Research On Detection Algorithms Of Non-orthogonal Multiple Access Technologies

The conventional orthogonal multiple access technology can no longer meet the demands of mass connectivity and massive data transmission brought about by the rapid development of mobile networks and Internet of Things.As a typical type of high spectrum efficiency,non-orthogonal multiple access technology has an effective way of accessing a large number of users and has become a research hotspot at home and abroad.In the code domain non-orthogonal multiple access technology,Sparse Code Division Multiple Access(SCMA)utilizes high-dimensional codebooks with sparse structure and has good performance,and can be applied to most application scenarios;multiple users share access(MUSA)can support several times of user overload with shorter spreading sequences,and utilizes low-complex serial interference cancellation strategy,which is suitable for low-cost,low-power IoT scenarios.Because of its high-dimensional modulation,optimal performance SCMA detection algorithm has extremely high complexity.And,MUSA needs a low-complexity and high-performance detection method to support low-power consumption.This article will focus on the low-complexity and high-performance detection algorithms of SCMA and MUSA.The application of the MCMC method with polynomial increasing complexity in the SCMA and MUSA is the focus of this article.In the uplink SCMA detection,first of all,this paper deduces the low complexity orthogonal separation SPMPA algorithm and the corresponding log domain SPMax-Log MPA algorithm in the constellation compression SCMA model.Simulation results show that it has no performance loss,and only 10% complexity of the conventional algorithm.Then,based on the application of MCMC in MIMO,the MCMC method is applied to SCMA detection,and the MCMC-SCMA method based on bit updating and symbol updating is deduced,and the performance enhancement techniques such as multi-channel parallel sampling and dithering techniques are applied..With 16 QAM modulation,compared to the conventional Max-Log MPA algorithm,symbol updating MCMCSCMA method requires only 16% of the computational complexity.In the uplink MUSA detection,this paper first deduces the MUSA model power allocation scheme,and proposes a perfect interference cancellation algorithm and a nonperfect interference cancellation algorithm.Then,the MCMC method is applied to the MUSA detection,and the MCMC-SIC method based on bit updating and symbol updating is deduced.In the low-order modulation,the MMSE-SIC algorithm is used to obtain 60% complexity and 90% complexity,respectively,and get 0.4dB and 0.8dB performance gain,approximating the performance of ML algorithms.In the LDPC coded SCMA model,in order to speed up the message interaction efficiency and reduce the detection complexity,the serial joint detection and decoding strategy is deduced and generalized.Meanwhile,in the logarithm domain,a lowcomplexity logarithmic serial joint detection algorithm is proposed.Simulation and statistics show that compared with the traditional joint detection algorithm,the serial joint detection and decoding algorithm can reduces 64% computational complexity.