在频谱感知过程中，采用协作感知的方式对空间内多个节点的感知结果进行融合，可以消除路径阴影和深度衰落情况的影响，有效提高结果的准确性和可靠性。基于加权融合的协作判决准则，为了保证融合结果的检测概率和虚警概率达到标准，需要使每个节点的感知结果均达到相应的标准。因此提出通过对每个感知节点设定合适的感知门限进行优化。首先对各感知节点的进行分析，可以得到每个节点在检测概率和虚警概率一定的条件下，感知门限与节点权值的关系，其次通过遗传算法对权值的优化实现权值优化——感知门限优化的自适应优化过程。最后通过仿真验证该方法可以高效准确地实现感知门限的自适应优化，从而保证了协作频谱感知的实际性能。
In the spectrum sensing process, cooperative sensing method is to fuse the sensing results of multiple nodes in space to eliminate the influence of path shadow and deep fading and effectively improve accuracy and reliability of results. In order to ensure that the detection probability and the false alarm probability of the fusion result reach the standard, the cooperative decision criterion based on weighted fusion needs to make the perceptual result of each node reach the corresponding standard. Therefore, this paper proposes a method to set an appropriate perceptual threshold for each perceptual node to achieve optimization. Firstly, the analysis of each sensory node can obtain the relationship between the threshold and node weight under the condition of fixed detection probability and false alarm probability. Secondly, using the genetic algorithm, the weight is optimized to realize the weight optimization, the adaptive optimization process of perceptual threshold optimization. Finally, simulation results show that the proposed method can efficiently and accurately realize adaptive optimization of sensing threshold, thus ensuring the actual performance of cooperative spectrum sensing.
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