Fundamental Limits of Bistatic Integrated Sensing and Communications over Memoryless Relay Channels

2025-07-12

AI Summary

This work investigates the fundamental performance limits of bistatic integrated sensing and communication (ISAC) over memoryless relay channels, where the destination simultaneously decodes messages and estimates unknown channel parameters under synchronization constraints. To accomplish this joint task, we propose a hybrid coding scheme combining partial decode-forward and compress-forward strategies. We extend the classical cut-set bound to ISAC-enabled relay systems for the first time and establish tight inner and outer bounds on the joint communication-sensing trade-off across three canonical relay channel models. Leveraging a state-dependent discrete memoryless channel framework, we rigorously characterize the fundamental rate–distortion trade-off between communication rate and parameter estimation distortion using capacity–distortion theory and joint code design. Numerical results demonstrate that the proposed joint design significantly outperforms conventional separation-based approaches, achieving simultaneous gains in both estimation accuracy and communication efficiency.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Intelligent Robots: State Estimation
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

Abstract

The problem of bistatic integrated sensing and communications over memoryless relay channels is considered, where destination concurrently decodes the message sent by the source and estimates unknown parameters from received signals with the help of a relay. A state-dependent discrete memoryless relay channel is considered to model this setup, and the fundamental limits of the communication-sensing performance tradeoff are characterized by the capacity-distortion function. An upper bound on the capacity-distortion function is derived, extending the cut-set bound results to address the sensing operation at the destination. A hybrid-partial-decode-and-compress-forward coding scheme is also proposed to facilitate source-relay cooperation for both message transmission and sensing, establishing a lower bound on the capacity-distortion function. It is found that the hybrid-partial-decode-and-compress-forward scheme achieves optimal sensing performance when the communication task is ignored. Furthermore, the upper and lower bounds are shown to coincide for three specific classes of relay channels. Numerical examples are provided to illustrate the communication-sensing tradeoff and demonstrate the benefits of integrated design.

Problem

• Characterize communication-sensing tradeoff in bistatic relay channels
• Derive bounds on capacity-distortion for integrated sensing-communication
• Evaluate hybrid coding for optimal sensing and communication

Innovation

• Hybrid-partial-decode-and-compress-forward coding scheme
• Capacity-distortion function characterizes performance tradeoff
• Cut-set bound extended for sensing operation