Cooperative Multi-Satellite ISAC Networks: Centralized vs. Distributed Sensing
Jeongbin Kim, Jaehong Jo, Seunghyeon Jeon, Wonjae Shin, Yo-Seb Jeon, and H. Vincent Poor

TL;DR
This paper explores cooperative sensing in multi-satellite ISAC networks, proposing centralized and distributed frameworks that improve target localization accuracy while balancing communication and sensing performance.
Contribution
It introduces novel centralized and distributed sensing frameworks with optimized beamforming and data association for multi-satellite ISAC systems.
Findings
Both frameworks outperform existing sensing schemes.
Distributed framework reduces signaling overhead.
Trade-offs between sensing accuracy and power consumption are analyzed.
Abstract
This paper investigates a downlink multi-satellite integrated sensing and communication (ISAC) network, in which multiple satellites simultaneously transmit ISAC signals to provide communication services to ground user equipments and enable cooperative sensing of airborne targets through multiple gateways. To support this dual functionality, we introduce communication and sensing beamforming designs based on uniform planar arrays with optimized power allocation. Building on these designs, we propose two cooperative sensing frameworks, namely centralized and distributed. In the centralized framework, each gateway forwards its sensing observations to a central unit (CU), where the positions of multiple targets are jointly estimated from the aggregated data using a sparse signal recovery formulation. To mitigate the signaling overhead inherent in centralized processing, a distributed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSatellite Communication Systems · Radar Systems and Signal Processing · Distributed Sensor Networks and Detection Algorithms
