VTC 2025 Spring Conference’s Shorts

Particle Filter Localization using a Hybrid Sub-6 GHz and mmWave System

Indoor localization has attracted considerable attention in recent years, driven by the growth of Internet of Things (IoT) applications. The transition of wireless communication systems toward higher frequency bands has further enabled higher accuracy user positioning. Various positioning methods have emerged over the years, supporting different levels of accuracy. In this work, we leverage measurements from multiple wireless communication technologies to address a dynamic positioning scenarios. We employ a Particle Filter (PF) to combine Time-of-Arrival (ToA) estimates from Sub-6 GHz and mmWave technology to enhance the localization accuracy in an indoor environment. Additionally, we evaluate the performance of the proposed algorithm by examining the positioning error statistics in different scenarios. Simulation results indicate that the proposed hybrid algorithm improves the mean localization and tracking error by approximately 42.8% and 17.8%, in comparison to the individual use of Sub-6 GHz and mmWave positioning technologies, respectively. The combination of these estimates results in a mean absolute positioning error better than 10 cm.Particle Filter Localization using a Hybrid Sub-6 GHz and mmWave SystemRamya Vasist, IHP - Leibniz-Institut für innovative Mikroelektronik; Vladica Sark, Leibniz-Institut für innovative Mikroelektronik; Jesus Gutiérrez, IHP; Eckhard Grass, IHP, Germany and HU, Berlin

Optimization of Probabilistic Constellation Shaping for Improving Secrecy Performance of O...

Physical layer security (PLS) is an attractive paradigm for protecting information confidentiality without the use of traditional key-based cryptography. This paper proposes a design of probabilistic constellation shaping to improve the PLS performance of optical wireless channels using M-ary pulse amplitude modulation (M-PAM) with the signal-dependent noise model. Specifically, the proposed design aims to maximize the reliability (i.e., minimization of the bit error rate - BER) of the legitimate user’s channel while guaranteeing that the modulation-constrained secrecy capacity is at least equal to that achieved by the uniform signaling. For this purpose, a novel upper bound for the BER of M-PAM constellation with signal-dependent noise channels with arbitrary input distribution is derived. Simulation results reveal that the proposed PCS design achieves a considerably lower BER of the legitimate user’s channel while attaining the same secrecy capacity as the uniform signaling.Optimization of Probabilistic Constellation Shaping for Improving Secrecy Performance of Optical Wireless Channels with Signal-Dependent NoiseThanh V. Pham, Shizuoka Univeristy; Susumu Ishihara, Shizuoka University

Misdetection Risk-aware Adaptive LiDAR Sensing for Automotive Driving

Automotive LiDARs typically have a uniform scanning range over their field of view (FoV). Such a range profile does not account for the varying risk of misdetecting targets in different regions. For instance, prioritizing crosswalks in a LiDAR scan is crucial, as the financial consequences of missing a pedestrian far exceed that of overlooking a distant vehicle. In this paper, we construct a spatial risk map that quantifies the risk of misdetecting targets across different regions around the vehicle. Our risk map incorporates lane semantics, knowledge about previously identified objects, and their potential trajectories. We use this risk map to adapt the LiDAR’s scanning range over different sectors in its FoV. Simulations on nuScenes episodes demonstrate that our misdetection risk-aware design reduces the effective risk by about 40% compared to a standard LiDAR.Misdetection Risk-aware Adaptive LiDAR Sensing for Automotive DrivingChris Hogendoorn, Ruben Wosten, Marnix Zimmerman, Nitin Jonathan Myers, Delft University of Technology

Maximizing Weighted Function in STAR-RIS aided SWIPT-IoT with Discrete Phase Shifting

