Joint Block Support Recovery for Sub-Nyquist Sampling Cooperative Spectrum Sensing

This letter aims to improve the efficiency and reliability of joint block sparse support recovery by exploiting block features in the MMV problem. For the block MMV problem, we first propose a Block SOMP algorithm extended from SOMP, which can reduce the number of iterations of the original method. Then, we perform an in-depth theoretical analysis of the proposed algorithm using Exact Recovery Condition (ERC). Both theoretical analysis and simulation experiments confirm that the proposed algorithm can provide reliable recovery for higher sparsity. However, the premise is that the design of the cooperative compressed sensing matrix requires special attention.