English

Coverage and Rate Analysis for Integrated Sensing and Communication Networks

Information Theory 2024-03-25 v2 Signal Processing math.IT

Abstract

Integrated sensing and communication (ISAC) is increasingly recognized as a pivotal technology for next-generation cellular networks, offering mutual benefits in both sensing and communication capabilities. This advancement necessitates a re-examination of the fundamental limits within networks where these two functions coexist via shared spectrum and infrastructures. However, traditional stochastic geometry-based performance analyses are confined to either communication or sensing networks separately. This paper bridges this gap by introducing a generalized stochastic geometry framework in ISAC networks. Based on this framework, we define and calculate the coverage and ergodic rate of sensing and communication performance under resource constraints. Then, we shed light on the fundamental limits of ISAC networks by presenting theoretical results for the coverage rate of the unified performance, taking into account the coupling effects of dual functions in coexistence networks. Further, we obtain the analytical formulations for evaluating the ergodic sensing rate constrained by the maximum communication rate, and the ergodic communication rate constrained by the maximum sensing rate. Extensive numerical results validate the accuracy of all theoretical derivations, and also indicate that denser networks significantly enhance ISAC coverage. Specifically, increasing the base station density from 11 km2\text{km}^{-2} to 1010 km2\text{km}^{-2} can boost the ISAC coverage rate from 1.4%1.4\% to 39.8%39.8\%. Further, results also reveal that with the increase of the constrained sensing rate, the ergodic communication rate improves significantly, but the reverse is not obvious.

Keywords

Cite

@article{arxiv.2403.08343,
  title  = {Coverage and Rate Analysis for Integrated Sensing and Communication Networks},
  author = {Xu Gan and Chongwen Huang and Zhaohui Yang and Xiaoming Chen and Jiguang He and Zhaoyang Zhang and Chau Yuen and Yong Liang Guan and Mérouane Debbah},
  journal= {arXiv preprint arXiv:2403.08343},
  year   = {2024}
}
R2 v1 2026-06-28T15:18:25.222Z