OFDM Waveform Optimization for Bistatic Integrated Sensing and Communications

2026-03-09

AI Summary

This work addresses the waveform design challenge in dual-functional integrated sensing and communication (ISAC) systems employing OFDM by jointly optimizing subcarrier allocation and power distribution to balance communication rate and sensing accuracy. The study reveals that communication performance hinges on the number of allocated subcarriers, while sensing precision—particularly delay estimation—depends critically on their spatial distribution. To this end, the authors propose a subcarrier allocation criterion based on the trade-off between Fisher information gain for sensing and communication rate loss, along with a bounded water-filling power allocation structure. A joint path coefficient and delay estimation scheme is further developed to guide waveform optimization. By leveraging quadratic transformation and Lagrangian dual decomposition, closed-form iterative updates for the optimization variables are derived. Experimental results demonstrate that the proposed method significantly outperforms existing baselines in both delay estimation accuracy and achievable communication rate.

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

This paper investigates the design of orthogonal frequency-division multiplexing (OFDM) waveforms for bistatic integrated sensing and communication (ISAC) systems. In the considered framework, an ISAC transmitter jointly optimizes subcarrier assignment and power allocation for a single OFDM waveform that simultaneously supports communication and sensing functionalities. Meanwhile, an ISAC receiver decodes information on communication subcarriers and estimates per-path propagation delays via exploiting pilot symbols on sensing subcarriers. We propose a joint path coefficient and delay estimation (JPCDE) scheme, revealing that the achievable communication data rate (CDR) is determined by the number of communication subcarriers, whereas the delay sensing accuracy is governed by the index distribution of sensing subcarriers. Building on this insight, we formulate an OFDM waveform optimization problem to maximize the CDR subject to sensing-accuracy and power-budget constraints. To solve this problem, we employ a quadratic transform and Lagrangian dual decomposition, which iteratively updates the subcarrier assignment and power allocation variables in closed-form. Our results reveal that a subcarrier is allocated for sensing if and only if its Fisher information gain exceeds the corresponding communication rate loss, while the power allocation for communication subcarriers exhibits a bounded water-filling structure. Simulation results demonstrate that the proposed frameworks substantially outperform existing baselines in both delay estimation accuracy and CDR.

Problem

• OFDM
• bistatic ISAC
• waveform optimization
• sensing accuracy
• communication data rate

Innovation

• OFDM waveform optimization
• bistatic ISAC
• joint subcarrier and power allocation
• delay estimation
• Fisher information