce interference to the primary user and improve throughput of cognitive radio, two kinds of weight selection methods that minimize interference and maximize throughput are proposed. As large weighting is allocated to the cognitive radios with high SNR or low channel gain to the coordinator, proportion of the sensing information sent by the cognitive radio with high SNR to the fusion information at the coordinator is increased. Lost information due to channel fading is compensated. Simulation results show that performance of the algorithm is better than those based on SNR weighting and those without weighting. The proposed algorithm can also reduce influences of the fading channel on detection performance. The results show that, by selecting appropriate weights, interference can be reduced and throughput increased.%为了提高认知无线电的频谱感知性能,提出了对认知无线电用户的检测信息进行加权软合并的联合频谱感知算法.该算法通过降低对授权用户的干扰和提高认知无线电吞吐量,分别使用最小化干扰加权和最大化吞吐量加权.算法为信噪比高的用户或者到合作中心信道增益低的用户分配较大的权重,能够提高高信噪比用户的检测信息在合作检测中所占的比例,同时补偿信道衰落对检测信息带来的损失.仿真表明:该算法的性能比基于信噪比加权或非加权的算法更好,能够降低干扰并提高吞吐量,同时能够降低信道衰落对联合频谱感知性能带来的影响.