基于变步长序贯压缩的频谱快速感知算法
Spectrum Sensing Algorithm Based on Variable Step Size Sequential Compressed Sampling

对信号稀疏度未知甚至时变的频谱感知应用 场景，将自适应思想与序贯压缩频谱感知技术相结合，提出了一种可变步长序贯压缩频 谱快速感知算法。新算法建立了下一次判决所需观测值数目步长因子与当前对数似然比距门 限距离之间的函数关系，克服了现有的序贯压缩检测算法以固定步长增加观测值的不足。分 别以分段函数和抛物线函数为步长因子调整规则进行理论分析和仿真实验。仿真结果表明： 与现有的序贯压缩检测算法相比，变步长算法具有检测速度快、观测值数目少和计算复杂度 小等优点。
The signal sparsity is often unknown, or even changed with time in spec trum sensing. Therefore, a variable step size sequential compressed de tection algorithm is proposed by combining the adaptive theory with the sequenti al compre ssed spectrum sensing technology. The functional relationship is established bet ween step size factor of the next needed measurement numbers and current distan c e from the likelihood ratio and the detection thresholds. In addition, the sh ortcoming of the fixed step size of the measurement increment in the existing se quential compressed sensing is overcomed in the proposed algorithm. Theoretical analysis and computer simulations are conducted by introducing the rules of step size adjustment with piecewise function and parabolic function, respecti vely. Simulations prove that, the proposed algorithm has the fast er detection speed, less measurements number and lower computational complexi ties, compared with the existing sequential compressed detection scheme.