集中式双非参量累积和的合作频谱感知技术

针对认知无线电网络频谱感知的检测时延降低问题,提出了一种采用双非参量累积和的合作频谱感知方法。在单主用户认知网络中,本地认知用户执行非参量累积和算法,处理能量观测数据,以缩短检测时延,减少对主用户先验信息的需求,同时为了降低带宽开销,只向融合中心传输1比特的预判决结果。融合中心在噪声干扰下接收融合预判决结果,执行非参量累积和算法,累加判决统计量,对主用户信号是否存在进行最终判决。仿真结果表明,在10%的虚警概率下,相比于传统的非参量合作频谱感知算法,双非参量累积和算法具有较低的检测延迟。

Cooperative Spectrum Sensing for Centralized Dual Nonparametric Cumulative

For the problem of reducing the detection delay of spectrum sensing in cognitive radio (CR) networks, the work proposed an improved approach of cooperative spectrum sensing (CSS) based on dual nonparametric cumulative sum (DualNCUSUM). In CR network with one primary user, local CR users adopted the NCUSUM to handle the energy observation data, which decreased the local detection delay and the need for prior information of primary user. In order to reduce the bandwidth consumption, 1-bit results of pre-decision are made and transmitted to the fusion center which fused 1-bit results disturbed by ambient noise in reporting channel. The fusion center also used the NCUSUM to accumulate the decision statistics to make the final decision whether the signal of primary user was present. The simulation shows that the proposed DualNCUSUM algorithm has shorter detection delay than the conventional nonparametric CSS approaches while maintaining the false alarm probability at 10%.