VTC 2025 Spring Conference’s Shorts

Cooperative Dual-Mode OFDM Index Modulation based Downlink Multi-User NOMA System

To fulfil the demand for high energy and spectral efficiency (SE) while serving multiple users concurrently for next-generation 6G systems, both non-orthogonal multiple access (NOMA) and orthogonal frequency division multiplexing (OFDM) aided index modulation (IM) endorse the requirements. NOMA serves several users concurrently while sharing the frequency and time resources. In addition, the single-mode OFDM-IM system improves the SE by broadcasting the additional bits of active subcarrier selection. Meanwhile, dual-mode OFDM-IM relatively enhances the SE via transmitting different constellation sets over a subblock OFDM vector. Furthermore, broadcasting the baseband NOMA symbols over a dual-mode OFDM-IM scheme improves the SE compared to the conventional IM schemes. This paper describes a dual-mode aided cooperative relaying OFDM-IM-based downlink hybrid NOMA system serving multiple users simultaneously. The Monte Carlo simulation results demonstrate that the bit error rate (BER) performance of the proposed system accessed using the maximum likelihood (ML) detector for different modulation schemes is significantly better as compared to the existing cooperative relaying OFDM-IM-aided NOMA systems, including single-mode and hybrid systems.Cooperative Dual-Mode OFDM Index Modulation based Downlink Multi-User NOMA SystemSandhya Soni, The LNMIIT; Rahul Makkar, IIIT Kota; Divyang Rawal, The LNMIIT; Gurinder Singh, LNMIIT Jaipur; Vivek Bohara, IIIT-Delhi; Zilong liu, University of Essex

Characterization of Intra-platoon V2V Links in Long Homogeneous Platoons

Vehicular platooning aims to improve fuel efficiency and traffic fluidity, and wireless protocols can support such goals. Platoons benefit all vehicle classes (e.g., passenger, truck, trailer), and can be made arbitrarily long, to the extent control and networking mechanisms allow. Vehicle-to-Vehicle (V2V) wireless links inside the platoon are susceptible to path loss, shadowing & diffraction by vehicular obstacles, and fading. In this paper we characterize V2V intra-platoon links at the physical and data-link levels, for platoons composed of same-class vehicles. Our simulation results, using a 30 vehicle-long platoon, show that vehicle dimensions affect propagation and link-level performance, notably that Packet Delivery Ratio (PDR) for edge nodes in an all-passenger vehicle scenario can be 3 times higher than for an all-trailer scenario.Characterization of Intra-platoon V2V Links in Long Homogeneous PlatoonsSaeid Sabamoniri, Pedro Miguel Santos, Universidade do Porto – Faculdade de Engenharia – CISTER Research Unit; Luis Almeida, FEUP - Universidade do Porto, Portugal

Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM Rad...

MIMO-OFDM is a key physical-layer architecture for current and next-generation wireless communication. This paper proposes a receive beamforming design scheme for MIMO-OFDM radars configured with partially-connected hybrid linear arrays, in an attempt to improve target parameter (i.e., angle, range, and velocity) estimation. Unlike existing joint estimation methods, our approach first adopts a subspace algorithm to acquire the angle information at the analog beamformer output. Then, maximum signal-to-interference ratio (MSINR) digital beamforming is conducted for target signal alignment to achieve (i) accurate range-velocity estimation thanks to suppressed interference, and (ii) automatic pairing of the identified parameter triple. Moreover, the received signal structure at the analog beamformer output is exploited for obtaining side information of the target range, which can be used to accelerate the search of range and velocity. Simulation results are used to illustrate the effectiveness of the proposed scheme.Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM RadarsWei-Cheng Kao, Jwo-Yuh Wu, Shang-Ho Tsai, National Yang Ming Chiao Tung University; Tsang-Yi Wang, National Sun Yat-Sen University

