一种基于置信度稳定性的SCMA多用户检测算法

稀疏码分多址(即非正交多址)(Sparse Code Multiple Access,SCMA) 技术,具有在有限频谱资源下过载通信的特点,能够显著提升频谱利用率。得益于稀疏码分多址码本的稀疏性,消息传递算法(Message Passing Algorithm,MPA)成为经典多用户检测算法。在传统MPA方法中,尽管与最大似然译码具有相近的误比特率(Bit Error Ratio,BER)性能,但指数运算的复杂度仍然很高。据此,设计一种基于置信度的动态边缘选择更新方法,以减少不必要的节点运算。每次迭代中,利用因子图模型中功能节点到变量节点的置信度稳定性信息,动态判定是否需要节点更新运算。仿真结果表明,动态边缘选择方案使得算法的复杂度得到显著降低,并且能够与BER取得良好的均衡。

Multiuser Detection Scheme for SCMA Systems Based on Stability of Belief Propagation

The main feature of sparse code multiple access,i.e.,non-orthogonal multiple access,is supported by overloaded connection with limited resources,which can greatly improve the spectrum utilization.Thanks to the sparsity of the SCMA codebook sets,MPA becomes a basic receiver decoding algorithm.Although there exists a similar bit error ratio (BER) performance between the maximum likelihood (ML) detection scheme and traditional MAP method,the complexity of the exponential calculation is still high.To further reduce the complexity problem,a novel low-complexity detection algorithm based on dynamic edge selection strategy was proposed to reduce unnecessary node operation.In each iteration,the belief propagation stability information of the function node to the variable node in the factor graph model is used to dynamically determine whether a node update operation is required.The simulation results show that the complexity of the dynamic edge selection algorithm is significantly reduced,and the BER can be well balanced.