认知无线电空闲频谱的联合检测算法

Collaborative Detection Algorithm of Idle Spectrum in Cognitive Radio

为了提高认知无线电中感知用户对主用户(弱信号)的检测性能,提出了一种多个感知用户合作的分布式优化联合检测算法.该算法在知道主用户信号和噪声的概率分布的条件下,通过最优化理论中的逐步二次规划法,联合求解检测系统的最优融合准则和各感知用户的最优判决门限,使系统联合检测概率取极大值.该算法不受接收机检测方式的限制,数值求解收敛速度快.仿真结果表明,感知用户为5个、融合中心虚警概率为0.1、相关符号累积为255次、不同融合准则下各感知用户信噪比相同时,与最好的固定融合准则检测算法相比,该算法使联合检测概率在高斯白噪声信道和平坦瑞利衰落信道中分别提高了13%和5%.

In order to improve the detection performance of sensing users for primary users with weak signals in the cognitive radio environment, a distributed optimal collaborative detection algorithm with multiple sensing users is proposed. In this algorithm, with the known probability dist.ributions of primary user＇ s signals and noises, both the optimal fusion rule of the detection system and the optimal decision threshold of each sensing user are obtained via the sequential quadratic programming in the optimization theory, which makes the collaborative detection probability maximum. Being independent of the detection form of the receiver, the proposed algorithm possesses high convergence rate of numerical solution. Simulated results indicate that, with five sensing users, 255 cumulative correlated symbols, 10% false alarm of the fusion center and the same signal-to-noise ratio of all sensing users, the proposed algorithm is superior to the existing best detection algorithm based on the fixed fusion rule in both the additive white Gaussian noise and the fiat Rayleigh fading channels ,with an improved collaborative detection probability by 13% and 5% , respectively.