8th MC Meeting and 8th Technical Meeting - Helsinki, Finland, June 17-20
TD Number | TD Author | TD Title | TD Abstract | TD WG |
| TD(24)08001 | Salah Eddine Zegrar, Hamza Haif, Hüseyin Arslan | OTFS-Based ISAC for Super-Resolution Range-Velocity Profile | The recently popularized ISAC paradigm attempts carry out both communication and sensing functionalities uses the same time-frequency resources to combat the scarcity of these resources. However, high-resolution range and velocity radars require wideband long-duration transmission, which implies complex, costly receivers to sample at a high-frequency rate. In this paper, we propose an orthogonal time-frequency space (OTFS)-based ISAC system which enables achieving highly accurate range-velocity profiles without the need for large bandwidth transmissions or long-duration frames. This approach relaxes the constraints on bandwidth and time while still providing precise sensing information. The proposed scheme exploits a single OTFS carrier with rectangular pulse shaping as a pilot to estimate both simultaneous accruing delay and Doppler, thereby determining range and velocity, respectively. By leveraging the sidelobes of the physical pulse shape of the pilot signal, we propose an algorithm that allows the detection of the range and the velocity of radar targets beyond the resolution limitation set by the time duration and the bandwidth of the transmitted signal. The conducted simulation results along with the real experimental results demonstrate that the proposed design can achieve accurate low-complexity radar parameter estimation. | WG1,WG2 |
| TD(24)08004 | Maxime Vaillant, Alix Jeannerot, Jean-Marie Gorce | Joint Constellation Shaping Using Gradient Descent Approach for MU-MIMO Broadcast Channel | We introduce a learning-based approach to optimize a joint constellation for a multi-user MIMO broadcast channel (T Tx antennas, K users, each with R Rx antennas), with perfect channel knowledge. The aim of the optimizer (MAX-MIN) is to maximize the minimum mutual information between the transmitter and each receiver, under a sum-power constraint. The proposed optimization method do neither impose the transmitter to use superposition coding (SC) or any other linear precoding, nor to use successive interference cancellation (SIC) at the receiver. Instead, the approach designs a joint constellation, optimized such that its projection into the subspace of each receiver $k$, maximizes the minimum mutual information I(Wk;Yk) between each transmitted binary input Wk and the output signal at the intended receiver Yk. The rates obtained by our method are compared to those achieved with linear precoders. | WG2 |
| TD(24)08005 | Marco Skocaj, Lukas Eller | Safe Online Mobile Network Optimization via Gradient-Aided Monte Carlo Tree Search | The efficient operation of cellular networks requires precise tuning of configuration parameters such as antenna downtilt and transmit power. Here, data-driven methods, which can integrate feedback from monitoring data, are promising but face challenges related to sample efficiency, scalability, and safety — limiting their real-world application. In this work, we introduce an innovative online coverage and capacity optimization framework that combines model-free exploration using Monte Carlo tree search with a safe, model-based baseline derived from a probabilistic differentiable network twin. We formulate the optimization problem as a sequential game, developing specialized tree policies to guide the exploration of the configuration space. The differentiable network twin aids both the selection policy, by pruning the search space with a prior action distribution, and the rollout policy, enabling domain knowledge-based selection of remaining actions. Our results demonstrate that the proposed approach effectively directs the optimization process, outperforming both purely model-free and model-based methods. It reduces the risk of testing poorly performing configurations, enhances the model-based solution, and can also compensate for severe model mismatches in the digital twin. Hence, the framework addresses a common obstacle in applying data-driven optimization to real-world network deployments. | WG3 |
| TD(24)08006 | Yang Miao, Carsten Smeenk, Alister Burr, Ana Garcia Armada | White Paper of WG2 | This is the current status of the White Paper that WG2 is preparing. | WG2 |
| TD(24)08007 | Johannes M. Eckhardt, Tobias Doeker, Thomas Kürner | Hybrid Channel Model for THz Links in a Data Center | The aim of channel models is the effective prediction of wireless channels in application-specific environments. For THz communications, deterministic ray-optical channel predictions are very common. This Temporary Document shows inherent limitations in the accuracy of three-dimensional models of the environment in the context of THz communications and presents a new hybrid channel model approach that combines ray-optical channel predictions with an analytic path gain model extracted from measurements. The model is applied for wireless inter-rack links in a data center and derived channel parameters show promising results compared with conducted reference measurements. | WG1,Sub-WG1.1 |
| TD(24)08008 | Johannes M. Eckhardt, Steffen Kroos, Christoph Herold, Thomas Kürner | Impact of RF-Impairments on THz Links in a Data Center | For modern communication systems, especially in the low THz band, the characteristics of cutting-edge hardware components have a crucial impact on the performance of the data transmission. Therefore, it is inevitable to model the impairments of RF devices on the signals and waveforms in order to get meaningful simulation results. This Temporary Document presents four types of RF impairments and its modeling approach within the link level simulations performed with SiMoNe – Simulator for Mobile Networks. The respective impact of the RF impairments on the physical layer performance is examined based on realistic hardware characterizations for a THz inter-rack link in a data center. | WG2 |
| TD(24)08009 | Dragana Bajic | Communications engineering in biosystems: an inspiration for future perspectives? | During the 40 years of its existence, our Action has both initiated and followed the incredible progress of communication engineering. Other global fields, however, were not as successful. Facing the lack of resources and climate change, a question of potential communication backup arises. This TD outlines communication engineering methods that have counterparts in Nature. The methods of Nature can be different, suboptimal, or even far from optimal, but Nature is known for rational resource usage, and sustainability is the proven advantage of its methods. Perhaps understanding their engineering aspects can inspire a design of alternative green, stable, and low-cost data transmission and storage. Although currently not within the Action mainstream, the TD shows alternatives that may be useful later. | WG2 |
| TD(24)08010 | Gianluca Rizzo | Mobile Networks on the Move: Optimizing Moving Base Stations Dynamics in Urban Scenarios | Base station densification is one of the key ap- proaches for delivering high capacity in radio access networks. However, current static deployments are often impractical and financially unsustainable, as they increase both capital and operational expenditures of the network. An alternative paradigm is the moving base stations (MBSs) approach, by which part of base stations are installed on vehicles. However, to the best of our knowledge, it is still unclear if and up to which point MBSs allow decreasing the number of static base stations (BSs) deployed in urban settings. In this work, we start tackling this issue by proposing a modeling approach for a first-order evaluation of potential infrastructure savings enabled by the MBSs paradigm. Starting from a set of stochastic geometry results, and a traffic demand profile over time, we formulate an optimization problem for the derivation of the optimal combination of moving and static BSs which minimizes the overall amount of BSs deployed, while guaranteeing a target mean QoS for users. Initial results on a two- district scenario with measurement-based network traffic profiles suggest that substantial infrastructure savings are achievable. We show that these results are robust against different values of user density. | WG3 |
| TD(24)08011 | Amilton V. Baptista and Fernando J. Velez | Q-Learning-Driven Enhancement of Slotted ALOHA in IEEE 802.15.4 WSNs | Given the proliferation of connected devices and the prioritization of real-time data acquisition across various scenarios, enhancing the energy efficiency within Wireless Sensor Networks (WSNs) is of paramount importance. This work has focused on the IEEE 802.15.4 standard and addresses existing medium access control protocols such as CSMA or Slotted ALOHA and proposes refinements in the Slotted ALOHA protocol through incorporating techniques like Binary Exponential Backoff (BEB) and Q-learning. These enhancements have demonstrated to be promising in terms of average delay reduction, energy efficiency and bolstered network throughput. As it facilitates more efficient energy management it constitutes a robust alternative to conventional CSMA in WSN MAC sub-layer protocols. | WG3 |
