基于智能反射表面大规模MIMO-NOMA系统频谱效率分析

Spectrum efficiency analysis of massive MIMO-NOMA system based on intelligent reflecting surface

摘要:

为了进一步提高频谱效率，在大规模多输入多输出(MIMO)系统中引入了非正交多址(NOMA)，然而当基站与用户之间的信道较差时，这很难保证用户的频谱效率。为解决这一问题，探讨了基于智能反射表面(IRS)的大规模MIMO-NOMA系统，来保证用户的频谱效率。具体地，首先考虑了IRS辅助的大规模MIMO-NOMA系统模型。然后根据簇头选择算法，为每个波束选择一个簇头来设计模拟预编码。之后，根据等效信道的相关性对用户进行分组，选择在每个波束中等效信道增益最强的用户来设计数字预编码。最后联合优化基站的功率分配和IRS的相移矩阵，来保证用户频谱效率的公平性，即最大化最小频谱效率。仿真结果表明，与没采用IRS的大规模MIMO-NOMA系统相比，IRS辅助的大规模MIMO-NOMA系统可显著改善最弱用户的频谱效率。

Abstract:

Non-Orthogonal Multiple Access(NOMA) is introduced into massive Multiple Input Multiple Output(MIMO) system in order to further improve the spectrum efficiency. Nevertheless, when the channel between the base station and the user is poor, it is difficult to guarantee the spectrum efficiency of the user. A massive MIMO-NOMA system based on Intelligent Reflecting Surface(IRS) is discussed to deal with this problem. An IRS-assisted massive MIMO-NOMA system model is considered firstly. Then according to the cluster head selection algorithm, a cluster head is selected for each beam to design analog precoding. Users are grouped according to the correlation of equivalent channels, and the user with the strongest equivalent channel gain in each beam is selected to design digital precoding. Finally, the power allocation of the base station and the phase shift matrix of the IRS are jointly optimized to ensure the fairness of the user's spectral efficiency, that is, to maximize the minimum spectral efficiency. The simulation results show that compared with the massive MIMO-NOMA system without IRS, the IRS-assisted massive MIMO-NOMA system can significantly improve the spectrum efficiency of the weakest user.