RIS辅助卫星物联网中基于压缩感知的SCMA信号重构

SCMA Signal Reconstruction Based on Compressed Sensing in RIS-assisted Satellite Internet of Things

卫星物联网是未来6G网络重要组成部分,在地面部署可重构智能反射面(Reconfigurable Intelligence Surface,RIS)则能进一步增强天地之间信号的传输能力;然而海量设备的接入和检测,以及RIS的引入带来的较高复杂度,给系统设计与实现带来挑战。针对卫星物联网设备和业务稀疏特性,本文提出了一种基于压缩感知的信号重构算法,旨在提高系统的接入用户数和检测成功率,同时降低检测的复杂度。首先,介绍了RIS辅助的卫星物联网系统架构,构建了天地信道模型和星上接收信号模型。然后考虑到卫星物联网地面终端的稀疏性和业务的稀疏性,结合稀疏码分多址(Sparse Code Multiple Access,SCMA)和压缩感知的信号处理方法,通过合理设计SCMA中的稀疏码字,将多用户检测转化为压缩感知理论中的信号重构。最后提出了一种演进的近似消息传播算法(Evolved Approximate Message-Passing,EAMP)来实现压缩感知中的信号重构。仿真结果表明,RIS辅助的SCMA系统与功率域的非正交多址接入技术相比可以提高系统的吞吐量性能,同时EAMP算法相比传统的SIC算法具有更高的正确检测概率和更低的算法复杂度。

Satellite Internet of Things(IoT)is an important part of the future 6G network.The deployment of Reconfigurable Intelligence Surface(RIS)on the ground can further enhance the transmission capability of signals between heaven and earth.However,the access and detection problems of a large number of devices and the high complexity brought by the introduction of RIS pose challenges to the system design and implementation.To address the sparse nature of satellite IoT devices and services, this paper proposed a signal reconstruction algorithm based on compressed sensing, aiming to in crease the number of users accessed by the system, while reducing the complexity of user detection and increasing the probability of successful detection. Firstly, the RIS-assisted satellite IoT system architecture was introduced, and the heaven and earth channel model and on-satellite received signal model were constructed. Then, considering the sparsity of satellite IoT ground terminals and the sparsity of services, the signal processing processes of Sparse Code Multiple Access (SCMA) and compressed sensing were combined, and the multi-user detection was transformed into the signal reconstruc tion in compressed sensing theory by reasonably designing the sparse code words in SCMA. Finally, an Evolved Approxi mate Message-Passing (EAMP) algorithm was proposed to solve the signal reconstruction problem in compressive sensing. Simulation results show that the RIS-assisted SCMA system can improve the throughput performance of the system com pared to non-orthogonal multiple access technology in the power domain, while the EAMP algorithm has a higher probabil ity of correct detection and lower algorithmic complexity than the conventional SIC algorithm.