| TD(24)08012 | Antoni Gelabert-Fons, Mario Garcia-Lozano and Sílvia Ruiz-Boqué | Integration of Drones into 5G Urban Networks with 3D Beamforming | The purpose of this research work is to conduct a detailed evaluation of the coverage and QoS of a 5G network in an urban environment that includes aerial users -drones-. To provide the 3D coverage needed to keep both ground and aerial users connected, beamforming is implemented with different antenna geometries. The quality of SSB (Synchronization Signal Block) and PDSCH (Physical Downlink Shared Channel) channels is analysed through different metrics as Received Power, Signal to Interference and Noise Ratio (SINR) and Modulation and Coding Scheme (MCS). Results are compared with those obtained by a classical trisectorization cell deployment. | WG3 |
| TD(24)08013 | Sergio Castelló-Palacios; Eva Antonino-Daviu; Antonio Vila-Jiménez; Ana Vallés-Lluch; Narcís Cardona; Concepcion Garcia-Pardo | Biocompatible Low-Cost Antennas Over Flexible Substrates for IoT-Health Applications | This paper presents a 10 GHz wearable antenna specifically designed for IoT-Health applications. Their main distinguishing features are its biocompatibility and flexibility, which are acquired by designing custom-made materials. Four custom-made materials were designed and manufactured in order to compare the performance of the antenna according to the selected substrate. The study assesses the impact of these materials on critical parameters such as bandwidth, efficiency, and radiation patterns. This work includes both the simulations of the antenna behaviour based on the dielectric properties of the materials, and also the experimental results from the real measurements performed on manufactured antennas. Results contribute to the ongoing evolution of materials in antenna design, opening new possibilities for the advancement of communication solutions in healthcare applications. | VT1 |
| TD(24)08015 | Xuanyu Liang, Ahmed Al-Tahmeesschi, Qiao Wang, Swarna Chetty, Chenrui Sun, Hamed Ahmadi | Enhancing Energy Efficiency in O-RAN Through Intelligent xApps Deployment | he proliferation of 5G technology presents an unprecedented challenge in managing the energy consumption of densely deployed network infrastructures, particularly Base Stations (BSs), which account for the majority of power usage in mobile networks. The O-RAN architecture, with its emphasis on open and intelligent design, offers a promising framework to address the Energy Efficiency (EE) demands of modern telecommunication systems. This paper introduces two xApps designed for the O-RAN architecture to optimize power savings without compromising the Quality of Service (QoS). Utilizing a commercial RAN Intelligent Controller (RIC) simulator, we demonstrate the effectiveness of our proposed xApps through extensive simulations that reflect real-world operational conditions. Our results show a significant reduction in power consumption, achieving up to 50% power savings with a minimal number of User Equipment (UEs), by intelligently managing the operational state of Radio Cards (RCs), particularly through switching between active and sleep modes based on network resource block usage conditions. | WG3 |
| TD(24)08019 | Jie Zhang, Qiao Wang, Paul Mitchell, Hamed Ahmadi | An Integrated Access and Backhaul Approach to Sustainable Dense Small Cell Network Planning | Integrated access and backhaul (IAB) networks offer transformative benefits, primarily their deployment flexibility in locations where fixed backhaul faces logistical or financial challenges. This flexibility is further enhanced by IAB’s inherent ability for adaptive network expansion. However, existing IAB network planning models, which are grounded in the facility location problem and are predominantly addressed through linear programming, tend to neglect crucial geographical constraints. These constraints arise from the specific deployment constraints related to the positioning of IAB donors to the core network, and the geographic specificity required for IAB-node placements. These aspects expose an evident research void. To bridge this, our research introduces a geographically aware optimization methodology tailored for IAB deployments. In this paper, we detail strategies for both single-hop and multi-hop situations, concentrating on IAB donors distribution and geographical constraints. Uniquely in this study, we employ the inherent data rate limitations of network nodes to determine the maximum feasible hops, differing from traditional fixed maximum hop count methods. We devise two optimization schemes for single-hop and multi-hop settings and introduce a greedy algorithm to effectively address the non-convex multi-hop challenge. Extensive simulations across various conditions (such as diverse donor numbers and node separations) were undertaken, with the outcomes assessed against the benchmark of the single-hop scenario’s optimal solution. Our findings reveal that the introduced algorithm delivers efficient performance for geographically constrained network planning. | WG3 |
| TD(24)08020 | Agnieszka Czapiewska, Andrzej Luksza, Ryszard Studanski, Lukasz Wojewodka, and Andrzej Zak | Comparison of Doppler Effect Estimation Methods for MFSK Transmission in Multipath Hydroacoustic Channel | Underwater wireless communication remains a challenging topic, particularly for applications such as wreck penetration where multipath and Doppler effects are very intense. These effects are becoming even more difficult to mitigate for fast data transmission systems that utilize wideband signals. Due to the low propagation speed of acoustic wave in the water, there is a significant difference between the Doppler shift for lower and upper frequencies of the utilized spectrum. To address these challenges, this paper describes various methods for determining the Doppler frequency shift for MFSK signals, including cross-correlation, double FFT, pilots, and additional Up-Down chirp signals. The reception quality of the transmitted data in a real environment was used as an evaluation criterion for each method. The tests were carried out in motion within the towing tank for different movement speeds of the transmitter relative to the receiver. The tank’s limited dimensions created conditions for multipath signal propagation. Under very difficult multipath signal propagation conditions, the pilots method was found to be the most effective. It gave over two times lower BER than the well-known Up-Down chirp method. | WG2 |
| TD(24)08021 | Guoda Tian, Dino Pjanić, Xuesong Cai, Bo Bernhardsson, Fredrik Tufvesson | Attention-aided Outdoor Localization in Commercial 5G NR Systems | The integration of high-precision cellular localization and machine learning (ML) is considered a cornerstone technique in future cellular navigation systems, offering unparalleled accuracy and functionality. This study focuses on localization based on uplink channel measurements in a fifth-generation (5G) new radio (NR) system. An attention-aided ML-based single-snapshot localization pipeline is presented, which consists of several cascaded blocks, namely a signal processing block, an attention-aided block, and an uncertainty estimation block. Specifically, the signal processing block generates an impulse response beam matrix for all beams. The attention-aided block trains on the channel impulse responses using an attention-aided network, which captures the correlation between impulse responses for different beams. The uncertainty estimation block predicts the probability density function of the UE position, thereby also indicating the confidence level of the localization result. Two representative uncertainty estimation techniques, the negative log-likelihood and the regression-by-classification techniques, are applied and compared. Furthermore, for dynamic measurements with multiple snapshots available, we combine the proposed pipeline with a Kalman filter to enhance localization accuracy. To evaluate our approach, we extract channel impulse responses for different beams from a commercial base station. The outdoor measurement campaign covers Line-of-Sight (LoS), Non Line-of-Sight (NLoS), and a mix of LoS and NLoS scenarios. The results show that sub-meter localization accuracy can be achieved. | WG1,WG2 |
| TD(24)08022 | Javier Otero Martinez and Ana García Armada | Simulation of Realistic Correlation Scenarios for Fluid Antenna Systems | Reconfigurable antennas are expected to play an important role in present and future communication systems. Following that trend, liquid antennas are able to change their topology in order to match different specifications and requirements. Unfortunately, it turns out that fewer details in hardware may imply that our current channel models cannot be applied successfully in this context. In particular, spatial correlation is key to understanding how this reconfiguration can be achieved and its strengths and limitations. This work pretends to develop a spatially consistent framework for modeling liquid antenna communications. | WG1 |
