通信学报2025，Vol.46Issue(2)：59-71,13.DOI:10.11959/j.issn.1000-436x.2025032
城轨车-地场景下基于CGAN-LSTM网络的OTFS-ISAC系统信道估计
OTFS-ISAC system channel estimation based on GAN-LSTM network in urban rail train-infrastructure scenario
摘要
Abstract
In order to solve the problem of integrated sensing and communication(ISAC)signal transmission channel es-timation in commercial B5G/6G urban rail train-infrastructure scenario,a channel estimation method based on deep learning was proposed.An ISAC signal transmission system model based on orthogonal time frequency space(OTFS)modulation was established,the OTFS pilot was introduced,with OTFS pilot introduced to aid,CGAN-LSTM combin-ing conditional generative adversarial network(CGAN)and long short-term memory(LSTM)network was designed.Chaos game optimization(CGO)algorithm was combined with classical Adam optimizer to optimize the network param-eters,and the optimized network was used to complete the channel estimation.Simulation results show that the proposed method is superior to traditional channel estimation methods in normalized mean square error and bit error rate,and pro-vides necessary data basis for ISAC signal detection and recovery.关键词
通信感知一体化/正交时频空/条件生成对抗网络/长短期记忆/混沌博弈优化Key words
ISAC/OTFS/CGAN/LSTM/CGO分类
电子信息工程引用本文复制引用
杨骞,苏宏升,陶旺林,刘大为..城轨车-地场景下基于CGAN-LSTM网络的OTFS-ISAC系统信道估计[J].通信学报,2025,46(2):59-71,13.基金项目
甘肃省高校教师创新基金资助项目(No.2025B-239) （No.2025B-239）
兰州工业学院青年科技创新基金资助项目(No.2024KJ-16) （No.2024KJ-16）
甘肃省高校青年博士支持项目(No.2023QB-049) The University Teachers'Innovation Fund Project of Gansu Province(No.2025B-239),The Youth Science and Technology Innovation Project of Lanzhou Institute of Technology(No.2024KJ-16),The University Young Doctor Support Project of Gansu Province(No.2023QB-049) （No.2023QB-049）
