Resource Allocation and AoI-Aware Detection for ISAC with Stacked Intelligent Metasurfaces

TL;DR

This paper proposes an energy-efficient resource allocation framework for SIM-assisted ISAC systems, optimizing beampattern synthesis, interference management, and QoS for communication and sensing, with significant EE improvements.

Contribution

It introduces a novel two-timescale optimization approach for resource allocation in SIM-aided ISAC, addressing joint communication and sensing requirements with low complexity.

Findings

Achieves up to 230% EE improvement over baseline

Requires fewer transmit antennas while maintaining QoS

Reveals trade-offs between EE and heterogeneous QoS

Abstract

Stacked intelligent metasurfaces (SIMs) provide wave-domain degrees of freedom that can empower integrated sensing and communication (ISAC) through flexible beampattern synthesis and interference management, while reducing hardware cost. In this paper, we investigate energy-efficient resource allocation for a downlink SIM-aided multi-user ISAC system that supports the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) via puncturing, while simultaneously illuminating sensing targets. We formulate an energy efficiency (EE) maximization problem that jointly optimizes resource block (RB) allocation, transmit power control, and SIM phase shifts. The formulated problem is highly challenging due to the large number of variables optimized on different time scales. To overcome this, we leverage the intrinsic two-timescale structure induced by the puncturing approach to decompose the original problem into two tractable subproblems: EE maximization for eMBB users in each time slot and EE maximization for URLLC users and sensing targets in each mini-slot. To address each subproblem, we develop an iterative algorithm that transforms the original non-convex formulation into a sequence of tractable subproblems, yielding convex updates for RB allocation and power control, along with low-complexity updates for SIM phase shifts. Simulation results show that the proposed design achieves up to 230% improvement in EE over a No-SIM baseline. In addition, it requires significantly fewer transmit antennas than conventional BS architectures, while preserving the EE achieved and satisfying the communication and sensing quality of service (QoS) requirements. Moreover, the results reveal fundamental trade-offs between EE and heterogeneous QoS requirements across communication and sensing functionalities.