Backtracking StOMP Detection Algorithm for GRASK Systems

‍ ‍In this paper， a low-complexity detection algorithm based on compressed sensing （CS） theory is proposed： backtracking stagewise Orthogonal Matching Pursuit （BStOMP） suboptimal detection algorithm， which obviously solves the problem that the complexity of optimal maximum likelihood （ML） detection algorithm increases greatly with the increase of activated receive antennas in generalized receive antenna shift keying （GRASK） system. Firstly， when the inner product of iterative residuals and equivalent channel matrices is greater than the set threshold， the candidate active antenna index is selected. Then the candidate active antenna index is estimated by the least square method. Finally， the backtracking process is introduced to eliminate some redundant indexes and improve the reconfiguration precision. Simulation results indicates that under the same conditions， compared with traditional StOMP detection algorithm， the detection performance of the proposed algorithm can be greatly improved with a small increase in computational complexity， thus ensuring a good balance between detection performance and computational complexity.