Sparse Code Multiple Access(SCMA)technology is a highly valued code domain-based Non-Orthogonal Multiple Access(NOMA)technology.In order to solve the problem that the existing SCMA codebook design fails to combine the properties of data and decoder and the high complexity of MPA,a compressed sensing-assisted low-complexity SCMA system optimization design scheme is proposed.First,a codebook self-updating method is designed based on the system bit error rate optimization goal,which uses the gradient descent method to achieve self-updating of the codebook during the sparse vector reconstruction training process.Second,a compressed sensing-assisted multi-user detection algorithm is designed:Sign Decision Orthogonal Matching Pursuit(SD-OMP)algorithm.By sparse processing of the transmitted signal at the transmitting end,the compressed sensing technology is used at the receiving end to efficiently detect and reconstruct multi-user sparse signals,this results in a reduction of conflicts between users and a reduction in system complexity.The simulation results show that under Gaussian channel conditions,the compressed sensing-assisted low-complexity SCMA system optimization and design scheme can effectively reduce the complexity of multi-user detection,and can show better bit error rate performance when the system user part is active.
维普
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