| TD(24)08023 | Bing Xue, Juha Tuomela, Katsuyuki Haneda, Clemens Icheln, Juha Ala-Laurinaho | Permittivity Characterization of Human Skin Based on Free Space Reflection Coefficients at Sub-THz | This paper introduces a novel approach to experimentally characterize effective human skin permittivity at sub-Terahertz (sub-THz) frequencies, specifically from $140$~to $210$~GHz, utilizing a quasi-optical measurement system. To ensure accurate measurement of the reflection coefficients of human skin, a planar, rigid, and thick reference plate with a low-loss dielectric is utilized to flatten the human skin surface. A permittivity characterization method is proposed to reduce permittivity estimation deviations resulting from the pressure effects on the phase displacements of skins under the measurements but also to ensure repeatability of the measurement. In practical permittivity characterizations, the complex permittivities of the finger, palm, and arm of seven volunteers show small standard deviations for the repeated measurements, respectively, while those show significant variations across different regions of the skins and for different persons. The proposed measurement system holds significant potential for future skin permittivity estimation in sub-THz bands, facilitating further studies on human-electromagnetic-wave interactions based on the measured permittivity values. | Sub-WG1.1,Sub-VT1 |
| TD(24)08024 | Haoqiu Xiong, Zhuangzhuang Cui, Yang Miao, Sofie Pollin | WiGig-based Joint Multi-person Positioning and Respiration Sensing | Wi-Fi sensing has gained significant interest thanks to its low cost and easy deployment. However, existing works in WiGig-based sensing highly rely on prior knowledge such as the location of transmitter and receiver or known relative positions. To address these limitations, the paper presents a prior-knowledge-free approach for multi-person localization and breath rate (BR) estimation using the IEEE 802.11ay standard. This approach accomplishes two key objectives: (1) utilizing the beamforming functionalities specified in IEEE 802.11ay to estimate the line-of-sight (LoS) path, aiding in target localization, and (2) employing the density-based spatial clustering of applications with noise (DBSCAN) algorithm to associate scatterers with their respective targets, enhancing the robustness of BR estimation. Simulation results demonstrate that the proposed method achieves centimeter-level localization and precise BR estimation, all without relying on prior knowledge. This holds true even in harsh scenarios where target locations are close together. | WG2,VT1 |
| TD(24)08025 | Oguz Bedir, Ali Riza Ekti, and Mehmet Kemal Ozdemir | Exploring Deep Learning for Adaptive Energy Detection Threshold Determination: A Multistage Approach | The concept of spectrum sensing has emerged as a fundamental solution to address the growing demand for accessing the limited resources of the wireless communications networks. This TD introduces a straightforward yet efficient approach that incorporates multiple stages that are based on deep learning (DL) techniques to mitigate radio frequency (RF) impairments and estimate the transmitted signal using the time domain representation of received signal samples. The proposed method involves calculating the energies of the estimated transmitted signal samples and received signal samples, and estimating the energy of the noise using these estimates. Subsequently, the received signal energy and the estimated noise energy, adjusted by a correction factor (k), are employed in binary hypothesis testing to determine the occupancy of the wireless channel under investigation. The proposed system demonstrates encouraging outcomes by effectively mitigating RF impairments, such as carrier frequency offset (CFO), phase offset, and additive white Gaussian noise (AWGN) to a considerable degree. As a result, it enables accurate estimation of the transmitted signal from the received signal, with 3.85\% false alarm and 3.06\% miss detection rates, underscoring the system’s capability in adaptively determining a decision threshold for energy detection. | WG2 |
| TD(24)08026 | Ali Al-Ameri, Juan Sanchez, Fredrik Tufvesson, and Xuesong Cai | A Fast Rotating-Mirror Sounder for Dynamic Millimeter-Wave Channel Characterization | A deep understanding of double-directional wireless channels is imperative for wireless system design. This necessitates the development of precise channel models through channel sounding. Given the dynamic nature of wireless channels, a fast measurement time is highly desirable. In this paper, we present and validate a dual-polarized millimeter-wave channel sounder that uses a rotating mirror mechanism. This enables swift sweeping of the azimuthal plane to capture the spatial channel characteristics at 27.5-28.5 GHz within less than a second. This is radically faster than conventional virtual array channel sounders. Following a detailed discussion of the sounder implementation and the rotating mirror concept, we present an indoor verification measurement scenario. The results demonstrate several discernible propagation paths with parameters that agree with the actual geometry of the indoor measurement environment. | WG1,Sub-WG1.1 |
| TD(24)08027 | Steffen N. Kroos, Johannes M. Eckhardt, Christoph Herold, Thomas Kürner | Realistic Interference Simulation in a Conference Room WPAN at THz Frequencies | Targeting for higher data rates, the communication technology is now so far advanced that the so-called „terahertz gap“ is being closed. Based on this development, communication systems are to be built that use frequencies in the THz range. For the development of these systems, simulators are needed that take into account the properties of THz radiation and directional antennas. This work documents the development, verification and application of an extension of the link-level simulator in the SiMoNe simulation framework for interference simulation in THz communication. Therefore, an overview of the basics and functionalities of the link-level simulator in SiMoNe is given first. Then, building on the structures already implemented in SiMoNe, a concept is developed and implemented which makes it possible to carry out a link-level simulation with several transmitters and receivers. The resulting interference at a receiver is calculated within one simulation run. Then various tests verified the correct functioning of the implemented extension. Within a realistic scenario, simulations show that the influence of interference in THz communication is not always negligible and, furthermore, cannot be represented by an equally strong Gaussian noise. Keywords: THz communication, Interference Simulation, Link-Level-Simulation, SiMoNe iii | WG1,VT3 |
| TD(24)08028 | João Pedro Baiense, Anniek Eerdekens, Jorn Schampheleer, Margot Deryuck, Ivan Miguel Pires and Fernando J. Velez | Intelligent PPG-based Heart Rate Signal Analysis for Car Drivers Monitoring | This temporary document (TD) contributes to improving road safety by designing and exploring an intelligent smart wrist band-based health monitoring of car drivers’ solution. Inspired in a previous TD, where we addressed the hardware components, in this work, based on the work from João Pedro Baiense in a recent STSM in the University of Gent. we explore the use of several sensors, including the photoplethysmogram (PPG) and an accelerometer to accurately estimate the heart rate. Learning strategies have been considered to create a model to simplify the heart rate signal processing. The decision to use Deep Learning for PPG heart rate estimation is based on its proven ability to handle complex, high-dimensional data, as well as its potential to identify intricate patterns within physiological signals. This approach offers a promising path forward for accurately estimating heart rate from PPG data. By leveraging this approach, our aim was to develop a robust and accurate model capable of real-time heart rate estimation from PPG signals, which has the potential to enhance the utility of Internet of Medical Things (IoMT) applications in healthcare settings. The document discusses the multiple processing steps required for model development, including data analysis, signal insight, and the application of various techniques such as filters, complex algorithms, and data manipulation to enhance the quality of input data, ensuring its readiness for efficient processing by the model. The model architecture was designed by implementing TensorFlow and conducting numerous experiments to achieve the best possible results. The leave-one-session-out (LOSO) cross-validation technique was integrated for the training and evaluation of the model, along with the tuning of hyperparameters to enhance model performance and efficiency. An outstanding Mean Absolute Error (MAE) of 3.450 ± 1.324 and Mean Squared Error (MSE) of 69.50 ± 93.57 have been achieved, representing the best results ever achieved for the heart rate estimation model. These results demonstrate a high-performance and accurate model, providing invaluable information for the system. Moreover, the model was deployed in a web application for testing purposes. Finally, the chapter describes the development of a custom mobile application for the Driver Health system, which offers crucial features such as real-time access to health status, device compatibility, power management, and integration of the heart rate estimation model to provide users with further insight into their health condition. The application’s connectivity with the Driver Health device works flawlessly and serves as a central hub containing updated information and offering intuitive and accessible functionality. | WG3,VT1,VT2 |
