Toward Multi-Functional LAWNs with ISAC: Opportunities, Challenges, and the Road Ahead
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866909751012491264 |
|---|---|
| author | Wu, Jun Yuan, Weijie Zhang, Xiaoqi Yu, Yaohuan Cui, Yuanhao Liu, Fan Sun, Geng Wang, Jiacheng Niyato, Dusit Kim, Dong In |
| author_facet | Wu, Jun Yuan, Weijie Zhang, Xiaoqi Yu, Yaohuan Cui, Yuanhao Liu, Fan Sun, Geng Wang, Jiacheng Niyato, Dusit Kim, Dong In |
| contents | Integrated sensing and communication (ISAC) has been envisioned as a foundational technology for future low-altitude wireless networks (LAWNs), enabling real-time environmental perception and data exchange across aerial-ground systems. In this article, we first explore the roles of ISAC in LAWNs from both node-level and network-level perspectives. We highlight the performance gains achieved through hierarchical integration and cooperation, wherein key design trade-offs are demonstrated. Apart from physical-layer enhancements, emerging LAWN applications demand broader functionalities. To this end, we propose a multi-functional LAWN framework that extends ISAC with capabilities in control, computation, wireless power transfer, and large language model (LLM)-based intelligence. We further provide a representative case study to present the benefits of ISAC-enabled LAWNs and the promising research directions are finally outlined. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_17354 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Toward Multi-Functional LAWNs with ISAC: Opportunities, Challenges, and the Road Ahead Wu, Jun Yuan, Weijie Zhang, Xiaoqi Yu, Yaohuan Cui, Yuanhao Liu, Fan Sun, Geng Wang, Jiacheng Niyato, Dusit Kim, Dong In Signal Processing Integrated sensing and communication (ISAC) has been envisioned as a foundational technology for future low-altitude wireless networks (LAWNs), enabling real-time environmental perception and data exchange across aerial-ground systems. In this article, we first explore the roles of ISAC in LAWNs from both node-level and network-level perspectives. We highlight the performance gains achieved through hierarchical integration and cooperation, wherein key design trade-offs are demonstrated. Apart from physical-layer enhancements, emerging LAWN applications demand broader functionalities. To this end, we propose a multi-functional LAWN framework that extends ISAC with capabilities in control, computation, wireless power transfer, and large language model (LLM)-based intelligence. We further provide a representative case study to present the benefits of ISAC-enabled LAWNs and the promising research directions are finally outlined. |
| title | Toward Multi-Functional LAWNs with ISAC: Opportunities, Challenges, and the Road Ahead |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.17354 |