A Novel Cross-Domain Channel Estimation Scheme for OFDM

2026-01-21

AI Summary

This work addresses the severe degradation of channel estimation performance in OFDM systems under high-mobility scenarios by proposing a cross-domain channel estimation algorithm. The method first maps time–frequency pilot symbols into the delay–Doppler domain and employs two-dimensional warped convolution to obtain coarse channel parameters. Subsequently, it refines the estimate by solving a sparse signal recovery problem formulated as an ℓ₁-regularized least squares optimization in the time–frequency domain. The approach innovatively integrates the coarse delay–Doppler domain estimation with a sparse recovery framework and establishes a theoretical analysis based on the ambiguity function. Experimental results demonstrate that the proposed method significantly outperforms conventional schemes in high-mobility environments, achieving notably improved channel estimation accuracy.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Mobility, Driving & Flight
• Intelligent Robots: State Estimation

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

In this paper, we propose a novel cross-domain channel estimation (CDCE) algorithm for orthogonal frequency division multiplexing (OFDM) systems, leveraging the unique characteristics of the delay-Doppler (DD) domain channel. Specifically, the proposed algorithm transforms the time-frequency (TF) domain pilot sequence of OFDM into the DD domain and applies a two-dimensional (2D) twisted-convolution for acquiring a coarse estimation of the underlying channel delay and Doppler. Then, the OFDM channel estimation is formulated as a sparse signal recovery problem in the TF domain according to the dictionary derived based on the obtained delay and Doppler estimates. Furthermore, a low-complexity $\ell_1$-regularized least-square estimator is proposed to effectively solve this problem. Moreover, we further develop a performance analysis framework of the proposed scheme based on the ambiguity function (AF) of the adopted pilot sequence. Our numerical results demonstrate noticeable estimation performance improvement compared to conventional OFDM channel estimation methods, particularly in the presence of high channel mobility.

Problem

• OFDM
• channel estimation
• high mobility
• cross-domain
• delay-Doppler

Innovation

• cross-domain channel estimation
• delay-Doppler domain
• sparse signal recovery
• twisted convolution
• ambiguity function