| TD(24)08029 | Sakshi Agarwal, Kallol Das and Remco Litjens | Development and assessment of resource management solutions for throughput enhancement in a RIS-aided mobile network | Reconfigurable Intelligent Surfaces (RIS) stand out among the key technologies driving 6G mobile network development. In this work, we develop and assess radio resource management solutions aimed to exploit the potential of RIS deployments for coverage and throughput enhancement for indoor users in 6G mobile networks. We introduce two heuristic algorithms that jointly control the cell-RIS-user association, user scheduling, transmit beamforming and the RIS’s reflective configuration, and compare these algorithms against a RIS-free benchmark. Simulation results are presented to (i) demonstrate the promising potential of RIS deployments in multi-cell/multi-user scenarios; (ii) reveal the inherent trade-off between coverage and throughput enhancement; and (iii) show the performance impact of distinct RIS deployment locations. Our study provides valuable insights for efficiently leveraging RIS in evolving mobile network architectures. | Sub-WG1.2,WG3 |
| TD(24)08030 | Sara Willhammar, Hiroki Iimori, Joao Vieira, Lars Sundstrom, Fredrik Tufvesson, and Erik G. Larsson | Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO | 5G systems are being deployed all over the world and one key enabler of these systems is massive MIMO. This technology has brought large performance gains in terms of serving many users. Despite the possibility to further exploit the spatial domain, there are situations where it is not possible to offer more than a single, or a few, data streams per user and where cell-edge coverage is an issue due to the lack of enough efficient channel scatterers. Looking ahead, distributed MIMO systems, where the antennas are spread over a larger area, are investigated for next generation systems. However, distributed MIMO comes with many practical deployment issues, making it a big challenge to adopt. As another way forward, we envision repeater-assisted cellular massive MIMO, where repeaters are deployed to act as channel scatterers to increase the rank of the channel and provide macro diversity for improved coverage and reliability. After elaborating on the requirements and hardware aspects of repeaters that enable this vision, we demonstrate through simulations the potential of repeater-assisted cellular massive MIMO to achieve distributed MIMO performance. Following this, we discuss open questions and future research directions. | WG1,WG2 |
| TD(24)08031 | Benjamin Deutschmann, Christian Nelson, Mikael Henriksson, Gian Marti, Alva Kosasih, Nuutti Tervo, Erik Leitinger, Fredrik Tufvesson | Accurate Direct Positioning in Distributed MIMO Using Delay-Doppler Channel Measurements | Distributed multiple-input multiple-output (D-MIMO) is a promising technology for simultaneous communication and positioning. However, phase synchronization between multiple access points in D-MIMO is challenging, which requires methods that function without the need for phase synchronization. We therefore present a method for D-MIMO that performs direct positioning of a moving device based on the delay-Doppler characteristics of the channel state information (CSI). Our method relies on particle-filter-based Bayesian inference with a state-space model. We use recent measurements from a sub-6 GHz D-MIMO OFDM system in an industrial environment to demonstrate centimeter accuracy under partial line-of-sight (LoS) conditions and decimeter accuracy under full non LoS. | WG2 |
| TD(24)08032 | Jérome Eertmans, Nicola Di Cicco, Enrico Maria Vitucci, Vittorio Degli Esposti | Learning to Sample Ray Paths for Faster Ray Tracing | Ray Tracing has been extensively utilized in recent years to model radio propagation. Depending on the application, two variants exist: Ray Launching and Point-to-Point Ray Tracing. In contrast to Ray Launching, Point-to-Point Ray Tracing aims to identify all possible paths between a pair of nodes. This typically entails a greater computational complexity, as the number of paths to be traversed increases exponentially in proportion to the size of the scene and the number of interactions permitted. Nevertheless, only a relatively small proportion of these paths ultimately prove to be valid. In this paper, we present a Machine Learning model that is capable of learning how to select the valid paths from the set of all possible paths. Consequently, the complexity of the model is constrained by the linear complexity of the Machine Learning model with respect to the number of objects in the scene. Moreover, in contrast to recent proposals in the literature, our model is designed to accommodate input scenes of any size and does not depend on electromagnetic properties such as frequency. | WG1 |
| TD(24)08033 | Jérome Eertmans, Claude Oestges, Laurent Jacques | DiffeRT2d: A Differentiable Ray Tracing Python Framework for Radio Propagation | Ray tracing is arguably one of the most prevalent methodologies in the field of radio propagation modeling. However, the access to ray tracing software is often constrained by its closed-source nature, licensing costs, or the requirement of high-performance computing resources. While this is typically acceptable for large-scale applications, it can present significant limitations for researchers who require more flexibility in their approach, while working on more simple use cases. We present DiffeRT2d, a 2D open-source differentiable ray tracer that addresses the aforementioned gaps. DiffeRT2d employs the power of JAX to provide a simple, fast, and differentiable solution. Our library can be utilized to model complex objects, such as reconfigurable intelligent surfaces, or to solve optimization problems that require tracing the paths between one or more pairs of nodes. Moreover, DiffeRT2d adheres to numerous high-quality open-source standards, including automated testing, documented code and library, and Python type-hinting. | WG1,Sub-WG1.2 |
| TD(24)08035 | Maximilian Graber, Thomas Wilding, Benjamin J.B. Deutschmann, Klaus Witrisal | Geometry-based Environment Estimation and Modeling with Massive MIMO Channel Measurements | This paper deals with the extraction and modeling of geometric indoor environment features of massive MIMO indoor channels from real-world synthetic aperture array measurements. A model-based approach, utilizing floor-plan knowledge is compared to a parametric method without any available prior knowledge. The former estimates the channel components for single antenna elements with a best linear unbiased estimator, while the latter relies on sparse Bayesian learning estimates of sub-arrays with an additional Bayesian Gaussian mixture model data fusion step. The amplitudes of the specular channel components are extracted, stored and assigned to their reflection points by leveraging the mirror source model in order to build up a three-dimensional model of the environment. A compression algorithm, based on the discrete Fourier transform is developed to reduce the large data size caused by the high antenna count in the system and to represent the amplitudes over the wall segments. In a wireless power transfer setting, the predictive capabilities of the model are evaluated, showing that a performance gain in comparison to a geometric line-of-sight-only model is possible. | WG1,Sub-WG1.2,WG2 |
| TD(24)08036 | Anders Malthe Westerkam, Troels Pedersen | Clutter Tracking using Variational Message Passing | We propose a message passing algorithm for track- ing of clutter signals in MIMO radar. The method exploits basis expansion to linearise the signal model, to enable mean field approach for tracking the posterior distribution of the clutter as it evolves across time, as well as the mean and precision of the clutter map. The method shows good estimation accuracy in simulations for a scenario that adhere to the statistical model used for derivation as well as one that does not. The complexity of the method is linear in both the amount of parameters chosen and the amount of data under consideration. | WG2 |
| TD(24)08037 | Pasi Koivumäki, Ilona Virtaranta, Riku Ertimo | Seasonal and Local Weather Effects on User Signal Strengths Across a Mobile Network in Finland | In this work, we present an analysis of the effects of local weather and seasonal changes on the radio network owned by the Finnish telecommunications operator Elisa Oyj. The analysis is based on metrics reported by users across the network over a period of one year, resulting in some unintuitive observations. It is shown that during the winter, signal power received by users can be up to 7 dB higher than during the summer, depending on the frequency band. Based on analysis of weather data, we propose this is best explained by seasonal changes of absolute air humidity. We then monitor approximately 2000 routers with known locations connected to 200 base stations at 700 MHz and 3.5 GHz in a region of Finland over a period of 30 days. Based on changes in received power and local weather, we propose a distance and air humidity dependent loss at 3.5 GHz. | WG1 |
