Sparse code multiple access(SCMA)is a new multi-carrier non-orthogonal multiple access technology proposed for the fifth generation(5G)communication system.The main idea is to design a multi-dimensional codebook at the transmitter.Combining the two steps of modulation and sparse spreading,at the receiver,depending on the sparsity of the userresource allocation matrix,a factor graph is established,and multi-user detection is performed through a message passing algorithm.The performance improvement offered by SCMA to the communication system mainly comes from the shaping gain of the multidimensional constellation diagram,and it can achieve a great increase in the number of loading.As a key technology at the 5G air-interface level,SCMA emerges in response to the widely connecting and using on a large scale,the demand for coverage and low latency in5 G wireless communication networks.The research content of this thesis mainly focuses on the application of index modulation in SCMA and resource allocation optimization based on matching theory model.This thesis firstly studies the application of index modulation(IM)to uplink sparse code multiple access,and proposes a novel scheme called SCMA-IM.In the scheme,the candidate resources of one user are partitioned into two groups.All the resources in the first group are utilized to transmit signals,and only part of resources in the second are activated through IM to transmit signals.The signal codebooks transmitted in these resources are jointly designed according to the same method as SCMA.Moreover,an effective message passing algorithm is presented to perform the multiuser detection of SCMA-IM.Simulation results show that when the receiver is equipped with more antennas,the proposed SCMAIM has better performance than traditional SCMA.Next,based on the matching theory,this thesis proposes an optimization scheme for user resource allocation of SCMA systems on slow fading channels.Firstly,through the iterative method of matching state update,the sum rate of SCMA system is maximized under the structural constraints of the resource allocation matrix.Furthermore,to consider the user fairness,two other optimizations are presented.The first is to introduce additional constraint on the maximum rate difference of any two users in the sum-rate maximization optimization.The second is to maximize the minimum user rate directly.Meanwhile,in the rate optimization considered here,the achievable rate is computed based on single-user detection and ordered successive interference cancellation,respectively.Finally,theoretical and simulated results verify the effectiveness of the proposed optimizations. |