PHY2 – Integrated Communications and Sensing
Wednesday, 4 June 2025, 16:00-17:30, room 1.E
Session Chair: Markku Juntti (University of Oulu, FI)
Performance Analysis of Multi-Target ISAC System Based on Kullback-Leibler Divergence
Yousef Kloob and Mohammad Ahmad Al-Jarrah, Sr. (University of Manchester, United Kingdom (Great Britain)); Emad Alsusa (Manchester University, United Kingdom (Great Britain))
This paper proposes a novel framework based on the Kullback-Leibler divergence (KLD) to quantify and analyse the performance trade-off between sensing and communication subsystems in an integrated sensing and communication (ISAC) system. We consider a multiple-input-multiple-output (MIMO) base station (BS) that simultaneously serves communication user equipments (UEs) and detects multiple targets using shared antenna deployment. The zero-forcing (ZF) and the conventional identity covariance based beamforming are employed for the communication and the radar subsystems, respectively. Our framework exploits the inherent communication signals alongside dedicated radar signals for target detection, enhancing radar performance through this dual-use approach. The proposed KLD-based approach provides a unified performance measure that encompasses both the UE error rate and the target detection capability. Through theoretical derivations and simulations for both subsystems and beamforming techniques, we demonstrate the accuracy of the derived KLD in characterizing the performance trade-off under various system configurations. The findings of this study facilitate the holistic design of ISAC systems for next-generation wireless networks, offering insights into optimizing the balance between sensing and communication capabilities.
RIS-Aided Radar Imaging Utilizing the Virtual Source Principle
Furkan Ilgac (Ruhr-University Bochum, Germany); Aydin Sezgin (RUB, Germany); Mounia Bouabdellah (Ruhr University of Bochum, Germany)
Synthetic Aperture Radar (SAR) is widely employed to generate radar images of large scenes by mechanically moving the antenna platform across or around the scene. However, at higher frequencies, such as terahertz (THz) domain, this approach becomes increasingly challenging, as motion errors as small as a few millimeters are directly translated into imaging errors. In this paper, we propose leveraging Reconfigurable Intelligent Surfaces (RIS) as a smart medium to synthesize a virtual source image that can be steered around the scene. This eliminates the need for platform motion, enabling radar imaging with even a static single-antenna system. Within this framework, the radar imaging process is redefined as a virtual source imaging problem and modeled in the wavenumber domain. Furthermore, image formation algorithms are developed for both near-field and far-field scenarios.
Joint Delay-Doppler Estimation Using OFDMA Payloads for Integrated Communications and Sensing
Marc Miranda (TU Ilmenau, Germany); Sebastian Semper, Christian Schneider and Reiner S. Thomä (Technische Universität Ilmenau, Germany); Giovanni Del Galdo (Fraunhofer Institute for Integrated Circuits IIS & Technische Universität Ilmenau, Germany)
The use of future communication systems for sensing offers the potential for a number of new applications. In this paper, we show that leveraging user data payloads in multi-node Orthogonal Frequency Division Multiple Access (OFDMA) networks for estimating target delay and Doppler-shift parameters can yield a significant advantage in SNR and addressable bandwidth. However, gaps in the frequency-time resources, reference signal boosting and amplitude modulation schemes introduce challenges for estimation at the sensing receiver.
In this work, we propose a joint delay and Doppler-shift model-based estimator designed to address these challenges. Furthermore, we demonstrate that incorporating knowledge of the device model into the estimation procedure helps mitigate the effects of the non-ideal radar ambiguity function caused by amplitude-modulated user payloads and sparse reference signals. Simulation results demonstrate that the estimator achieves the theoretical lower bound on estimation variance.
Distributed Intelligent Sensing and Communications for 6G: Architecture and Use Cases
Kyriakos Stylianopoulos (University of Athens, Greece); Giyyarpuram Madhusudan (Orange Labs, France); Guillaume Jornod (Robert Bosch GmbH, Germany); Sami Mekki (Nokia Networks France, France); Francesca Costanzo (CEA Leti, France); Hui Chen (Chalmers University of Technology, Sweden); Placido Mursia (NEC Laboratories Europe GmbH, Germany); Maurizio Crozzoli (Telecom Italia, Italy); Emilio Calvanese Strinati (CEA-LETI, France); George C. Alexandropoulos (University of Athens & University of Illinois Chicago, Greece); Henk Wymeersch (Chalmers University of Technology, Sweden)
The Distributed Intelligent Sensing and Communication (DISAC) framework redefines Integrated Sensing and Communication (ISAC) for 6G by leveraging distributed architectures to enhance scalability, adaptability, and resource efficiency. This paper presents key architectural enablers, including advanced data representation, seamless target handover, support for heterogeneous devices, and semantic integration. Two use cases illustrate the transformative potential of DISAC: smart factory shop floors and Vulnerable Road User (VRU) protection at smart intersections. These scenarios demonstrate significant improvements in precision, safety, and operational efficiency compared to traditional ISAC systems. The preliminary DISAC architecture incorporates intelligent data processing, distributed coordination, and emerging technologies such as Reconfigurable Intelligent Surfaces (RIS) to meet 6G’s stringent requirements. By addressing critical challenges in sensing accuracy, latency, and real-time decision-making, DISAC positions itself as a cornerstone for next-generation wireless networks, advancing innovation in dynamic and complex environments.
Optimal Detector with Correlated RF Source Signal in Ambient Backscatter Communication Systems
Anuranjan Jha, Vidhi Desai and Adarsh Patel (IIT Mandi, India)
This paper considers an ambient backscatter communication (AmBC) system with a generalized ambient radio frequency (RF) source signal, i.e., allowing correlated ambient RF source signal samples. A Neyman-Pearson (NP) criterion based optimal detector statistic for a correlated RF source signal in the AmBC system is obtained. To further analyze the detection performance of the proposed optimal detector, closed-form expressions of the probability of detection and probability of false alarm are derived. Simulation comparisons illustrate the proposed optimal detector’s superior receiver operating characteristics (ROC) performance over the state-of-the-art detectors under the considered framework. Further, the simulation section demonstrates the ROC equivalence of the simulation performance with the derived analytical expressions of the proposed detector.
