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On the Performance Trade-off of Distributed Integrated Sensing and Communication Networks

Xuran Li, Shuaishuai Guo, Tuo Li, Xiaofeng Zou, Dengwang Li

TL;DR

This letter analyzes the performance trade-off in distributed integrated sensing and communication (ISAC) networks with the aid of stochastic geometry theory and derives the probability of detection of that of the coverage given user number.

Abstract

In this letter, we analyze the performance trade-off in distributed integrated sensing and communication (ISAC) networks. Specifically, with the aid of stochastic geometry theory, we derive the probability of detection of that of the coverage given user number. Based on the analytical derivations, we provide a quantitative description of the performance limits and the performance trade-off between sensing and communication in a distributed ISAC network under the given transmit power and bandwidth budget. Extensive simulations are conducted and the numerical results validate the accuracy of our derivations.

On the Performance Trade-off of Distributed Integrated Sensing and Communication Networks

TL;DR

This letter analyzes the performance trade-off in distributed integrated sensing and communication (ISAC) networks with the aid of stochastic geometry theory and derives the probability of detection of that of the coverage given user number.

Abstract

In this letter, we analyze the performance trade-off in distributed integrated sensing and communication (ISAC) networks. Specifically, with the aid of stochastic geometry theory, we derive the probability of detection of that of the coverage given user number. Based on the analytical derivations, we provide a quantitative description of the performance limits and the performance trade-off between sensing and communication in a distributed ISAC network under the given transmit power and bandwidth budget. Extensive simulations are conducted and the numerical results validate the accuracy of our derivations.
Paper Structure (11 sections, 2 theorems, 17 equations, 5 figures, 1 table)

This paper contains 11 sections, 2 theorems, 17 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. System model
  3. Network Model
  4. Channel Model
  5. Performance Analysis Model
  6. Performance Analysis
  7. Sensing Performance Analysis
  8. Communication Performance Analysis
  9. Performance Trade-off Analysis
  10. Simulations and Discussions
  11. Conclusion

Key Result

Theorem 1

The probability of detection $P_D$ in the ISAC network can be expressed by where $\eta=\frac{\gamma_s (4 \pi)^3}{p_s G_t G_r \lambda_w^2}$ and $\gamma_s= \frac{ 2^{ \frac{2 T \zeta_s}{\delta} } -1 }{2 T B_s}$.

Figures (5)

  • Figure 1: An ISAC Network.
  • Figure 2: Probability of detection $P_D$ varies with threshold value $\gamma_s$.
  • Figure 3: Probability of detection $P_D$ varies with transmit power $p_s$.
  • Figure 4: Performance trade-off of the ISAC network between the communication and sensing under power allocation.
  • Figure 5: Performance trade-off of the ISAC network between the communication and sensing under bandwidth allocation.

Theorems & Definitions (4)

  • Theorem 1
  • proof
  • Theorem 2
  • proof