1 bit Compressive Spectrum Sensing Algoritbm Based on Distributed Model - Zhijin Zhao; Weikang Hu; Junwei Hu (Dianxin kexue)
Since the actual sparsity of spectrum is unknown and time-varying, information transmit frequently between nodes in the distributed spectrum sensing network consumes communication bandwidth. To relieve the network communication bandwidth pressure, a spectrum algorithm based on 1 bit compressed sensing and distributed model was proposed. The sensing data of the nodes was compressive sampled and quantified in 1 bit, and then the data was fused in fusion node, through the mode of JSM-2. Finally the spectrum was reconstructed by the BIHT algorithm to implement spectrum sensing. Simulation results show that the proposed method has better spectrum detection performance with a few samples in low SNR, so it is a practical method of spectrum sensing.