Cooperative Sensing and Communication for ISAC Networks: Performance Analysis and Optimization

TL;DR

The paper addresses network-level ISAC by integrating CoMP transmission and distributed radar within a stochastic-geometry framework to analyze the balance between sensing and communication. It introduces a cooperative ISAC architecture with dynamic clustering, derives tractable metrics for CRLB-based sensing performance and rate-based communication performance, and reveals a $\ln^2 N$ scaling law for localization accuracy as the number of cooperative transceivers grows. Through closed-form approximations and simulations, it shows that larger backhaul capacity and optimized cluster sizes can significantly enhance both sensing accuracy and data rates compared with time-sharing. These results provide practical guidelines for designing scalable ISAC networks with cooperative sensing and communication under backhaul and resource constraints.

Abstract

In this work, we study integrated sensing and communication (ISAC) networks intending to effectively balance sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose a cooperative networked ISAC scheme to enhance both S&C services. Then, the tool of stochastic geometry is exploited to capture the S&C performance, which allows us to illuminate key cooperative dependencies in the ISAC network. Remarkably, the derived expression of the Cramer-Rao lower bound (CRLB) of the localization accuracy unveils a significant finding: Deploying $N$ ISAC transceivers yields an enhanced sensing performance across the entire network, in accordance with the $\ln^2N$ scaling law. Simulation results demonstrate that compared to the time-sharing scheme, the proposed cooperative ISAC scheme can effectively improve the average data rate and reduce the CRLB.

Figures (5)

• Figure 1: Illustration of cooperative S&C networks.
• Figure 2: CRLB value comparison with $\kappa_c = 1$.
• Figure 3: CRLB value with the acceptance probability.
• Figure 4: Cooperative communication performance.
• Figure 5: Performance tradeoff versus different backhaul capacity constraints.