WiFi-Based Channel Impulse Response Estimation and Localization via Multi-Band Splicing

Khalilsarai, Mahdi Barzegar; Groß, Benedikt; Stefanatos, Stelios; Wunder, Gerhard; Caire, Giuseppe

doi:10.1109/globecom42002.2020.9348213

Cited by 15 publications

(5 citation statements)

References 13 publications

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“…Compressed sensing (CS) based methods: In an indoor environment, the CIR is sparse since it consists of only a small number of paths. Motivated by the sparsity of CIR over the delay domain, many state-of-the-art delay estimation algorithms have been proposed based on CS methods [15], [16], [17]. In [15], [16], the authors formulated l 1 -norm minimization problems for capturing the signal sparsity.…”

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

“…In [15], [16], the authors formulated l 1 -norm minimization problems for capturing the signal sparsity. In [17], orthogonal matching pursuit (OMP) methods have been used…”

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

“…On the other hand, many works have not considered the imperfect phase distortion factors caused by receiver timing offset or phase noise in practical systems [14], [18], [20], [29]. Though some studies in [15], [17], [19] have considered the phase distortion, the calibration of the phase distortions with extra information is required via a handshaking procedure under the assumption of channel reciprocity. However, this assumption is restrictive and the transceiver needs to have the ability of Tx/Rx switching.…”

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

“…Then, a novel two-stage global estimation (TSGE) scheme is proposed to fully exploit all the multiband gains, where we consider all the phase distortion factors and calibrate them implicitly without using extra handshaking procedures. Compared to the CS-based delay estimation methods in [15], [16], [17], our proposed algorithm achieves higher estimation accuracy with lower computational complexity. It is because we adopt a dynamic grid adjustment strategy and we do not need a very dense grid.…”

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

“…However, the estimation accuracy of the multipath channel delays is limited by the bandwidth of the transmitted signal. To address this issue, the multiband delay estimation schemes have been proposed in [14], [15], [16], [17], [18], [19], [20], [21], which make use of the channel state information (CSI) measurements across multiple frequency bands to obtain high accuracy delay estimation. Compared to single band delay estimation, multiband delay estimation can obtain extra multiband gains, which consist of two parts: (i) Multiband CSI samples lead to more subcarrier apertures gain; (ii) Frequency band apertures gain brought by the difference of carrier frequency between subbands [19].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme

Wan¹,

Liu²,

Hu³

et al. 2022

Preprint

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The time of arrival (TOA)-based localization techniques, which need to estimate the delay of the line-of-sight (LoS) path, have been widely employed in location-aware networks. To achieve a highaccuracy delay estimation, a number of multiband-based algorithms have been proposed recently, which exploit the channel state information (CSI) measurements over multiple non-contiguous frequency bands.However, to the best of our knowledge, there still lacks an efficient scheme that fully exploits the multiband gains when the phase distortion factors caused by hardware imperfections are considered, due to that the associated multi-parameter estimation problem contains many local optimums and the existing algorithms can easily get stuck in a "bad" local optimum. To address these issues, we propose a novel two-stage global estimation (TSGE) scheme for multiband delay estimation. In the coarse stage, we exploit the group sparsity structure of the multiband channel and propose a Turbo Bayesian inference (Turbo-BI) algorithm to achieve a good initial delay estimation based on a coarse signal model, which is transformed from the original multiband signal model by absorbing the carrier frequency terms.The estimation problem derived from the coarse signal model contains less local optimums and thus a more stable estimation can be achieved than directly using the original signal model. Then in the refined stage, with the help of coarse estimation results to narrow down the search range, we perform a global delay estimation using a particle swarm optimization-least square (PSO-LS) algorithm based on a refined multiband signal model to exploit the multiband gains to further improve the estimation accuracy. Simulation results show that the proposed TSGE significantly outperforms the benchmarks with comparative computational complexity.

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Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

“…In [15], [16], the authors formulated l 1 -norm minimization problems for capturing the signal sparsity. In [17], orthogonal matching pursuit (OMP) methods have been used…”

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

Section: Subspace Based Estimation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme

Wan¹,

Liu²,

Hu³

et al. 2022

Preprint

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Survey on coherent multiband splicing techniques for wideband channel characterization

Dimce,

Dressler

2024

IET Communications

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Coherent multi‐band splicing is an optimal solution for extending existing band‐limited communication systems to support high‐precision sensing applications. Conceptually, the communication system performs narrow‐band measurements at different centre frequencies, which are then concatenated to increase the effective bandwidth without altering the sampling rate. This can be done in parallel for multiple non‐contiguous subbands or by hopping across the different bands. However, multi‐band splicing poses significant challenges, particularly in compensating for phase offsets and hardware distortions before stitching the acquired samples, which can be distributed in contiguous or non‐contiguous manners. This survey paper studies the state of the art in coherent multi‐band splicing and identify open research questions. For beginners in the field, this review serves as a guide to the most relevant literature, enabling them to quickly catch up with the current achievements. For experts, open research questions that require further investigation are highlighted.

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Channel Sounder in Indoor Environment with Multipath Fading using Software Defined Radio

Pamungkas,

Isnawati,

Larasati

et al. 2023

2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)

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WiFi-Based Channel Impulse Response Estimation and Localization via Multi-Band Splicing

Cited by 15 publications

References 13 publications

Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme

Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme

Survey on coherent multiband splicing techniques for wideband channel characterization

Channel Sounder in Indoor Environment with Multipath Fading using Software Defined Radio

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