NOMA系统基于改进的近似消息传递算法的联合信道估计与多用户检测

Joint Channel Estimation and Multiuser Detection of NOMA System Based on Improved Approximate Message Passing Algorithm

针对免调度非正交多址接入(Non-Orthogonal Multiple Access,NOMA)系统,多用户传输场景的上行信道估计(Channel Estimation,CE)与活动用户检测(Active User Detection,AUD)问题可被建模为压缩感知重建问题。本文提出了一种改进的近似消息传递(Approximate Message Passing,AMP)算法——阈值自适应-加约束重加权-近似消息传递(Threshold Adaptive Constrained Reweighted Approximate Message Passing,TA-CR-AMP)算法来联合解决CE和AUD问题。该算法在合适的迭代终止准则下,对AMP算法加入更新稀疏信号稀疏结构的操作,在此基础上对算法引入加约束的重加权,并令阈值自适应变化。仿真结果表明,与AMP算法相比,本文提出的算法以较低的复杂度获得了更加优越的信道估计和活跃用户检测性能。另外,本算法获得了与更加复杂的期望最大-贝叶斯AMP(Expectation Maximization Bayesian Approximate Message Passing,EM-B-AMP)算法相近的性能。

For scheduling-free non-orthogonal multiple access(NOMA)systems,the uplink channel estimation(CE)and active user detection(AUD)issues in multi-user transmission scenarios can be modeled as the reconstruction problem of compressed sensing.In view of the shortcomings of the existing compressed sensing algorithms,this paper proposes an improved Approximate Message Passing(AMP)algorithm-Threshold Adaptive Constrained Reweighted Approximate Message Passing(TA-CR-AMP)algorithm to combine Solve CE and AUD problems.The algorithm adds the operation of updating the sparse structure of the sparse signal to the AMP algorithm under a suitable iteration termination criterion,and on this basis introduces a constrained heavy weighting to the algorithm,and makes the threshold adaptively change.The simulation results show that,compared with the AMP algorithm,the algorithm proposed in this paper obtains more superior channel estimation and active user detection performance with lower complexity.In addition,the algorithm proposed in this paper has achieved similar performance to the more complex Expectation Maximization Bayesian Approximate Message Passing(EM-B-AMP)algorithm.