电波科学学报2023，Vol.38Issue(6)：1048-1056,9.DOI:10.12265/j.cjors.2022253
H-ResGAN在智能反射面辅助通信系统中的信道估计
Hybrid loss based residual generative adversarial network for channel estimation in intelligent reflecting surface assisted communication systems
摘要
Abstract
Intelligent reflecting surface(IRS)aided communication systems have high channel dimensionality and the existing channel estimation methods require a lot of pilots to obtain an accurate channel matrix.To address this problem,a hybrid loss based residual generative adversarial network(H-ResGAN)model is proposed.H-ResGAN uses multiple residual blocks to deepen the network,which can fully extract channel features and mitigate the gradient disappearance problem.At the same time,a hybrid loss combining least squares loss and LI loss is adopted as the objective function to improve the stability of the training.Simulation experiments demonstrate that H-ResGAN is more robust to environmental noise and has significantly lower estimation errors than traditional methods.In addition,H-ResGAN can obtain accurate estimation results by sending only few pilots compared to traditional estimation algorithms.关键词
智能反射面(IRS)/信道估计/毫米波/基于混合损失的残差生成对抗网络(H-ResGAN)/混合损失Key words
intelligent reflecting surface(IRS)/channel estimation/millimeter wave/hybrid loss based residual generative adversarial networks(H-ResGAN)/hybrid loss分类
信息技术与安全科学引用本文复制引用
张欣怡,江沸菠,彭于波,董莉..H-ResGAN在智能反射面辅助通信系统中的信道估计[J].电波科学学报,2023,38(6):1048-1056,9.基金项目
国家自然科学基金(41874148,41904127,41604117) （41874148,41904127,41604117）
