Multipath Component-Enhanced Signal Processing for Integrated Sensing and Communication Systems
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908399427387392 |
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| author | Liu, Haotian Wei, Zhiqing Wang, Xiyang Wu, Huici Liu, Fan Li, Xingwang Feng, Zhiyong |
| author_facet | Liu, Haotian Wei, Zhiqing Wang, Xiyang Wu, Huici Liu, Fan Li, Xingwang Feng, Zhiyong |
| contents | Integrated sensing and communication (ISAC) has gained traction in academia and industry. Recently, multipath components (MPCs), as a type of spatial resource, have the potential to improve the sensing performance in ISAC systems, especially in richly scattering environments. In this paper, we propose to leverage MPC and Khatri-Rao space-time (KRST) code within a single ISAC system to realize high-accuracy sensing for multiple dynamic targets and multi-user communication. Specifically, we propose a novel MPC-enhanced sensing processing scheme with symbol-level fusion, referred to as the "SL-MPS" scheme, to achieve high-accuracy localization of multiple dynamic targets and empower the single ISAC system with a new capability of absolute velocity estimation for multiple targets with a single sensing attempt. Furthermore, the KRST code is applied to flexibly balance communication and sensing performance in richly scattering environments. To evaluate the contribution of MPCs, the closed-form Cramér-Rao lower bounds (CRLBs) of location and absolute velocity estimation are derived. Simulation results illustrate that the proposed SL-MPS scheme is more robust and accurate in localization and absolute velocity estimation compared with the existing state-of-the-art schemes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_07495 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multipath Component-Enhanced Signal Processing for Integrated Sensing and Communication Systems Liu, Haotian Wei, Zhiqing Wang, Xiyang Wu, Huici Liu, Fan Li, Xingwang Feng, Zhiyong Signal Processing Integrated sensing and communication (ISAC) has gained traction in academia and industry. Recently, multipath components (MPCs), as a type of spatial resource, have the potential to improve the sensing performance in ISAC systems, especially in richly scattering environments. In this paper, we propose to leverage MPC and Khatri-Rao space-time (KRST) code within a single ISAC system to realize high-accuracy sensing for multiple dynamic targets and multi-user communication. Specifically, we propose a novel MPC-enhanced sensing processing scheme with symbol-level fusion, referred to as the "SL-MPS" scheme, to achieve high-accuracy localization of multiple dynamic targets and empower the single ISAC system with a new capability of absolute velocity estimation for multiple targets with a single sensing attempt. Furthermore, the KRST code is applied to flexibly balance communication and sensing performance in richly scattering environments. To evaluate the contribution of MPCs, the closed-form Cramér-Rao lower bounds (CRLBs) of location and absolute velocity estimation are derived. Simulation results illustrate that the proposed SL-MPS scheme is more robust and accurate in localization and absolute velocity estimation compared with the existing state-of-the-art schemes. |
| title | Multipath Component-Enhanced Signal Processing for Integrated Sensing and Communication Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2506.07495 |