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Performance Analysis of Integrated Sensing and Communication Networks with Blockage Effects

Zezhong Sun, Shi Yan, Ning Jiang, Jiaen Zhou, Mugen Peng

TL;DR

This work analyzes Integrated Sensing and Communication (ISAC) networks in urban settings where blockages from buildings shape signal propagation. It develops a distance-dependent blockage model that jointly captures LoS, NLoS, and target-reflection paths within a stochastic-geometry framework, and derives SINR-based coverage probabilities for both communication and sensing. The main contributions include a unified analytical framework with tractable special cases, semi-closed-form results for key regimes, and simulations that reveal an optimal base-station density and the potential positive impact of blockages on coverage. The results provide practical guidance for designing ISAC deployments in dense urban environments by illustrating how blockage structure and BS density interact to determine performance.

Abstract

Communication-sensing integration represents an up-and-coming area of research, enabling wireless networks to simultaneously perform communication and sensing tasks. However, in urban cellular networks, the blockage of buildings results in a complex signal propagation environment, affecting the performance analysis of integrated sensing and communication (ISAC) networks. To overcome this obstacle, this paper constructs a comprehensive framework considering building blockage and employs a distance-correlated blockage model to analyze interference from line of sight (LoS), non-line of sight (NLoS), and target reflection cascading (TRC) links. Using stochastic geometric theory, expressions for signal-to-interference-plus-noise ratio (SINR) and coverage probability for communication and sensing in the presence of blockage are derived, allowing for a comprehensive comparison under the same parameters. The research findings indicate that blockage can positively impact coverage, especially in enhancing communication performance. The analysis also suggests that there exists an optimal base station (BS) density when blockage is of the same order of magnitude as the BS density, maximizing communication or sensing coverage probability.

Performance Analysis of Integrated Sensing and Communication Networks with Blockage Effects

TL;DR

This work analyzes Integrated Sensing and Communication (ISAC) networks in urban settings where blockages from buildings shape signal propagation. It develops a distance-dependent blockage model that jointly captures LoS, NLoS, and target-reflection paths within a stochastic-geometry framework, and derives SINR-based coverage probabilities for both communication and sensing. The main contributions include a unified analytical framework with tractable special cases, semi-closed-form results for key regimes, and simulations that reveal an optimal base-station density and the potential positive impact of blockages on coverage. The results provide practical guidance for designing ISAC deployments in dense urban environments by illustrating how blockage structure and BS density interact to determine performance.

Abstract

Communication-sensing integration represents an up-and-coming area of research, enabling wireless networks to simultaneously perform communication and sensing tasks. However, in urban cellular networks, the blockage of buildings results in a complex signal propagation environment, affecting the performance analysis of integrated sensing and communication (ISAC) networks. To overcome this obstacle, this paper constructs a comprehensive framework considering building blockage and employs a distance-correlated blockage model to analyze interference from line of sight (LoS), non-line of sight (NLoS), and target reflection cascading (TRC) links. Using stochastic geometric theory, expressions for signal-to-interference-plus-noise ratio (SINR) and coverage probability for communication and sensing in the presence of blockage are derived, allowing for a comprehensive comparison under the same parameters. The research findings indicate that blockage can positively impact coverage, especially in enhancing communication performance. The analysis also suggests that there exists an optimal base station (BS) density when blockage is of the same order of magnitude as the BS density, maximizing communication or sensing coverage probability.
Paper Structure (21 sections, 2 theorems, 65 equations, 7 figures, 3 tables)

This paper contains 21 sections, 2 theorems, 65 equations, 7 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background and Motivations
  3. Related Works
  4. Our Contributions
  5. Outline of the Paper
  6. System Model
  7. Path Loss and Blockage Model
  8. Desired Signal Model
  9. Interference Model
  10. Small-scale Fading Model
  11. Performance Metrics
  12. Performance Analysis
  13. Communication Coverage Probability
  14. Sensing Coverage Probability
  15. Simulation Results and Analysis
  16. ...and 6 more sections

Key Result

Theorem 1

For specific detection threshold $T_\mathrm{comm}$, LoS and NLoS path loss exponents $\alpha_L$ and $\alpha_N$, and blockage parameters $p$ and $\beta$, the communication coverage probability, $p_{\mathrm{c}}^{\mathrm{comm}}(T^{\mathrm{ comm}},\lambda_{\mathrm{bs}},\alpha_L,\alpha_N,\beta ,p)$, can where

Figures (7)

  • Figure 1: Schematic diagram of the considered system model.
  • Figure 2: Variation of sensing coverage probability with detection threshold for different ST's RCS and comparison with that under communication coverage probability with the same parameters.
  • Figure 3: Variation of communication coverage probability with detection threshold for different BS deployment densities.
  • Figure 4: Variation of sensing coverage probability with detection threshold for different BS deployment densities.
  • Figure 5: Variation of coverage probability with BS deployment density for different detection thresholds.
  • ...and 2 more figures

Theorems & Definitions (2)

  • Theorem 1
  • Theorem 2