TS-QAIC Optimization Method Based on Jointly-solved OMP Algorithm

Quadrature analog-to-information converter (QAIC) has emerged as a novel framework in spectrum detection and reconstruction in recent years. Compared with traditional architectures, time-segmented QAIC (TS-QAIC) can significantly reduce the number of physical branches. In this paper, a novel optimization method is proposed to improve the performance of the TS-QAIC framework, in which the TS-QAIC signals can be treated as a multi-solution recovery model (i.e. a joint multiple measurement vectors (MMV) problem with the same support). So, an optimized orthogonal matching pursuit (OMP) algorithm for this joint problem is proposed, which can jointly solve MMV problems with identical support, different solution coefficients, and different sensing matrices. This method can address the issue of different signals sampled in different time segments, and the cases where signal strengths varying along the sampling times. Simulation results validated the superiority and adaptability of the jointly-solved OMP algorithm.