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提出了基于最优用户选择的协作频谱感知方案,通过引入Gerschgorin圆盘理论建立用户选择机制,筛选出信道条件最优的若干个认知用户,由其对应的感知数据空间生成全局判决统计量以实现最优协作感知,并在此基础上提出迭代门限算法,进一步优化感知性能.理论分析和仿真结果表明,该方案无需知晓授权用户信号、信道、噪声功率等先验信息,对噪声功率不确定性具有较强的鲁棒性,且当接收机采样次数和参与协作的用户数都受限时,感知性能仍然很稳定,可作为协作频谱感知的现实可实现方案.
A cooperative spectrum sensing scheme based on optimal user selection is proposed. By introducing Gerschgorin disc theory, a user selection mechanism is established to filter out a number of cognitive users with the best channel conditions and generate global decision statistics from the corresponding perceptual data space And realize iterative threshold algorithm to further optimize the sensing performance.The theoretical analysis and simulation results show that this scheme does not need to know prior information such as authorized user signal, channel and noise power, It has strong robustness. When the number of receiver samples and the number of users participating in the collaboration are limited, the perceptual performance is still stable and can be used as a realistic solution for cooperative spectrum sensing.