Detecting Unauthorized Drones with Cell-Free Integrated Sensing and Communication
Xinyue Li, Zinat Behdad, Ozan Alp Topal, Ozlem Tugfe Demir, and Cicek, Cavdar

TL;DR
This paper introduces a cell-free massive MIMO-ISAC framework for detecting unauthorized drones, optimizing sensing and communication trade-offs to improve timeliness and coverage.
Contribution
It proposes a novel joint sensing blocklength and power optimization algorithm along with an adaptive weight selection method for enhanced drone detection performance.
Findings
Increasing communication requirements reduces sensing coverage and timeliness.
The adaptive weight algorithm reduces AoS by 45% compared to fixed weights.
The framework effectively balances sensing accuracy and communication needs.
Abstract
Integrated sensing and communication (ISAC) boosts network efficiency by using existing resources for diverse sensing applications. In this work, we propose a cell-free massive MIMO (multiple-input multiple-output)-ISAC framework to detect unauthorized drones while simultaneously ensuring communication requirements. We develop a detector to identify passive aerial targets by analyzing signals from distributed access points (APs). In addition to the precision of the sensing, timeliness of the sensing information is also crucial due to the risk of drones leaving the area before the sensing procedure is finished. We introduce the age of sensing (AoS) and sensing coverage as our sensing performance metrics and propose a joint sensing blocklength and power optimization algorithm to minimize AoS and maximize sensing coverage while meeting communication requirements. Moreover, we propose an…
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Taxonomy
TopicsMolecular Communication and Nanonetworks · Wireless Communication Security Techniques · SARS-CoV-2 and COVID-19 Research