OTFS Sensing with SDR: Experimental Results and Analysis

Localization will be an essential requirement for various 6th generation (6G) communication system applications. Integrated Sensing and Communication (ISAC) is seen as a key enabling technology that can provide the capability of combined communication and localization. Reliable ISAC in a high-mobility environment can be challenging and existing communication waveforms suffer from severe degradation due to significant Doppler effect. The Delay-Doppler (DD) domain can be commonly seen in the results of Radio Detection and Ranging (RADAR) systems, which is the baseline for Orthogonal Time Frequency Space (OTFS) modulation. Due to the information encoding in DD domain, OTFS shows significant resilience against doubly-selective channels. In this work, we report the sensing functionality performance of our complete sub-6GHz ISAC system based on the OTFS waveform, implemented on a USRP X310 Software Defined Radio (SDR). The sensing capability of the system is experimentally verified in both an anechoic chamber and in an office scenario for single and for multitargets.OTFS Sensing with SDR: Experimental Results and AnalysisMuhammad Nauman, Lukasz Lopacinski, IHP; Nebojsa Maletic, IHP - Leibniz-Institut für innovative Mikroelektronik; Matthias Scheide, Jesus Gutiérrez, IHP; Milos Krstic, IHP - Leibniz-Institut für innovative Mikroelektronik; Eckhard Grass, IHP, Germany and HU, Berlin

MovBeat: A Contrastive Learning Based WiFi CSI Sensing for Respiration Monitoring in Mobil...

Vital sign monitoring plays a key role in modern healthcare, supporting applications ranging from chronic disease management to more advanced elderly care. While traditional systems rely on contact-based devices, recent advances in WiFi sensing allow contactless monitoring using channel state information (CSI), offering a more convenient and unobtrusive approach. However, most existing WiFi-based methods mainly concentrate on monitoring in static conditions, rendering them unsuitable for real-world scenarios such as measuring respiration rate during walking. To address this gap, in this paper we propose MovBeat, a respiration prediction system designed to deliver high-accuracy respiratory monitoring when the subject is in motion. By integrating a contrastive learning framework with attention-based feature extraction, MovBeat effectively mitigates interference from the environment and body movements. Experimental results demonstrate that MovBeat achieves over 90% accuracy in monitoring respiration on the move - an improvment of approximately 20% compared to traditional methods. Comprehensive evaluations in diverse movement states, including both line-of-sight (LoS) and non-line-of-sight (NLoS) environments, demonstrate the robustness and generalizability of MovBeat in real-world scenarios.MovBeat: A Contrastive Learning Based WiFi CSI Sensing for Respiration Monitoring in Mobility ScenariosYifan Feng, University of Sydney; Peng Cheng, La Trobe University; Shenghong Li, Data 61, CSIRO, Australia; Hongze Liu, Geng Wang, University of Sydney; Branka Vucetic, The University of Sydney; Yonghui Li, University of Sydney

Joint Behavior and Location Recognition Framework Based on Electromagnetic Fingerprints

Simultaneous perception of human behavior and location in indoor environments is a significant challenge. Multi-task Learning (MTL) frameworks have been shown to effectively address this problem by leveraging correlations between tasks. However, traditional MTL models usually rely on a fixed parameter sharing mechanism, which can limit model learning capabilities and lead to substantial accuracy variations across tasks. To address these issues, we propose a novel joint perception framework that utilizes Channel State Information (CSI) fingerprinting. First, we introduce a selective sharing method based on sparse parameters to mitigate the problems associated with fixed parameter sharing in MTL. This approach dynamically allocates shared parameters according to the specific needs of each task, thereby enhancing the flexibility of the model. Second, to further balance the model performance between two tasks, we introduce an adaptive loss weight adjustment approach. This approach dynamically adjusts the loss weights based on the performance of each task, ensuring good accuracy for both behavior recognition and location estimation. Experimental results demonstrate that our proposed framework significantly enhances accuracy in both behavior recognition and location estimation.Joint Behavior and Location Recognition Framework Based on Electromagnetic FingerprintsMinmin Liu, Xi'an Jiaotong University; Sijie Liu, Renmin University of China; Xuewen Liao, Xi'an JiaoTong University; Dingxuan Chen, Xi’an Jiaotong University

