Research On Multi-user Detection Technology Based Compressive Sensing For Multi-User Shared Access System

In the rapid development of mobile communications,multiple access technology has become the core technology to achieve internet of everything,and it is also the key technologies to affect the performance of communication systems.Orthogonal multiple access is used in the first four generations of mobile communication systems,in which the orthogonality of user resources should be strictly guaranteed so that users do not interfere with each other,so as to ensure that multi-user detection at the receiver has lower bit error rate and computational complexity.However,the existing orthogonal multiple access technology can not meet the high requirements of the fifth generation mobile communication system(5G)for system capacity,spectrum efficiency and other performance.The introduction of non-orthogonal multiple access(NOMA)technology can improve the spectral efficiency and increase the number of users,so it is important to study non-orthogonal multiple access technology in 5G to effectively improve the system capacity.Through in-depth research on non-orthogonal multiple access technology,it is found that the combination of non-orthogonal multiple access and grant-free access can reduce the burden of access signaling and transmission delay.In the non-orthogonal multiple access scheme,only the multi-user shared multiple access(MUSA)scheme is proposed and the grant-free access is considered.This thesis considers grant-free access in the MUSA system,and considers that the user's transmission behavior with sparse characteristics.In this scenario,active users need to be detected in advance to adopt the traditional multi-user detection method for data recovery,which leads to high complexity of the receiver.The sparse reconstruction ideas in compressive sensing can solve such problems.Combining compressive sensing and MUSA system to study multi-user detection technology in this thesis,and the key research work is the following aspects.Firstly,the uplink and downlink system models and capacities of non-orthogonal multiple access are studied,and two non-orthogonal multiple access schemes,sparse code multiple access(SCMA)and MUSA,are introduced emphatically.At the same time,the multi-user detection technology in non-orthogonal multiple access system is analyzed and introduced.Secondly,summarize the research progress of compressive sensing theory,analyze the single-slot grant-free uplink MUSA system model,and summarize the multi-user detection algorithm based on compressive sensing by using its sparse transmission behavior.In the compressive sensing reconstructlion algorithm,the orthogonal matching pursuit(OMP)algorithm and the compressive sampling matching pursuit(CoSaMP)algorithm are mainly studied to realize the multi-user detection in this system.At the same time,in order to improve the multi-user detection performance of compressive sensing reconstruction algorithm,a Toeplitz matrix is designed as a spread spectrum sequence to meet the design requirements of compressive sensing measurement matrix.Through algorithm analysis and simulation verification,it shows that multi-user detection algorithm based on compressive sensing has good error code performance.At the same time,under the condition of high overload rate,better recovery effect can be obtained.Thirdly,based on the study of single-slot grant-free uplink MUSA system,the multi-slot grant-free uplink MUSA system is further studied,and a multi-user detection method based on structured compressive sensing is proposed.First of all,based on the research of compressive sensing theory,the structured comppressive sensing theory is further studied.The structure sparse characteristics of the active user's transmission behavior set in the case of multi-slots grant-free uplink MUSA system are analyzed.Then using the structured matching pursuit(SMP)algorithm to perform multi-user detection in the uplink MUSA system.Finally,algorithm analysis and simulation results show that compared with the traditional compressive sensing algorithm,the SNR gain is about 2 dB when the bit error rate is 10-3.