Resource Allocation for ISAC Networks with Application to Target Tracking

TL;DR

This paper proposes a joint resource allocation framework for integrated sensing and communication (ISAC) networks in 6G, optimizing target tracking and communication throughput through a novel non-convex problem solution.

Contribution

It introduces a comprehensive optimization model for resource allocation in ISAC systems that accounts for target movement and channel variations, with a new algorithm to solve it.

Findings

The proposed algorithm effectively balances sensing and communication performance.

Simulation results validate the optimization approach and demonstrate its efficiency.

Trade-offs between sensing accuracy and communication throughput are characterized.

Abstract

Future 6G networks are expected to empower communication systems by integrating sensing capabilities, resulting in integrated sensing and communication (ISAC) systems. However, this integration may exacerbate the data traffic congestion in existing communication systems due to limited resources. Therefore, the resources of ISAC systems must be carefully allocated to ensure high performance. Given the increasing demands for both sensing and communication services, current methods are inadequate for tracking targets frequently in every frame while simultaneously communicating with users. To address this gap, this work formulates an optimization problem that jointly allocates resources in the time, frequency, power, and spatial domains for targets and users, accounting for the movement of targets and time-varying communication channels. Specifically, we minimize the trace of posterior Cram\'er-Rao bound for target tracking subject to communication throughput and resource allocation constraints. To solve this non-convex problem, we develop a block coordinate descent (BCD) algorithm based on the penalty method, successive convex approximation (SCA), and one-dimensional search. Simulation results demonstrate the validity of the proposed algorithm and the performance trade-off between sensing and communication.