Design of Integrated Communication and Remote Sensing in LEO Satellite Systems

In this paper, we investigate the integration of communication and synthetic aperture radar (SAR)-based remote sensing in low Earth orbit (LEO) satellite systems. To address the high-mobility characteristic of LEO satellites, we propose an integrated system architecture based on an orthogonal delay-Doppler division multiplexing (ODDM) signal waveform. Specifically, we provide a wireless frame compatible with the 5G NR standard for signal sharing and design a unified channel sensing scheme that utilizes shared ODDM signals for both channel estimation in communication and interference-free range reconstruction in SAR imaging. Finally, numerical simulation results confirm the effectiveness of the proposed scheme.Design of Integrated Communication and Remote Sensing in LEO Satellite SystemsYichao Xu, Xiaoming Chen, Ming Ying, Zhaoyang Zhang, Zhejiang University

On the Sensing Performance of FMCW-based Integrated Sensing and Communications with Arbitr...

Integrated sensing and communications (ISAC) is expected to play a major role in numerous future applications, e.g., smart cities. Leveraging native radar signals like the frequency modulated continuous wave (FMCW) waveform additionally for data transmission offers a highly efficient use of valuable physical radio frequency (RF) resources allocated for automotive radar applications. In this paper, we propose the adoption of higher-order modulation formats for data modulation onto an FMCW waveform and provide a comprehensive overview of the entire signal processing chain. We evaluate the impact of each component on the overall sensing performance. While alignment algorithms are essential for removing the information signal at the sensing receiver, they also introduce significant dispersion to the received signal. We analyze this effect in detail. Notably, we demonstrate that the impact of non-constant amplitude modulation on sensing performance is statistically negligible when the complete signal processing chain is considered. This finding highlights the potential for achieving high data rates in FMCW-ISAC systems without compromising the sensing capabilities.On the Sensing Performance of FMCW-based
Integrated Sensing and Communications with
Arbitrary ConstellationsDaniel Gil Gaviria, Benedikt Geiger, Charlotte Muth, Laurent Schmalen, Karlsruhe Institute of Technology

Integrated Sensing and Communications for Unsourced Random Access: A Spectrum Sharing Comp...

This paper addresses the unsourced/uncoordinated random access problem in an integrated sensing and communications (ISAC) system, with a focus on uplink multiple access code design. Recent theoretical advancements highlight that an ISAC system will be overwhelmed by the increasing number of active devices, driven by the growth of massive machine-type communication (mMTC). To meet the demands of future mMTC network, fundamental solutions are required that ensure robust capacity while maintaining favorable energy and spectral efficiency. One promising approach to support emerging massive connectivity is the development of systems based on the unsourced ISAC (UNISAC) framework. This paper proposes a spectrum-sharing compressive sensing-based UNISAC (SSCS-UNISAC) and offers insights into the practical design of UNISAC multiple access codes. In this framework, both communication signals (data transmission) and sensing signals (e.g., radar echoes) overlap within finite channel uses and are transmitted via the proposed UNISAC protocol. The proposed decoder exhibits robust performance, providing 20-30 dB capacity gains compared to conventional protocols such as TDMA and ALOHA. Numerical results validate the promising performance of the proposed scheme.Integrated Sensing and Communications for Unsourced Random Access: A Spectrum Sharing Compressive Sensing ApproachZhentian Zhang, Jian Dang, Southeast University; Kai-Kit Wong, University College London; Zaichen Zhang, Southeast University; Christos Masouros, University College London

Demo: Driver Gaze-Aware Adaptive LiDAR Sensing for Advanced Driver Assistance Systems

Light detection and ranging (LiDAR) plays a crucial role in machine perception for advanced driver assistance systems. Existing LiDARs, however, do not adapt their sensing strategy to complement driver’s perception. We demonstrate a novel LiDAR prototype that dynamically adapts its range and resolution over the field of view, according to real-time driver gaze. Our gaze-aware LiDAR emphasizes scanning peripheral zones the driver may overlook, i.e., critical areas during driving. Our demonstration showcases enhanced perception, highlighting the potential of hybrid human-machine sensing for safer driving.Demo: Driver Gaze-Aware Adaptive LiDAR Sensing for Advanced Driver Assistance SystemsFederico Scarì, Arkady Zgonnikov, Chen Quan, Nitin Jonathan Myers, Delft University of Technology