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在基于数据融合的协作频谱感知中,检测门限与中继用户是影响总错误率的主要因素。为避免采用复杂度高的全搜索方法,分别提出检测门限快速优化算法以及中继用户快速优化算法。前者依据总错误率的单调性,采用二分法逐步逼近最佳检测门限;后者根据贪婪思想,渐次选择一个最佳中继用户直至总错误率不再降低。仿真结果表明在保证高频谱感知性能的前提下,两者搜索次数均远低于全搜索方法。
In cooperative spectrum sensing based on data fusion, the detection threshold and relay users are the main factors affecting the total error rate. In order to avoid using the full search method with high complexity, fast threshold optimization algorithm and fast user optimization algorithm are proposed. According to the monotonicity of the total error rate, the former approaches the best detection threshold gradually by dichotomy. The latter gradually selects an optimal relay user according to the greedy idea until the total error rate no longer decreases. Simulation results show that under the premise of ensuring high spectrum sensing performance, the search times of both are far lower than the full search method.