Network Integrated Sensing and Communication

TL;DR

This work develops a network-level ISAC framework that couples multi-node routing with spatial sensing, formalizing the sensing--throughput region $R$ under a per-link linear trade-off between communication and sensing. It provides a complete analytical characterization for a one-dimensional path network, showing the maximum throughput $f^*=\min_{u\in U} c_u$ and a closed-form boundary $s=\sum_{u\in U(A)} c_u-|U(A)|\,f$, with a linear Pareto trade-off slope of $-1/|U(A)|$. For general networks, the paper proves convexity of $R$, derives the structure of the Pareto boundary as piecewise-linear with slopes $-1/k_i$ determined by the routing-sensing interaction, and offers a practical framework (via LPs like $\mathcal{P}_1$) to compute the boundary and the optimal routing that balances sensing coverage and communication throughput. The results illuminate fundamental trade-offs between sensing coverage and routing, providing fundamental design insights for 6G heterogeneous networks and guiding network deployments that simultaneously support high-rate communication and spatial sensing.

Abstract

Integrated sensing and communication (ISAC) is a cornerstone technology for 6G networks, offering unified support for high-rate communication and high-accuracy sensing. While existing literature extensively covers link-level designs, the transition toward large-scale deployment necessitates a fundamental understanding of network-level performance. This paper investigates a network ISAC model where a source node communicates with a destination via a relay network, while intermediate nodes concurrently perform cooperative sensing over specific spatial regions. We formulate a novel optimization framework that captures the interplay between multi-node routing and sensing coverage. For a one-dimensional path network, we provide an analytical characterization of the complete sensing-throughput region. Extending this to general network topologies, we establish that the sensing-throughput Pareto boundary is piecewise linear and provide physical interpretations for each segment. Our results reveal the fundamental trade-offs between sensing coverage and communication routing, offering key insights for the design of future 6G heterogeneous networks.

Figures (10)

• Figure 1: A one-dimensional ISAC network
• Figure 2: The sensing-throughput region of the one-dimensional ISAC network
• Figure 3: Subfigure (a) shows a one-dimensional ISAC network example. Subfigures (b)--(d) shows different operating points, where the green boxes represent communication rates, and blue boxes, sensing rates.
• Figure 4: The sensing--throughput region of the network in Figure \ref{['fig:1D-example-rates']}
• Figure 5: The structure of the sensing--throughput region for the general ISAC network.

Theorems & Definitions (22)

• Remark 1
• Lemma 1
• Lemma 2
• Lemma 3
• Lemma 4
• Lemma 5
• Lemma 6
• Lemma 7
• Lemma 8
• Remark 2