移动通信2026，Vol.50Issue(4)：2-15,14.DOI:10.3969/j.issn.1006-1010.20260130-0001
面向低空经济超可靠低时延通信的信道估计研究进展
Research Progress on Channel Estimation for High-Reliability and Low-Latency Communications in Low-Altitude Economy
摘要
Abstract
As a strategic emerging industry,the development of the low-altitude economy is highly dependent on ultra-reliable and low-latency communication(URLLC)technology.Channel estimation,as a prerequisite for achieving ultra-high reliability at the physical layer of URLLC,faces severe challenges posed by the high dynamic and non-stationarity of low-altitude channels,as well as the short-packet transmission characteristics of URLLC.Therefore,this paper systematically reviews the research progress in channel estimation for URLLC in the low-altitude economy.Firstly,the particularities of low-altitude communication systems and channel models are elaborated,clarifying the core design principle of seeking the optimal trade-off between pilot overhead,estimation accuracy,and computational complexity under extreme latency and reliability constraints.Secondly,the existing technologies are comprehensively compared and analyzed from four dimensions:prior information acquisition,compressed sensing,tensor decomposition,and deep learning.Finally,current challenges are identified,including the contradiction between computational complexity and real-time requirements,insufficient tracking capability for non-stationary channels,and sensitivity to non-ideal factors,and future development trends under emerging architectures are discussed,such as the combination of multimodal and generative learning,integrated sensing and communication and massive multiple-input multiple-output.关键词
低空经济/超可靠低时延通信/信道估计/稀疏压缩感知/张量分解/深度学习Key words
low-altitude economy/ultra-reliable and low-latency communication/channel estimation/sparse compressed sensing/tensor decomposition/deep learning分类
信息技术与安全科学引用本文复制引用
廖勇,韩知孝..面向低空经济超可靠低时延通信的信道估计研究进展[J].移动通信,2026,50(4):2-15,14.基金项目
重庆市自然科学基金项目"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）