| TD(24)08038 | Nila Bagheri, Fernando J. Velez and Jon M. Peha | Advancements in High-Frequency Antenna Design: Integrating Photonic Crystals for Next-Generation Communication Technologies | Central to this study is the introduction of a pioneering photonic crystal-based microstrip patch antenna array with high gain. Engineered to meet the demands of evolving wireless communication technologies, this novel antenna system leverages Photonic Band Gap (PBG) structures. A fractal microstrip patch antenna, operating within the E-W-F band, is designed and simulated using the High-Frequency Structure Simulation (HFSS) software. With an operational frequency spanning 60.15 GHz to 120 GHz and a resonant band at 64.80 GHz, the antenna achieves a peak gain of 10.50 dBi within the obtained bandwidth. In this study, we selected Rogers RT/Duroid 5880 as the substrate material for our antenna, capitalizing on its unique properties to achieve superior functionality in high-frequency applications. One of the advantages of RT/Duroid 5880 is its exceptionally low dielectric constant (Ɛr = 2.2). This property is paramount for high-frequency antennas, as a lower dielectric constant facilitates improved signal propagation characteristics. The result is reduced signal loss and enhanced impedance matching, contributing to the overall efficiency of the antenna. The mechanical machinability of RT/Duroid substrates, including RT/Duroid 5880, adds another layer of advantage. The material can be easily cut, sheared, and machined to shape, streamlining the manufacturing process, and allowing for precise customization of the antenna design. In addition, by creating air hole in substrate reduce the dielectric constant, the introduction of air holes can decrease the effective dielectric constant of the material. As a lower dielectric constant results in a slower wave propagation speed, a reduction wavelength and a more compact antenna design may result. The presence of air holes or a photonic crystal structure can modify the electromagnetic properties of the substrate, potentially leading to enhanced bandwidth characteristics of broadband antennas. | WG1 |
| TD(24)08039 | Mostafa Rahmani, Junbo Zhao and Alister Burr | Simulation of cell-free massive MIMO in 5GNR | Most previous simulations of cell-free massive MIMO (CFmMIMO) have used a version of system-level simulation to calculate the distribution of SINR for each user, from which a mean throughput or throughput distribution has been calculated using the Shannon capacity formula. These simulations in effect assume flat fading channels between all users and all access points, with single carrier modulation. In this paper we discuss how CFmMIMO may be implemented and simulated for the 5G New Radio (5GNR) air interface. We give some initial simulation results for a simplified scenario giving plots of block error ratio (BLER) with different forms of CFmMIMO detection, compared with a baseline small cell system. | WG2 |
| TD(24)08040 | Ana Jeknic, Enis Kocan, Milica Pejanovic-Djurisic | Performance assesment of multi-link operation in WiFi 7 networks | The seventh generation of Wi-Fi standards is primarily designed to enable extremely fast transmission speeds and to minimize packet delays. Multi-link operation (MLO) plays a vital role in meeting these requirements. Using ns3 simulation tool, we examine MLO performance in the propagation scenario of a residential building, considering various number of users. The obtained results demonstrate that, when comparing the same total occupied bandwidth, the two-link MLO mode exhibits slightly better performance than single-link operation (SLO) mode. Furthermore, our findings indicate that MLO significantly reduces average packet delay, particularly in scenarios with large number of users. | WG2 |
| TD(24)08041 | Diego Dupleich, Jonas Gedshold, Alexander Ebert, Mate Boban | Early results on Doppler measurements inside Machines for ISAC in Industrial Scenarios at (sub-)THz. | This contribution brings to discussion and shows the early results on measurements of Doppler at (sub-)THz in industrial machines. The objective is to characterise propagation conditions for integrated sensing and communications. | WG1,Sub-WG1.1,VT3 |
| TD(24)08042 | Robin Byl, François Quitin | Propagation and performance analysis of 5G communications in maritime environments | The increasing demands for ubiquitous wireless communications has led to multiple new communication scenarios, such as satellite links, maritime networks and Massive Machine-Type Communications. In this work, we investigate the use of 5G New Radio (NR) radio access networks for maritime communication networks. More specifically, this paper aims at evaluating 5G capabilities in maritime environments by investigating the propagation mechanisms that predominate in over-the-sea channels. Our study compares different existing propagation models for over-the-sea wireless channels, emphasizing on the Frequency Range 1 (FR1) of 5G communications (i.e. sub-6 GHz carrier frequencies). We propose an augmented model, based on the classical 2-rays model, which has already been observed in experimental evaluations of maritime communications. We enrich the 2-ray model by i) taking into account the evaporation duct (leading to a 3-ray model), ii) including the attenuation due to rainy weather, iii) modifying the reflection coefficient on the sea to account for sea waves (thereby drawing the link to meteorological conditions), and iv) taking into account the curvature of the earth. We validate our augmented model by comparing it to experimental data collected in the Belgian North Sea. The measurements are collected by considering an LTE eNodeB placed on an offshore wind farm and a UE placed aboard a ship navigating through the North Sea. Finally, we use the developed model in order to have an estimation of maximal achievable datarates based on 5G standard and different configurations in a maritime communication scenario. | WG1 |
| TD(24)08044 | Marina Barbiroli, Vittorio Degli Esposti, Andrea Garzia, Simona Valbonesi, Paolo Grazioso, Luís M. Correia, Custódio Peixeiro, Bernardo Galego | Exposure compliance evaluation for active antennas and RIS in 5G+ | This paper addresses Electromagnetic Field (EMF) exposure evaluation techniques in Fifth Generation (5G) and in forthcoming future generation mobile networks in general. The problem of estimating exposure and of determining exclusion zones has been massively investigated since the advent and the widespread diffusion of mobile phones (and subsequently of other mobile devices) in the last decades of the 20th Century. However, the advent of 5G brought about many new technological solutions and concepts, like beamforming, active antennas, massive MIMO, Reconfigurable Intelligent Surfaces (RISs), etc. which require new and more advanced exposure evaluation techniques respect to the traditional evaluation methods suitable for former generation networks. This need for advanced exposure evaluation methods will become even more stringent with the evolution of 5G and with the forthcoming advent of 6G and future generations. In this paper we present some preliminary evaluations of exposure in real environments, using ray-tracing simulations of a real 5G active antenna in selected scenarios, as well as evaluations, also by simulation, of the near field region of RISs. The achieved results, though preliminary, are encouraging and further advancements and evolutions of these activities have already been planned for the forthcoming months. | Sub-WG1.2,Sub-VT1 |
| TD(24)08045 | Chathuri Weragama, Joonas Kokkoniemi, Mar Francis De Guzman, Katsuyuki Haneda, Pekka Kyösti, and Markku Juntti | Characterization of Spatial-Temporal Channel Statistics from Indoor Measurement Data at D Band | Millimeter-wave (mmWave) and D Band (110-170 GHz) frequencies are poised to play a pivotal role in the advancement of sixth-generation (6G) systems and beyond, owing to their ability to enhance performance metrics such as capacity, ultra-low latency, and spectral efficiency. This paper concentrates on deriving statistical insights into power, delay, and the number of paths based on measurements conducted across four distinct locations at a center frequency of 143.1 GHz. The findings underscore the suitability of various distributions in characterizing power behavior in line-of-sight (LOS) scenarios, including lognormal, Nakagami, gamma, and beta distributions, whereas the loglogistic distribution gives the optimal fit for power distribution in non-line-of-sight (NLOS) scenarios. Moreover, the exponential distribution shows to be the most appropriate model for the delay distribution in both LOS and NLOS scenarios. In terms of the number of paths, observations indicate a tendency for the highest concentration within the 10 m to 30 m distance range between the transmitter (Tx) and receiver (Rx). These insights shed light on the statistical nature of D band propagation characteristics, which are vital for informing the design and optimization of future 6G communication systems. | WG1,Sub-WG1.1 |
