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低频谱利用率条件下的信道状态向量具有稀疏性,为降低认知无线电网络中各个认知用户的频谱感知冗余,基于压缩感知技术提出了一种低复杂度的协作频谱感知方法.仿真结果表明,通过稀疏观测矩阵提高了单个认知用户感知过程的速度和效率;在融合中心对观测数据进行重构过程中使用因子图迭代算法,大幅降低了计算难度;同时可以根据认知网络中的频率使用情况,自适应调整认知用户的感知点数,确保整个网络的高效感知.
In order to reduce spectrum-aware redundancy of cognitive users in cognitive radio network, a low-complexity cooperative spectrum sensing method is proposed based on compressed sensing technology. The simulation results It is shown that the speed and efficiency of a single cognitive user perception process are improved by using a sparse observation matrix. Using the iterative algorithm of factor graph in the process of reconstructing the observed data in the fusion center greatly reduces the computational complexity. At the same time, Frequency usage, adaptive adjustment of cognitive users perceived points to ensure efficient perception of the entire network.