无线电通信技术2025，Vol.51Issue(1)：29-35,7.DOI:10.3969/j.issn.1003-3114.2025.01.004
基于改进CPD的RIS辅助毫米波OFDM系统信道估计算法
Improved CPD-based RIS-assisted Millimeter Wave OFDM System Channel Estimation Algorithm
摘要
Abstract
In the field of wireless communication,the performance of a system is often closely related to the characteristics of wire-less channel.Accurately grasping channel and signal parameters is crucial for improving the reliability and efficiency of information transmission,making channel estimation one of the core technologies in this field.However,due to the unpredictability of wireless channel and the involvement of multiple dimensions(such as space,time,frequency,etc.)during signal transmission,the design of channel estimation methods becomes extremely complex.Recent studies have shown that converting these multidimensional signals into tensors for analysis can significantly reduce the technical difficulty of channel estimation.This article mainly discusses the improvement methods of channel estimation algorithms,particularly introducing centralized processing as part of data pre-processing.Centralized processing improves the Signal-to-Noise Ratio(SNR)by adjusting the mean value of the data to reduce low-frequency noise.This not only enhances the accuracy of channel estimation but also simplifies the complexity of algorithm implementation,accelerating model training speed and improving convergence efficiency.Additionally,we employ factorization methods to decompose tensors,which fur-ther reduces computational complexity and improves estimation accuracy.Simulation results indicate that the improved algorithm not on-ly has higher accuracy but also exhibits superior performance in low SNR environments.关键词
智能反射面辅助/正交频分复用技术/信道估计/张量/因子分解Key words
RIS-assisted/OFDM/channel estimation/tensor/factorization分类
信息技术与安全科学引用本文复制引用
任进,李一博,周培豫,李玉宇..基于改进CPD的RIS辅助毫米波OFDM系统信道估计算法[J].无线电通信技术,2025,51(1):29-35,7.基金项目
2025 年北京市大学生创新创业训练计划项目 （）
2023 年北京市高等教育学会面上课题(MS2023178) 2025 Beijing College Students Innovation and Entrepreneurship Training Program Project （MS2023178）
2023 Beijing Higher Education Association General Project(MS2023178) （MS2023178）
