Meng, K., Han, K., Masouros, C., & Hanzo, L. (2024). Network-level ISAC: Performance Analysis and Optimal Antenna-to-BS Allocation. arXiv preprint arXiv:2410.06365.
This paper investigates the impact of different antenna-to-base station (BS) allocation strategies on the performance of cooperative integrated sensing and communication (ISAC) networks. The authors aim to determine the optimal allocation strategy that balances the benefits of centralized and distributed antenna configurations for both sensing and communication functionalities.
The authors develop a mathematical framework based on stochastic geometry to analyze the performance of cooperative ISAC networks. They consider three different target localization methods: angle-of-arrival (AOA)-based, time-of-flight (TOF)-based, and a hybrid approach combining both AOA and TOF measurements. The performance of each localization method is evaluated using the Cramér-Rao lower bound (CRLB) as a metric for accuracy. For communication performance, the authors derive a tractable expression for the data rate, considering various cooperative region sizes and antenna-to-BS allocation strategies.
The research concludes that a cooperative ISAC scheme, balancing centralized and distributed antenna allocation, effectively improves both sensing and communication performance. The optimal allocation strategy should consider factors like the number of antennas, path loss characteristics, and the chosen localization method.
This study provides valuable insights into the design and optimization of cooperative ISAC networks, particularly regarding antenna resource allocation. The findings contribute to the development of efficient and high-performance ISAC systems for future wireless networks.
The research primarily focuses on theoretical analysis using stochastic geometry. Future work could involve practical implementations and experimental validation of the proposed cooperative ISAC scheme. Additionally, exploring the impact of different channel models, user mobility, and dynamic resource allocation strategies could further enhance the analysis.
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by Kaitao Meng,... : arxiv.org 10-10-2024
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