| TD(24)08046 | Greta Vallero, Michela Meo | Microgrid for Radio Access Network Resilience | The consistent growth in electricity demand, coupled with factors such as political instability, cyberattacks, and the rising frequency of natural disasters due to the climate crisis, poses challenges to the reliability and consistency of the power grid supply. The malfunctioning of the power grid, in turn, has a cascading effect on the communication infrastructure, which heavily relies on the stability of the electricity grid. Despite this, enhancing the resilience of computing and communication facilities is fundamental. Their crucial role in supporting essential aspects of our daily lives requires ensuring their continuous and dependable operation. To cope with this, in this work, we view a group of Base Stations (BSs) of a Radio Access Network (RAN) as consumers within a Microgrid (MG), each equipped with a Photovoltaic (PV) Panel and interconnected through dedicated power cables to exchange their generated energy. We introduce a RAN resource and energy management, that, during a Power Grid Outage (PGO), aims at keeping active the most loaded BSs, given the available generated energy within the MG. We evaluate the impact of the number of BSs in the MG, the PV Panel capacity, the duration of the PGOs and the BS traffic shape profiles, formalizing also the required setting which guarantees the efficacy of our methodology. Results reveal that the performance achieved with PV Panels not exceeding 6 kWp is comparable to that of larger PV Panels (up to 12 kWp), if the MG and the RAN resource management are implemented, making our solution feasible in terms of installation space requirements and increasing the hourly served traffic up to 300%. | WG3,VT4 |
| TD(24)08047 | Yingjie Xu, Michiel Sandra, Xuesong Cai, Sara Willhammar, Fredrik Tufvesson | Spatial separation of closely-spaced ssers in measured distributed massive MIMO channels | Aiming for the sixth generation (6G) wireless communications, distributed massive multiple-input multiple-output (MIMO) systems hold significant potential for spatial multiplexing. In order to evaluate the ability of a distributed massive MIMO system to spatially separate closely-spaced users, this paper presents an indoor channel measurement campaign. The measurements are conducted at a carrier frequency of 5.6 GHz with a bandwidth of 400 MHz, employing distributed antenna arrays with a total of 128 elements. Multiple scalar metrics are selected to evaluate the spatial separability in line-of-sight (LoS), non-LoS (NLoS), and mixed conditions. Firstly, through studying the singular value spread (SVS), it is shown that in LoS condition, better user orthogonality is achieved with a distributed MIMO setup compared to a co-located MIMO array. Furthermore, the dirty-paper coding (DPC) capacity and zero forcing (ZF) precoding sum-rate capacities are investigated across varying number of antennas and their topologies. Results show that in all three conditions, the less complex ZF precoder can be applied in distributed massive MIMO systems while still achieving a large fraction of the DPC capacity. Additionally, in LoS conditions, both sum-rate capacities and user fairness benefit from more antennas and a more distributed antenna topology. However, in the given NLoS condition, the improvement on spatial separability brought by distributed antenna topologies is limited. | WG1,WG2 |
| TD(24)08048 | Rizqi Hersyandika, Yang Miao, Sofie Pollin | Guard Beam: Protecting mmWave Communication through In-Band Early Blockage Prediction | Human blockage is one of the main challenges for mmWave communication networks in dynamic environments. The shadowing by a human body results in significant received power degradation and could occur abruptly and frequently. A shadowing period of hundred milliseconds might interrupt the communication and cause significant data loss, considering the huge bandwidth utilized in mmWave communications. An even longer shadowing period might cause a long-duration link outage. Therefore, a blockage prediction mechanism has to be taken to detect the moving blocker within the vicinity of mmWave links. By detecting the potential blockage as early as possible, a user equipment can anticipate by establishing a new connection and performing beam training with an alternative base station before shadowing happens. This paper proposes an early moving blocker detection mechanism by leveraging an extra guard beam to protect the main communication beam. The guard beam is intended to sense the environment by expanding the field of view of a base station. The blockage can be detected early by observing received signal fluctuation resulting from the blocker’s presence within the field of view. We derive a channel model for the pre- shadowing event, design a moving blockage detection algorithm for the guard beam, and evaluate the performance of the guard beam theoretically and experimentally based on the measurement campaign using our mmWave testbed. Our results demonstrate that the guard beam can extend the detection range and predict the blockage up to 360 ms before the shadowing occurs. | Sub-WG2,HA2 |
| TD(24)08049 | Peize Zhang, Veikko Hovinen, Xuesong Cai, Marko E. Leinonen, Aarno Pärssinen, Fredrik Tufvesson, and Pekka Kyösti | Sub-Terahertz Dual-Band Channel Measurements and Characterization in Industrial Environments | Sub-Terahertz (sub-THz) communications are very promising to cope with the tight requirements of industrial Internet of Things (IIoT) application, such as extremely low latency and high reliability. In this TD, we present the results of two sub-THz channel measurement campaigns conducted in factory hall and warehouse at both 234 GHz and 318 GHz. The dual-band channel data was collected using the same channel sounder hardware at identical transceiver locations, which enables fair comparison of sub-THz frequency dependent channel characteristics. We primarily focus on the analysis of large-scale channel fading including path loss and shadowing, as well as time dispersion. | WG1,Sub-WG1.1 |
| TD(24)08050 | Javier Gómez, José Jaime Camacho-Escoto, Luis Orozco-Barbosa and Diego Rodríguez Torres | PROFEE: A Probabilistic-Feedback Based Speed Rate Adaption for IEEE 802.11bc | WiFi is a widely used wireless technology for data transmission. WiFi can also play a crucial role in simultaneously broadcasting content to multiple devices in multimedia transmission for venues such as classrooms, theaters, and stadiums, etc. Broadcasting allows for the efficient dissemination of information to all devices connected to the network, and it becomes crucial to ensure that the WiFi network has sufficient capacity to transmit broadcast multimedia content without interruptions or delays. However, using WiFi for broadcasting presents challenges that can impact user experience, specifically the difficulty of obtaining real-time feedback from potentially hundreds or thousands of users due to potential collisions of feedback messages. This work focuses on providing accurate feedback to the Access Point about the percentage of users not receiving broadcast traffic correctly so it can adjust its Modulation and Coding Scheme (MCS) while transmitting broadcast multimedia content to many users. The proposed method is comprised of two sequential algorithms. In order to reduce the probability of a collision after transmitting each message, an algorithm searches for the best probability value for users to transmit ACK/NACK messages, depending on whether messages are received correctly or not. This feedback allows the Access Point to estimate the number of STAs correctly/incorrectly receiving the messages being transmitted. A second algorithm uses this estimation so the Access Point can select the best MCS while maintaining the percentage of users not receiving broadcast content correctly within acceptable margins, thus providing users with the best possible content quality. We implemented the proposed method in the ns-3 simulator, and the results show it yields quick, reliable feedback to the Access Point that was then able to adjust to the best possible MCS in only a few seconds, regardless of the user density and dimensions of the scenario | WG3 |
| TD(24)08051 | Kimmo Kansanen, Jenny Aune Forbord, Johan Suarez | Bayesian range estimation for Bluetooth | Two-way phase measurements over multiple frequencies can be used to measure the range between two radios. An unknown phase offset on each measured frequency between the two radios must be accomodated by the estimator. We coonsider a single-path propagation channel, and derive a maximum a posteriori estimator for the range from first principles by treating the unknown phase as a nuisance parameter. We analyse the behavior of the estimation metric, and find its local maxima and minima. Under high signal-to-noise ratio, we demonstrate the estimator provides sub-wavelength accuracy. | WG2 |
| TD(24)08052 | Tran Tra My, Janos Bito, BME, Hungary | MICROWAVE PROPAGATION INVESTIGATIONS IN RESPECT OF CLIMATE CHANGE | The local and global weather conditions are changing due to natural and artificial influences such as pollution and emissions of the manufacturing industry, generally called Climate change. The occurrence of extreme meteorological events has increased throughout the years. The main goal of the current work is to investigate the influence of climate change on wireless wave propagation at higher frequencies using the rain fade duration statistics. These statistics are derived from 10-year measurements of a satellite (ALPHASAT) link operating at Ka-band (19.701 GHz). In this work, the study focuses on the investigation of rain fade duration statistics at different fading levels (3, 5, 10, 15, and 20 dB, respectively). A comparison of measured statistics is presented using the MATLAB simulation environment to investigate changes in fade duration through the years. | WG1 |
