Affine Frequency Division Multiplexing for Compressed Sensing of Time-Varying Channels

Fuente: arXiv
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Hauptverfasser: Benzine, Wissal, Bemani, Ali, Ksairi, Nassar, Slock, Dirk
Format: Preprint
Veröffentlicht: 2024
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author Benzine, Wissal
Bemani, Ali
Ksairi, Nassar
Slock, Dirk
author_facet Benzine, Wissal
Bemani, Ali
Ksairi, Nassar
Slock, Dirk
contents This paper addresses compressed sensing of linear time-varying (LTV) wireless propagation links under the assumption of double sparsity i.e., sparsity in both the delay and Doppler domains, using Affine Frequency Division Multiplexing (AFDM) measurements. By rigorously linking the double sparsity model to the hierarchical sparsity paradigm, a compressed sensing algorithm with recovery guarantees is proposed for extracting delay-Doppler profiles of LTV channels using AFDM. Through mathematical analysis and numerical results, the superiority of AFDM over other waveforms in terms of channel estimation overhead and minimal sampling rate requirements in sub-Nyquist radar applications is demonstrated.
format Preprint
id arxiv_https___arxiv_org_abs_2407_02953
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Affine Frequency Division Multiplexing for Compressed Sensing of Time-Varying Channels
Benzine, Wissal
Bemani, Ali
Ksairi, Nassar
Slock, Dirk
Information Theory
This paper addresses compressed sensing of linear time-varying (LTV) wireless propagation links under the assumption of double sparsity i.e., sparsity in both the delay and Doppler domains, using Affine Frequency Division Multiplexing (AFDM) measurements. By rigorously linking the double sparsity model to the hierarchical sparsity paradigm, a compressed sensing algorithm with recovery guarantees is proposed for extracting delay-Doppler profiles of LTV channels using AFDM. Through mathematical analysis and numerical results, the superiority of AFDM over other waveforms in terms of channel estimation overhead and minimal sampling rate requirements in sub-Nyquist radar applications is demonstrated.
title Affine Frequency Division Multiplexing for Compressed Sensing of Time-Varying Channels
topic Information Theory
url https://arxiv.org/abs/2407.02953