基于BP神经网络的协作频谱感知技术

认知无线电技术可以利用主用户未使用的频谱资源来有效地提高频谱利用率。单用户感知技术虽然简单但可靠性较低,协作频谱感知技术可以显著地提高频谱感知的性能。现有的大部分协作感知都是在假设各认知用户的信噪比相同的前提下进行研究。然而在实际环境中,由于每个认知用户所处的环境不同,其信噪比不同,对融合中心判决的影响也不同。如何在提升检测性能的同时提升系统的能量效率是关键问题。提出一种基于BP(Back Propagation)神经网络的协作频谱感知技术,它利用频谱环境的历史信息,通过BP神经网络提高频谱感知性能。仿真结果表明,该算法可以在保证协作感知性能的同时减少参与协作的认知用户数,从而减少能量消耗。

Cooperative Spectrum Sensing Technology Based on BP Neural Network

The technology of cognitive radio can use the untapped spectrum resource to increase the cognitive radio technology efficiency dramatically.Although the spectrum sensing for only one technique is simple,it is not reliable.However,using the cooperative spectrum sensing can improve the capability of spectrum sensing.Recently,most of the studying about the cooperative spectrum sensing is based on one simple condition that is assuming the signal to noise ratio for each cognitive user is similar.In reality,each cognitive radio user will have different environment,which will produce different signal to noise ratio and different influence on the justification of the fusion center.In addition,another important issue is how to improve the performance of CR system while enhancing the energy efficiency.This paper proposed a method of cooperative spectrum sensing based on BP (Back Propagation) neural network which will improve spectrum sensing performance by using the historical information about the spectrum through BP neural network.The simulation identifies the algorithm can reduce the involved cognitive users and the energy consumption,and guarantee the performance of the cooperative sensing at the same time.