| TD(24)08053 | Mar Francis De Guzman and Katsuyuki Haneda | Ray-launcher Calibration Using Sub-THz Channel Measurements | In this paper, an in-house ray-launcher tool is calibrated using sub-THz channel measurements. The calibration is based on the use of multipath data obtained from directional channel measurements performed in an entrance hall environment. It presents the ray-launching process accounting propagation mechanisms such as reflection, transmission, and diffraction. Simplification of the 3-dimensional mesh model of the physical environment is discussed. The captured paths from ray-launching were filtered by comparing them with the measured paths. The path losses of the measured and simulated links are then optimized by sweeping the relative permittivity of the objects. Some initial results of this calibration process are also presented in this paper. | WG1,Sub-WG1.1 |
| TD(24)08054 | Bashar Husain, Kevin Kolpatzeck, Lars Häring, and Andreas Czylwik | Volterra-Based Machine Learning Compensation of Non-Linear Distortions in an Optoelectronic Terahertz Communication System | This paper presents a new approach based on machine learning (ML) to estimate the third-order Volterra series kernel for an optoelectronic Terahertz (THz) communication system. The ML consists of an optimizer and a Volterra series, where a two-tone signal is utilized for the learning process. In addition, an analytical digital predistortion (DPD) system that represents the inverse model of the THz system is calculated and utilized for the system linearization. Simulation results reveal that the proposed ML approach can effectively estimate the third-order kernel of the system. The DPD performance is evaluated and compared to the theoretical upper limit in the case of a known system model. Moreover, simulation results show that the DPD has a good performance and can effectively suppress the power of third-order intermodulation products. | WG2 |
| TD(24)08055 | Miled Alam, Abdul Karim Gizzini, Laurent Clavier | A Deep Learning-Based Approach to Secure Transmission in Multi-User NOMA Systems | Deep learning (DL) algorithms have been widely integrated in various aspects of wireless communications research. In this paper, we investigate the secrecy energy-efficiency (SEE) of a multi-user downlink non-orthogonal multiple access (NOMA) system in the presence of a passive eavesdropper based on a DL approach. Hence, we formulate the convex optimization problem as maximizing the SEE defined as the trade-off between the secrecy sum-rate and the power budget. Notably, this optimization problem has been recently solved in a closed form. The solution can also be utilized to efficiently maximize the ratio between the secrecy sum-rate and power consumption, requiring only a line search. This approach is then used to generate training, validation, and test datasets. Our method relies on a deep neural network designed for resource allocation. The benefits of using a deep neural network include achieving optimal resource allocation results while minimizing complexity and latency. The results presented in this paper highlight the superiority and efficacy of DL optimization compared to traditional iterative search methods. | WG2,HA1,HA3 |
| TD(24)08056 | Pyry Kiviharju, Nam Ha-Van, Zachary Taylor, Clemens Icheln, Katsuyuki Haneda | Coexisting Microwave and Optical Component for Wireless Capsule Endoscopy – A Feasibility Study by Radio Link Analysis | Wireless capsule endoscopy (WCE) is one of the few options for small intestine disease diagnosis. The small size of the capsule poses a major design challenge for engineers. This article proposes a space saving solution of integrating antenna into a hybrid component which can be used as an optical component in a dual-viewing imaging system as well as an antenna in microwave wireless data transmission. In this paper we concentrate on the hybrid component’s microwave operation. Operation is studied by conducting a full wave radio link simulation, where the link gain is used as a performance metric. The results show that the hybrid component has potential to operate as an antenna. | VT1 |
| TD(24)08057 | Silvi Kodra, Jiaohao Hu, Elena Bernardi, Nicolò Cenni, Marina Barbiroli, Enrico M. Vitucci, Franco Fuschini, Sana Salous , Vittorio Degli-Esposti | MM-WAVE AND SUB-THZ CHARACTERIZATION OF VARIOUS BUILDING MATERIALS | Millimeter wave (mmWave) and sub-THz communication systems promise high data rates and low latency but face challenges in obstructed indoor environments. Effective coverage planning requires understanding how different frequencies interact with indoor structures and materials, considering factors such as transmission, reflection, and scattering. This study investigates the attenuation characteristics of common building materials at 25.6 GHz, 28 GHz, 38 GHz, 77 GHz, and 153 GHz. Utilizing experimental measurements for penetration loss, along with ray-tracing simulations for scattering, we provide comprehensive insights into material attenuation. These findings aim to support the design and optimization of future communication systems and assist in calibrating wireless planning simulators. | Sub-WG1.1 |
| TD(24)08059 | Martin Murko, Aleš Simončič, Andrej Hrovat, Teodora Kocevska, Luka Zmrzlak, Tomi Mlinar, Boštjan Batagelj, Tomaž Javornik, Grega Morano | Evaluation of Cost-Effective UWB Technology for Accurate Indoor CIR Measurements | Low-cost ultra-wideband (UWB) technology can estimate the channel impulse response (CIR) for novel environmental sensing solutions, supporting adaptive, environmentally aware, and robust wireless networks. This paper assesses the accuracy and reliability of CIR estimates obtained with off-the-shelf UWB devices compared to Vector Network Analyzer (VNA) measurements. The experimental evaluation included collecting and analyzing the data obtained with UWB and VNA methods in a controlled indoor environment. The focus is on investigating the reliability and precision of UWB in detecting multipath components and estimating CIR. The study shows that the accuracy of the CIR measured with UWB is comparable with VNA measurements and confirms the potential of UWB as a cost-effective approach for accurate CIR measurements in novel sensing solutions. | WG1 |
| TD(24)08061 | Aleš Simončič, Ke Guan, Aleš Švigelj, Grega Morano, Tomaž Javornik, Andrej Hrovat, Teodora Kocevska | Performance Evaluation of CFO-resilient Switching Patterns for Accurate DoA Estimation | Direction of Arrival (DoA) estimation accuracy is degraded in single RF chain systems due to non-simultaneous signal sampling and the adverse impact of carrier frequency offset (CFO). The conventional approaches based on CFO estimation and correction to mitigate the estimation errors are intensive for the computationally restricted and low-cost devices deployed in Internet of Things (IoT) networks. In this paper, we propose exploiting the switching patterns used for sampling the signal at the antenna to mitigate the CFO effect and estimate the DoA with high accuracy. We define and evaluate the effectiveness of a switching pattern obtained based on the center of gravity where the phase progressions due to CFO are modeled as weights and a mirror switching pattern. To analyse the performance and evaluate the effectiveness of the proposed solution, a signal model is proposed, and MATLAB simulations are performed considering uniform linear and circular arrays and the MUSIC algorithm. The impact of Signal-to-Noise-Ration (SNR), DoA, and CFO on the performance is evaluated and discussed. Close to zero DoA estimation error can be achieved with both switching pattern methods. The effectiveness is limited with a high-frequency CFO bound, after which the performance drops. The conclusions are confirmed with measurements-based evaluation considering a uniform linear array. | WG2 |
| TD(24)08062 | Dino Pjanić, Korkut Emre Arslantürk, Xuesong Cai, Fredrik Tufvesson | Dynamic UE grouping based on Location and Heading in 5G NR System | User grouping based on geographical position in the fifth-generation (5G) new radio (NR) system has several applications that can significantly enhance general network performance, user experience, and service delivery. We demonstrate how to utilize sounding reference signals (SRS) channel fingerprints for dynamic UE grouping in a commercial environment based on outdoor positions and heading direction utilising machine learning (ML) methods such as deep neural networks (DNN) combined with clustering methods. | WG1,WG2 |
| TD(24)08063 | Radovan Zentner | Improving Isotropy of 3-Axes Sensor for Standardized EMF Measurements | In this document a straightforward method is proposed that can improve isotropy of typical 3-axes E-field sensors for EMF measurements. The method is based on simple post processing of commonly obtained EMF measurement data. For implementing the method, the 3-D radiation pattern of the sensor must be known in advance which is easily obtained in any state-of-the-art anechoic chamber. As isotropy contributes to uncertainty of EMF measurements such as described in IEC 62232:2022 standard, this method can be a useful tool for reducing uncertainty of such measurements. | VT1,Sub-VT1 |
