Novel hardware architecture of sparse recovery based on FPGAs

Compressed sensing is currently one of the most popular fields in signal processing, which enables us to acquire “sparse” signals by sampling under Nyquist´s frequency. In this paper, a novel hardware architecture based on Optimized CoSaMP algorithm is presented for sparse recovery of compressed sensing. Due to the crucial calculation of least squares in the algorithm, the proposed architecture develops a least squares module (LS module) with linear array structure, which achieves good efficiency as well as flexibility and scalability. The running results obtained from the implementation on a field-programmable gate array (FPGA) show that our design possesses excellent performance and high accuracy.