协作频谱感知中数据融合与决策算法比较

Comparison of Data Fusion and Decision Algorithms in Cooperative Spectrum Sensing

协作频谱感知中融合多个认知用户的本地检测结果并准确判决至关重要。研究了基于大数合并的硬判决和基于置信(最大似然)合并的软判决,对不同算法的检测性能和复杂度进行了定性和定量的分析和比较。指出未来协作频谱感知中应结合协作用户数的优化和控制信道条件进行数据融合和决策算法设计。

In cooperative spectrum sensing, combining multiple cognitive users＇ local detection results and making accurate judgment is essential. Hard decision based on the combination of large numbers and soft decision based on the confidence （maximum likelihood） combined are studied, detection performance and complexity of different algorithms are analyzed and compared respectively. In future applications, data fu- sion and decision algorithms should be combined with optimization of the number of cooperative users and the conditions of control channel for rational design.