| TD(24)08064 | N. Cenni, V. Degli-Esposti, E. M. Vitucci, F. Fuschini, M. Barbiroli | RAY TRACING BASED ANALYSIS OF SATELLITE TO URBAN PROPAGATION | Non-Terrestrial Networks (NTNs) are expected to play a crucial role in future 6G wireless networks, enhancing global connectivity and performance in conjunction with terrestrial networks. To effectively design and deploy NTNs, it is essential to accurately characterize the satellite-to-ground channel, especially in urban environments. This paper employs Ray Tracing to assess the fading and dispersion properties of the wireless channel across different types of urban settings. After a thorough tuning phase to optimize Ray Tracing parameters for the specific application case, results are analyzed and compared to the 3GPP model | WG1 |
| TD(24)08065 | Dheeraj R. Kumar, Carles Antón-Haro, Xavier Mestre | Performance-Complexity Tradeoff Analysis for MIMO Channel Estimation: GNN vs. CNN Architectures | Graph Neural Networks (GNNs) are gaining popularity to solve wireless communication problems due the inherent nature of viewing wireless networks as graphs. In this paper, we investigate the potential of using GNN for channel estimation in point-to-point multi-input and multi-output (MIMO) systems. The analysis includes an assessment of the channel estimation error performance alongside the computational complexity associated to the training and inference phases. The performance is compared against benchmarks such as the conventional least squares , (linear) MMSE estimators, and shallow 1D convolutional neural network (1D-CNN) architectures from the literature. We evaluate the peformance-complexity tradeoff of GNN versus shallow 1D-CNN which have been shown to outperform deep architectures for MIMO channel estimation. | WG2 |
| TD(24)08067 | Slawomir J. Ambroziak, Olga Korostynska, Nila Bagheri, Conception Garcia Pardo, Tamara Skoric, Charalambos Sergiou, Sergio Castello Palacios, Konstantinos Katzis, and Pawel Kulakowski | A Joint Initiative Coming From VT1: A Survey on Communication With In-Body Medical Devices | This document reports an ongoing work undertaken by a group of researchers from INTERACT VT1, being a survey on communications with in-body medical devices. First, implantable and ingestible medical devices are discussed, focusing on their capabilities for health monitoring in the context of personalized medicine. Then, a complete architecture of the personalized healthcare system is presented, together with possible scenarios of communication between the system components. The next sections deal with antennas, frequency bands, and wireless links suitable for these types of communications. Then, modulation techniques for in-body communication are described, also specifying the respective power consumption and achievable data rates. This is followed by a discussion on security issues for in-body networks. In the next section, the electromagnetic field influence on human tissues is addressed, together with safety guidelines that in-body devices must meet. Finally, current standardization efforts related to in-body communications are reviewed. | VT1 |
| TD(24)08068 | Conor Brennan, Allan Wainaina Mbugua, Yun Chen, Sajjad Hussain | Interpolation of Reflected and Diffracted Rays for Accelerated Ray Tracing Simulation | The problem of efficiently computing an image-based ray-trace for a receiver moving along a linear trajectory in an urban area is considered. The requirement to sample channel information at the Nyquist rate or higher imposes a considerable computational burden. The proposed algorithm instead makes use of the fact that such receivers will move in and out of well-defined finite illumination regions within which reflected and diffracted rays can potentially propagate. Rather than computing an independent ray trace for each receiver location within such regions a simple model for the associated ray is created. This model is based on field information computed at a finite set of locations within the region which is then interpolated to efficiently give amplitude and phase data along the trajectory. The TD examines the effectiveness of this operation within a simulated street canyon environment and examines how the accuracy and efficiency depends on the interpolation scheme employed. | WG1,VT2 |
| TD(24)08069 | Juan Sanchez, Ali Al-Ameri, Xuesong Cai, Fredrik Tufvesson | Low-Complexity, Near-Optimal Switching Schemes for Dynamic Channel Sounding | Channel sounding is essential for the design of communication systems, and a proper characterization of the environment in which signals are propagating can play a crucial role in maximizing overall system performance. Switched-array sounding is one of the most popular choices in channel sounding, and the design of switching sequences is decisive for the parametric estimation performance of the sounder. Sequence optimization can be a very computationally intensive task when the number of antenna pairs grows, as is the trend with massive multiple-input-multiple-output systems employed in modern communications. This paper provides a novel and comprehensive analysis of the design of the switching sequence from multiple points of view. First, a study that incorporates multiple polarization pairs when optimizing sequences with the help of the so-called spatio-temporal ambiguity function. Second, an analysis of the combinatorial aspect of switching sequences that proposes an alternative and faster design approach than the one based on the ambiguity function. We call this approach Fourier-Fisher, since the optimization procedure is based on the Fourier spectrum of sequences and the Fisher information matrix associated with the parametric estimation problem. The results show that the performances of both ambiguity and Fourier-Fisher design approaches are identical and that the Fourier-Fisher approach is computationally less intensive, achieving convergence and near-optimal results in orders of magnitude less time than the ambiguity approach. | Sub-WG1.1 |
| TD(24)08070 | Juha-Matti Runtti, Usman Virk, Pekka Kyösti, Lassi Hentilä, Jukka Kyröläinen, Fengchun Zhang | FR3 Measurement-Based 3GPP-Like Channel Model for an Industrial Environment | 6G radio access architecture is envisioned as a network of short-range in-X subnetworks with enhanced capabilities to provide efficient and reliable wireless connectivity. Short-range communications in industrial environments are actively researched at the so-called mid-bands or FR3, e.g., in the European Union SNS JU 6G-SHINE project. In this TD, we analyze the omni-directional radio channel measurements at 10–12 GHz frequency band to estimate large-scale channel characteristics including power-delay profile, delay spread, K-factor, and pathloss for 254 radio links measured in the Industrial Production Lab at Aalborg University, Denmark. Moreover, we present a non-stationary dynamic channel model developed based on the estimated parameters from the measurements and the directional parameters complemented by the 3GPP Indoor Factory channel model. | WG1 |
| TD(24)08071 | Michiel Sandra, Robert Pöhlmann, Markus Wirsing, Ronald Raulefs, Anders J Johansson | Leveraging the Two-Ray Model for C-band Ranging in Maritime Applications | We propose a novel ranging algorithm that can be utilized for positioning in maritime applications when the global navigation satellite system (GNSS) is unreliable or faulty. Our algorithm is based on the extended Kalman filter and utilizes channel measurements from a large vertical antenna array at the shore to estimate the range to a vessel. Because of the two-ray propagation environment at sea, range information is embedded in the amplitude and phase differences among the antennas. Other ranging methods such as time-of-arrival, which are solely based on delay measurements, require accurate time synchronization. With our algorithm, this requirement is alleviated by also utilizing the range information provided by the two-ray model. An essential part of our algorithm includes continuous over-the-air calibration of the hardware contributions to the measured channel. The algorithm has been verified by channel measurements between a sailboat and a vertical array ashore. In our evaluation, we considered a scenario where ranging is performed during a 30-minute period after a simulated GNSS failure. The results show an RMSE of 2.1 meters for distances between 700 m and 2800 m. | WG2 |
| TD(24)08072 | Flor Ortiz, Juan A Vasquez-Peralvo, Jorge Querol, Eva Lagunas, Jorge L González Rios, Marcele OK Mendonça, Luis Garces, Symeon Chatzinotas | Supervised Learning Based Real-Time Adaptive Beamforming On-Board Multibeam Satellites | Satellite communications (SatCom) are crucial for global connectivity, especially in the era of emerging technologies like 6G and narrowing the digital divide. Traditional SatCom systems struggle with efficient resource management due to static multibeam configurations, hindering quality of service (QoS) amidst dynamic traffic demands. This paper introduces an innovative solution – real-time adaptive beamforming on multibeam satellites with software-defined payloads in geostationary orbit (GEO). Utilizing a Direct Radiating Array (DRA) with circular polarization in the 17.7 – 20.2 GHz band, the paper outlines DRA design and a supervised learning-based algorithm for on-board beamforming. This adaptive approach not only meets precise beam projection needs but also dynamically adjusts beamwidth, minimize | WG3 |