Localization Accuracy Improvement in Multistatic ISAC with LoS/NLoS Condition using 5G NR Signals
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916581219500032 |
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| author | Khosroshahi, Keivan Sehier, Philippe Mekki, Sami Suppa, Michael |
| author_facet | Khosroshahi, Keivan Sehier, Philippe Mekki, Sami Suppa, Michael |
| contents | Integrated sensing and communication (ISAC) is anticipated to play a crucial role in sixth-generation (6G) mobile communication networks. A significant challenge in ISAC systems is the degradation of localization accuracy due to poor propagation conditions, such as multipath effects and non-line-of-sight (NLoS) scenarios. These conditions result in outlier measurements that can severely impact localization performance. This paper investigates the enhancement of target localization accuracy in multistatic ISAC systems under both line-of-sight (LoS) and NLoS conditions. We leverage positioning reference signal (PRS), which is currently employed in fifth-generation (5G) new radio (NR) for user equipment (UE) positioning, as the sensing signal. We introduce a novel algorithm to improve localization accuracy by mitigating the impact of outliers in range measurements, while also accounting for errors due to PRS range resolution. Eventually, through simulation results, we demonstrate the superiority of the proposed method over previous approaches. Indeed, we achieve up to 28% and 20% improvements in average localization error over least squares (LS) and iteratively reweighted least squares (IRLS) methods, respectively. Additionally, we observe up to 16% and 13% enhancements in the 90th percentile of localization error compared to LS and IRLS, respectively. Our simulation is based on 3rd Generation Partnership Project (3GPP) standards, ensuring the applicability of our results across diverse environments, including urban and indoor areas. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_17577 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Localization Accuracy Improvement in Multistatic ISAC with LoS/NLoS Condition using 5G NR Signals Khosroshahi, Keivan Sehier, Philippe Mekki, Sami Suppa, Michael Signal Processing Integrated sensing and communication (ISAC) is anticipated to play a crucial role in sixth-generation (6G) mobile communication networks. A significant challenge in ISAC systems is the degradation of localization accuracy due to poor propagation conditions, such as multipath effects and non-line-of-sight (NLoS) scenarios. These conditions result in outlier measurements that can severely impact localization performance. This paper investigates the enhancement of target localization accuracy in multistatic ISAC systems under both line-of-sight (LoS) and NLoS conditions. We leverage positioning reference signal (PRS), which is currently employed in fifth-generation (5G) new radio (NR) for user equipment (UE) positioning, as the sensing signal. We introduce a novel algorithm to improve localization accuracy by mitigating the impact of outliers in range measurements, while also accounting for errors due to PRS range resolution. Eventually, through simulation results, we demonstrate the superiority of the proposed method over previous approaches. Indeed, we achieve up to 28% and 20% improvements in average localization error over least squares (LS) and iteratively reweighted least squares (IRLS) methods, respectively. Additionally, we observe up to 16% and 13% enhancements in the 90th percentile of localization error compared to LS and IRLS, respectively. Our simulation is based on 3rd Generation Partnership Project (3GPP) standards, ensuring the applicability of our results across diverse environments, including urban and indoor areas. |
| title | Localization Accuracy Improvement in Multistatic ISAC with LoS/NLoS Condition using 5G NR Signals |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2412.17577 |