Windowed Dictionary Design for Delay-Aware OMP Channel Estimation under Fractional Doppler
Hanning Wang, Xiang Huang, Rong-Rong Chen, and Arman Farhang

TL;DR
This paper introduces a delay-aware OMP algorithm with a windowed dictionary to improve channel estimation in delay-Doppler domains, effectively handling fractional Doppler shifts and outperforming standard methods.
Contribution
The paper proposes a novel windowed dictionary design and a delay-aware OMP algorithm that mitigates fractional Doppler effects without needing a predefined stopping criterion.
Findings
Significant NMSE improvement over standard OMP.
Effective reduction of column correlation in the dictionary.
Robust performance in fractional Doppler scenarios.
Abstract
Delay-Doppler (DD) signal processing has emerged as a powerful tool for analyzing multipath and time-varying channel effects. Due to the inherent sparsity of the wireless channel in the DD domain, compressed sensing (CS) based techniques, such as orthogonal matching pursuit (OMP), are commonly used for channel estimation. However, many of these methods assume integer Doppler shifts, which can lead to performance degradation in the presence of fractional Doppler. In this paper, we propose a windowed dictionary design technique while we develop a delay-aware orthogonal matching pursuit (DA-OMP) algorithm that mitigates the impact of fractional Doppler shifts on DD domain channel estimation. First, we apply receiver windowing to reduce the correlation between the columns of our proposed dictionary matrix. Second, we introduce a delay-aware interference block to quantify the interference…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Communication Networks Research · Advanced Wireless Communication Techniques · Advanced MIMO Systems Optimization
