Coordinated FMCW and OFDM for Integrated Sensing and Communication

2025-09-30

AI Summary

To address channel estimation inaccuracy and multipath interference caused by arbitrary delay channels under shared RF frontends, antennas, and spectrum in Integrated Sensing and Communication (ISAC) systems, this paper proposes an FMCW-OFDM joint waveform architecture. It overlays FMCW signals to simultaneously enable bistatic radar sensing and low-overhead channel estimation. We design two novel algorithms—Fast Cyclic Correlation Reconstruction (FCCR) and Delay-Matched Decomposition (DMD)—to achieve high-accuracy joint delay-Doppler estimation and sensing-aided channel reconstruction under arbitrary delays. The scheme further integrates cyclic correlation detection, digital mixing-based downsampling, and successive interference cancellation. Simulation results demonstrate substantial improvements over conventional separated or narrowband ISAC approaches in range/velocity resolution, channel estimation mean-square error, and bit error rate—thereby significantly enhancing the overall sensing-communication synergy.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Security and Privacy: Large-scale security measurements

Abstract

We propose a coordinated FMCW-OFDM (Co-FMCW-OFDM) system that enables integrated sensing and communication (ISAC) by allowing sensing and communication to share the same RF front end, antennas, and spectral resources. In the proposed ISAC system, the FMCW signal is superimposed on the OFDM signal and serves dual purposes: facilitating bistatic sensing and enabling channel estimation at the receiver end. Based on proposed Co-FMCW-OFDM waveform, we propose two efficient sensing algorithms-fast cyclic correlation radar (FCCR) and digital mixing and down-sampling (DMD)- which significantly reduce system complexity while accurately estimating target range and velocity. We consider a realistic channel model where delays can take any value, not just integer multiples of the sampling period. This leads to a significantly larger number of effective paths compared to the actual number of targets, which makes the sensing, channel estimation, and interference cancellation more challenging. Leveraging the sensing results, we develop a sensing-aided effective channel estimation method which effectively reconstructs the channel under arbitrary delay condition based on successive interference cancellation and propose an interference cancellation scheme that removes the FMCW signal before the OFDM demodulation. Simulation results demonstrate that the proposed system achieves superior sensing accuracy, improved channel estimation, and lower bit error rate (BER) compared to conventional OFDM systems with embedded pilots. The proposed scheme demonstrates superior BER performance in comparison to the conventional OFDM-plus-FMCW approach.

Problem

• Integrating sensing and communication using shared RF resources
• Developing efficient algorithms for target range and velocity estimation
• Enhancing channel estimation and interference cancellation under arbitrary delays

Innovation

• Coordinated FMCW-OFDM system shares RF resources
• FCCR and DMD algorithms reduce sensing complexity
• Sensing-aided channel estimation with interference cancellation