Estimating Multipath Component Delays With Transformer Models
Multipath in radio propagation provides essential environmental information that is exploited for positioning or channel-simultaneous localization and mapping. This enables accurate and robust localization that requires less infrastructure than traditional methods. A key factor is the reliable and a...
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| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Journal of Indoor and Seamless Positioning and Navigation |
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| Online Access: | https://ieeexplore.ieee.org/document/10584252/ |
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| author | Jonathan Ott Maximilian Stahlke Tobias Feigl Christopher Mutschler |
| author_facet | Jonathan Ott Maximilian Stahlke Tobias Feigl Christopher Mutschler |
| author_sort | Jonathan Ott |
| collection | DOAJ |
| description | Multipath in radio propagation provides essential environmental information that is exploited for positioning or channel-simultaneous localization and mapping. This enables accurate and robust localization that requires less infrastructure than traditional methods. A key factor is the reliable and accurate extraction of multipath components (MPCs). However, limited bandwidth and signal fading make it difficult to detect and determine the parameters of the individual signal components. In this article, we propose multipath delay estimation based on a transformer neural network. In contrast to the state of the art, we implicitly estimate the number of MPCs and achieve subsample accuracy without using computationally intensive super-resolution techniques. Our approach outperforms known methods in detection performance and accuracy at different bandwidths. Our ablation study shows exceptional results on simulated and real datasets and generalizes to unknown radio environments. |
| format | Article |
| id | doaj-art-92ca83e2e76e4c52b343957cb29edbc7 |
| institution | OA Journals |
| issn | 2832-7322 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Indoor and Seamless Positioning and Navigation |
| spelling | doaj-art-92ca83e2e76e4c52b343957cb29edbc72025-08-20T02:05:01ZengIEEEIEEE Journal of Indoor and Seamless Positioning and Navigation2832-73222024-01-01221922910.1109/JISPIN.2024.342290810584252Estimating Multipath Component Delays With Transformer ModelsJonathan Ott0https://orcid.org/0009-0006-4328-4228Maximilian Stahlke1https://orcid.org/0000-0002-3572-7707Tobias Feigl2https://orcid.org/0000-0002-3040-3543Christopher Mutschler3https://orcid.org/0000-0001-8108-0230Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Division Positioning and Networks, Nuremberg, GermanyFraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Division Positioning and Networks, Nuremberg, GermanyFraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Division Positioning and Networks, Nuremberg, GermanyFraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, Division Positioning and Networks, Nuremberg, GermanyMultipath in radio propagation provides essential environmental information that is exploited for positioning or channel-simultaneous localization and mapping. This enables accurate and robust localization that requires less infrastructure than traditional methods. A key factor is the reliable and accurate extraction of multipath components (MPCs). However, limited bandwidth and signal fading make it difficult to detect and determine the parameters of the individual signal components. In this article, we propose multipath delay estimation based on a transformer neural network. In contrast to the state of the art, we implicitly estimate the number of MPCs and achieve subsample accuracy without using computationally intensive super-resolution techniques. Our approach outperforms known methods in detection performance and accuracy at different bandwidths. Our ablation study shows exceptional results on simulated and real datasets and generalizes to unknown radio environments.https://ieeexplore.ieee.org/document/10584252/5Gattentionmultipath (MP)radio localizationtransformer (TF)ultrawideband (UWB) |
| spellingShingle | Jonathan Ott Maximilian Stahlke Tobias Feigl Christopher Mutschler Estimating Multipath Component Delays With Transformer Models IEEE Journal of Indoor and Seamless Positioning and Navigation 5G attention multipath (MP) radio localization transformer (TF) ultrawideband (UWB) |
| title | Estimating Multipath Component Delays With Transformer Models |
| title_full | Estimating Multipath Component Delays With Transformer Models |
| title_fullStr | Estimating Multipath Component Delays With Transformer Models |
| title_full_unstemmed | Estimating Multipath Component Delays With Transformer Models |
| title_short | Estimating Multipath Component Delays With Transformer Models |
| title_sort | estimating multipath component delays with transformer models |
| topic | 5G attention multipath (MP) radio localization transformer (TF) ultrawideband (UWB) |
| url | https://ieeexplore.ieee.org/document/10584252/ |
| work_keys_str_mv | AT jonathanott estimatingmultipathcomponentdelayswithtransformermodels AT maximilianstahlke estimatingmultipathcomponentdelayswithtransformermodels AT tobiasfeigl estimatingmultipathcomponentdelayswithtransformermodels AT christophermutschler estimatingmultipathcomponentdelayswithtransformermodels |