Problem
Research questions and friction points this paper is trying to address.
Joint Communication and Sensing
Aerial Corridors
UAV Networks
Coverage Probability
Stochastic Geometry
Joint Communication and Sensing in Aerial Corridors: A Novel Stochastic Geometry Framework
🤖 AI Summary
This study addresses the challenge of analyzing joint communication and sensing (JCAS) coverage probability within unmanned aerial vehicle (UAV) network airspace corridors by proposing, for the first time, a theoretical framework based on stochastic geometry. Methodologically, a three-dimensional binomial point process is employed to model the spatial distribution of user equipment, which, in conjunction with 3GPP antenna models, enables the derivation of exact analytical expressions for JCAS coverage probability under clutter interference. This research fills a critical theoretical gap in JCAS performance analysis for airspace corridor scenarios. Furthermore, it elucidates the underlying mechanism through which highly directional antennas can significantly enhance system performance in short-corridor configurations.
📝 Abstract
In unmanned aerial vehicle (UAVs) networks, joint communication and sensing (JCAS) is emerging as a key enabler to support extended and continuous communication and sensing capabilities for sixth-generation (6G) services among UAVs operating in swarms. Within this framework, aerial corridors provide a structured environment for supporting coordinated and reliable operations. In this paper, a comprehensive frame- work is presented to investigate the JCAS coverage probability (CP) of a UAV-base station (BS) in an aerial corridor populated by UAV-user equipments (UEs). The corridor is modeled as a finite cylinder, within which a fixed number of UAV-UEs are spatially distributed according to a three-dimensional (3D) binomial point process (BPP). The UAV-BS is assumed to be equipped with a realistic 3D third generation partnership project (3GPP) antenna pattern and exploits radar sensing capabilities to track a known UAV-UE. Subsequently, the tracked UAV-UE is assumed to perform uplink communication with the UAV-BS. Accordingly, the JCAS CP at the UAV-BS is analyzed under the presence of clutter and uplink communication interference, and exact-form analytical expressions are derived. To the best of our knowledge, this is the first work to develop a stochastic geometry framework for the rigorous analysis of JCAS performance in aerial corridors, with UAV-UE locations modeled as a 3D BPP. Among several insights, results show that increasing the directivity of the UAV-BS antenna beams leads to notable JCAS performance gains, particularly for shorter UAV corridors.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Joint Communication and Sensing
Stochastic Geometry
Aerial Corridors
3D Binomial Point Process
UAV Networks
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