重庆邮电大学学报（自然科学版）2024，Vol.36Issue(2)：242-249,8.DOI:10.3979/j.issn.1673-825X.202306150201
基于ROAMP-Net的大规模MIMO系统智能信号检测方法
Intelligent signal detection method based on ROAMP-Net for massive MIMO systems
赵梓焱 1刘丽哲 1杨朔 1李勇1
作者信息
- 1. 中国电科网络通信研究院 通信网信息传输与分发技术重点实验室,石家庄 050081
- 折叠
摘要
Abstract
The signal detection in massive multiple-input multiple-output(MIMO)systems usually confronts the challenges of high computation complexity and low detection accuracy.Artificial intelligence technologies have been widely applied to improve the performance of signal detection.OAMP-Net is a signal detection algorithm based on deep learning,and its com-prehensive performance is relatively better than other typical signal detection algorithms.Inspired by the ideas of OAMP-Net,we propose a new intelligent signal detection model,i.e.ROAMP-Net,by introducing residual structure.In ROAMP-Net,the iteration of orthogonal approximate message passing(OAMP)is extended to a deep learning network.Meanwhile,to prevent the performance degradation of deep network with the increase of network layers,the model introduces residual structure to correct the linear and non-linear signal estimation layer by layer,so that the estimation errors would not be for-warded and accumulated.Consequently,high accuracy of signal detection can be expected.Simulation experimental tests suggest that ROAMP-Net outperforms many benchmarks on the accuracy of signal detection under different modulation methods and antenna arrays.关键词
大规模MIMO/信号检测/深度学习/残差结构Key words
massive MIMO/signal detection/deep learning/residual structure分类
信息技术与安全科学引用本文复制引用
赵梓焱,刘丽哲,杨朔,李勇..基于ROAMP-Net的大规模MIMO系统智能信号检测方法[J].重庆邮电大学学报（自然科学版）,2024,36(2):242-249,8.
