Backscatter Device-aided Integrated Sensing and Communication: A Pareto Optimization Framework

2025-07-12

AI Summary

In dense urban environments with severe occlusions and non-line-of-sight (NLoS) conditions, integrated sensing and communication (ISAC) performance degrades significantly. To address this, we propose a backscatter device-assisted ISAC architecture that leverages passive environmental reflectors to establish additional controllable propagation paths. We innovatively define the Pareto frontier between sensing mutual information and communication rate, unifying the fundamental sensing-communication trade-off for both bistatic and MIMO ISAC systems. Within an OFDM framework, we jointly optimize time-frequency resources, transmit power, and backscatter modulation. The resulting non-convex problem is solved via a hybrid algorithm combining block coordinate descent, successive convex approximation, augmented Lagrangian water-filling, and semidefinite relaxation. Simulation results demonstrate that the proposed scheme substantially outperforms state-of-the-art ISAC methods in both sensing accuracy and communication reliability.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search
• Security and Privacy: Large-scale security measurements

Abstract

Integrated sensing and communication (ISAC) systems potentially encounter significant performance degradation in densely obstructed urban and non-line-of-sight scenarios, thus limiting their effectiveness in practical deployments. To deal with these challenges, this paper proposes a backscatter device (BD)-assisted ISAC system, which leverages passive BDs naturally distributed in underlying environments for performance enhancement. These ambient devices can enhance sensing accuracy and communication reliability by providing additional reflective signal paths. In this system, we define the Pareto boundary characterizing the trade-off between sensing mutual information (SMI) and communication rates to provide fundamental insights for its design. To derive the boundary, we formulate a performance optimization problem within an orthogonal frequency division multiplexing (OFDM) framework, by jointly optimizing time-frequency resource element (RE) allocation, transmit power management, and BD modulation decisions. To tackle the non-convexity of the problem, we decompose it into three subproblems, solved iteratively through a block coordinate descent (BCD) algorithm. Specifically, the RE subproblem is addressed using the successive convex approximation (SCA) method, the power subproblem is solved using an augmented Lagrangian combined water-filling method, and the BD modulation subproblem is tackled using semidefinite relaxation (SDR) methods. Additionally, we demonstrate the generality of the proposed system by showing its adaptability to bistatic ISAC scenarios and MIMO settings. Finally, extensive simulation results validate the effectiveness of the proposed system and its superior performance compared to existing state-of-the-art ISAC schemes.

Problem

• Enhance ISAC performance in obstructed urban scenarios
• Optimize sensing-communication trade-off via Pareto boundary
• Jointly manage resources, power, and BD modulation

Innovation

• Backscatter devices enhance ISAC performance passively
• Pareto optimization balances sensing and communication
• BCD algorithm solves non-convex optimization subproblems