The conventional reflection-only Reconfigurable Intelligent Surface (RIS) extends its 180-degrees coverage to 360-degrees with Simultaneously Transmitting and Reflecting-RIS (STAR-RIS). When integrated with the Simultaneous Wireless Information and Power Transfer (SWIPT) system, it enhances performance by directing energy and information signals to energy receiver (ER) and information receiver (IR), with Energy Splitting (ES) and Mode Switching (MS) operational protocol. Considering a practical system with discrete phase shift (DPS) model and non-linear energy harvesting (EH) model, we aim to maximize the weighted rate-energy (WRE) function, with certain QoS constraints by optimizing power parameters. An alternating optimizing (AO) algorithm solves the complicated WRE maximization problem. Numerical results highlight the impact of energy split ratio and element division on the performance, with the critical selection of DPS level (quantization bits) balancing device bulkiness (phase control bits) and system efficiency.Maximizing Weighted Function in STAR-RIS aided SWIPT-IoT with Discrete Phase ShiftingNeha Sharma, Manojkumar B. Kokare, Indian Institute of Technology Indore; Swaminathan R, Indian Institute of Technology Indore, India; Sumit Gautam, Indian Institute of Technology - Indore

Leveraging Large Reconfigurable Intelligent Surfaces as Anchors for Near-Field Positioning

In this work, we present a recent investigation on leveraging large reconfigurable intelligent surfaces (RISs) as anchors for positioning in wireless communication systems. Unlike existing approaches, we explicitly address the uncertainty arising from the substantial physical size of the RIS—particularly relevant when a user equipment (UE) resides in the near field—and propose a method that ensures accurate positioning under these conditions. We derive the corresponding Cramér–Rao bound (CRB) for our scheme and validate the effectiveness of our scheme through numerical experiments, highlighting both the feasibility and potential of our approach.Leveraging Large Reconfigurable Intelligent Surfaces as Anchors for Near-Field PositioningZeyu Huang, TU Wein; Markus Rupp, Stefan Schwarz, TU Wien

Knowledge Distillation for Modulation Classification in Resource-Constrained Devices

Automated modulation classification (AMC) is crucial in electronic warfare because it enhances situational awareness and prompts responses to hostile transmissions. This research addresses the challenges of deploying AMC in limited computational environments by proposing using response-based knowledge distillation (KD) to train compact yet accurate AMC models. The methodology involves a framework that integrates a signal-based convolutional neural network (SBCNN) and an image-based convolutional neural network (IBCNN). The SBCNN extracts features from preprocessed signal data, which is subsequently used to train the IBCNN. Experimental results indicate that the SBCNN-based approach, when trained with teacher distillation, achieves superior performance compared to its standalone counterpart. Our findings show that KD has significant potential to enhance AMC performance in real-time applications by balancing computational demands with classification accuracy.Knowledge Distillation for Modulation Classification in Resource-Constrained DevicesPedro Marcio Raposo Pereira, Felipe Augusto Pereira de Figueiredo, Rausley Adriano Amaral de Souza, National Institute of Telecommunications (Inatel)

Intent-based Service Composition in 6G Cross-chain Marketplaces: Leveraging Trust

A key tenet of 6G is a network of networks, upon which sophisticated services can be composed in real-time; this service composition can be realized through decentralized 6G marketplaces of services. These services may include high fidelity real-time holograms, as well as sensitive medical applications, and hence users will have stringent privacy expectations of these services and on the trustworthiness of the constituent service providers and the marketplaces themselves. Rather than specify the details of the required trust in each constituent service provider/marketplace, users will want to specify their requirements through high-level intents on the functionality, price, and trust of their desired composite services. Cross-chain technologies, together with reputation frameworks, provide accountability as an underpinning of trust in such decentralized marketplaces. In this paper, we present an intent-based architecture for cross-chain marketplaces of 6G services, where trust is a first-class factor. Building on our earlier work, we describe several design and implementation approaches for such intent-based service composition integrated with Hyperledger Fabric and Hyperledger Cacti blockchain/cross-chain technologies, and evaluate the comparative benefits of these approaches with respect to key aspects of intent fulfillment and intent assurance. Our work is in the context of UNEXT™, an intelligent networking platform being created at Nokia Bell Labs.Intent-based Service Composition in 6G Cross-chain Marketplaces: Leveraging TrustFarhad Keramat, University of Turku; Shushu Liu, Nokia bell labs; Lalita Jagadeesan, Nokia Bell Labs; Lizette Velazquez, Nokia

