移动通信2024，Vol.48Issue(7)：46-56,11.DOI:10.3969/j.issn.1006-1010.20240422-0001
基于机器学习的OTFS系统信道估计与信号检测研究进展
Advancements in Machine Learning-Based Channel Estimation and Signal Detection for OTFS Systems
摘要
Abstract
OTFS modulation effectively combats ICI in high-mobility scenarios,offering significant performance gains over traditional OFDM and enhancing spectral efficiency and communication quality in high-Doppler environments,thus attracting extensive research interest in recent years.The primary focus and challenge in OTFS systems lie in channel estimation and signal detection.Artificial intelligence has emerged as a potent information processing tool,widely adopted across various industries.Machine learning,as a crucial branch of artificial intelligence,when integrated with the OTFS technique,addresses issues in channel estimation and signal detection,thereby improving system performance,stability,and reliability.This paper provides a comprehensive survey,analysis,comparison,and synthesis of current machine learning-based algorithms for channel estimation and signal detection in OTFS systems,identifies technical challenges,and discusses future technological development trends.关键词
人工智能/机器学习/第六代移动通信/正交时频空/信道估计/信号检测Key words
artificial intelligence/machine learning/sixth generation mobile communication/orthogonal time-frequency space/channel estimation/signal detection分类
电子信息工程引用本文复制引用
廖勇,韩小金..基于机器学习的OTFS系统信道估计与信号检测研究进展[J].移动通信,2024,48(7):46-56,11.基金项目
重庆市自然科学基金"面向超高速移动场景的OTFS系统信道估计与均衡研究"(CSTB2023NSCQ-MSX0025) （CSTB2023NSCQ-MSX0025）