Comparison of Multilateration using Wi-Fi RSSI and 5G ToA in a High School Scenario

This study explores indoor positioning using wireless technologies, specifically 5G NR and WiFi (2.4 GHz and 5 GHz) frequencies, applying multilateration techniques, which are used natively in 5G NR, and the KNN supervised learning algorithm. In order to apply these positioning techniques, we will use RSSI value, due to its ease of use in real-life situations, and the Time of Arrival parameters, as this is the value used in the 5G NR integrated positioning protocol, known as LMF. This study compares 5G NR and WiFi positioning accuracy, demonstrating improvements using 5G NR. For this study, the EMSlice simulation solution was chosen, which has been configured to mimic a real high school. The generated measurements have been compared with real samples to check their quality level.This study aims to provide insights into the advantages and limitations of each technology in various indoor scenarios. The findings contribute to the development of reliable indoor positioning systems. The study revealed that the 5G NR FR1 exhibited a positioning accuracy of 2.35 m RMSE, in comparison to 2.75 m for 2.4 GHz Wi-Fi and 3.80 m for 5 GHz Wi-Fi. Combining Time of Arrival (ToA) with RSSI achieves the highest accuracy, with an RMSE of 2.23 m.Comparison of Multilateration using Wi-Fi RSSI and 5G ToA in a High School ScenarioVladimir Bellavista-Parent, Universitat Oberta de Catalunya; Joaquin Torres Sospedra, Universitat de València; Antoni Pérez-Navarro, Universitat Oberta de Catalunya

Enhancing 5G Resilience to Smart-Jammer Attacks: Incorporating Frequency Hopping to 5G

Cellular mobile networks have enabled several new use cases with their rapid development, and they are now considered for mission-critical and even military applications with 5G, their latest commercially available version. However, it is of utmost importance that communication channels operate in a secure and reliable manner for these purposes. Smart jammers pose a significant threat due to their accessibility, strong potential for causing service disruptions, and their difficulty in detection. This issue can be reduced by hopping between frequencies, making it harder for a malicious actor to disrupt communication. In this study, the handover mechanism, which is a supported feature in all commercial devices according to 3GPP standards, is evaluated as a frequency hopping technique in terms of feasibility and performance at preventing the attack. The proposed method is proven effective, as it can switch frequencies every second while keeping data interruptions below 75 ms for 99% of the time.Enhancing 5G Resilience to Smart-Jammer Attacks: Incorporating Frequency Hopping to 5GMiguel Villanueva Fernandez, Preben Mogensen, Klaus Pedersen, Aalborg University; Hung Tuan Nguyen, Rohde & Schwarz Technology Center Denmark; Alejandro RamÃ

Differential Delay Mitigation in Multi-Antenna Aircraft Transmissions

In multi-antenna transmit diversity systems, accurate Channel State Information estimation is essential for reliable data decoding. In aeronautical telemetry, the spatial separation of antennas onboard aircraft, which can span several meters, introduces non negligible differential delays between received signals which degrades channel estimation, thereby impacting receiver performance. To address this issue, we propose a novel approach where both pilot sequences and transmitted data are Space-Time Block Coded to enhance CSI estimation by mitigating the degradation caused by differential delay. Thus leading to improved receiver robustness in multi-antenna aircraft telemetry. Simulation results demonstrate significantly better cross-correlation properties for the proposed pilot sequences over IRIG-106 ones. Complete communication system simulation using AWGN channel confirms that the new sequences provide gains in CSI estimation without computational complexity increase.Differential Delay Mitigation in Multi-Antenna Aircraft TransmissionsOussama AIT SIDI ALI, University of Rennes; Romain TAJAN, IMS Laboratory; Bertrand LE GAL, IRISA Laboratory; Alain THOMAS, SAFRAN DATA SYSTEMS