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Evgenii Vinogradov

Publications and source records attributed to Evgenii Vinogradov.

At least 19 recordsLinked to original sources

UPSim: UxNB Propagation Simulator for 3D Map-Driven FR3 Deployments

We introduce UPSim (UxNB Propagation Simulator), an open-source, Ray Tracing-calibrated solution for spatially consistent FR3 (16.95 GHz) air-to-ground propagation modeling in Uncrewed Aerial Vehicle (UAV) networks. Instead of executing point-to-point ray launches for every ground position, UPSim derives deterministic visibility regions directly from global 3D building geometry (3D-GloBFP) via fast shadow projection. It then augments these regions with Line-of-Sight (LOS) state-specific, UAV height- and distance-dependent path loss, spatially correlated large-scale fading, and log-logistic small-scale fading parameterized by over 136 million Ray Tracing (RT) channels. Validation against reference RT data demonstrates that UPSim accurately reproduces empirical attenuation maps, outperforming the 3GPP baseline by reducing the aggregate Kolmogorov-Smirnov distance from 0.33 to 0.04. The resulting maps enable route-based analysis of channel evolution in complex urban layouts, capturing critical trajectory-level metrics such as spatial outage persistence. Consequently, UPSim provides a highly scalable, open-source middle ground between computationally expensive full RT and purely stochastic models for mobility-aware 6G aerial network planning.

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Reinforcement Learning-Based 3D Beam Adaptation for Underwater Wireless Optical Communication with AUVs

Underwater Wireless Optical Communications (UWOC) provide essential high data rates for Autonomous Underwater Vehicles (AUVs), but reliable connectivity is critically affected by transmitter-receiver misalignment. This work addresses the beam pointing problem for a moving AUV subject to unknown ocean currents through a Deep Reinforcement Learning (DRL) framework. We develop a comprehensive 3D UWOC channel model incorporating depth-dependent attenuation, turbulence, and a discrete-ray method to accurately quantify geometric and misalignment losses. The resulting agent jointly optimizes beam steering and divergence angles, learning a policy that prioritizes continuous link maintenance. Evaluated using real oceanographic data, the framework's performance is assessed via the excess outage metric, which isolates outages occurring exclusively due to pointing errors. Relative to perfect alignment between nodes, the proposed method bounds this metric to 8.5% under ocean current-free tracking conditions and limits it to 16.2% when subjected to current-induced drift. The findings obtained in this work confirms that DRL-enabled beam control is capable of adaptive tracking and mitigating link outages in dynamic underwater environments.

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Channel Knowledge Maps for FR3 UAV Base Stations: Dataset and ML-based Modeling

This paper introduces a dense upper mid-band Frequency Range (FR3) Channel Knowledge Map (CKM) dataset for Uncrewed Aerial Vehicles (UAVs) with an on-board base station (UxNB). It contains 16,180 CKM samples from 3,236 urban locations in 66 cities at 7.125 GHz and UxNB heights of up to 500 meters. Every 513x513 sample stores the building geometry, the line-of-sight (LOS) state, attenuation, delay spread, angular spread, and variable transmitter height. As a focused first use-case, we propose an interpretable height-aware attenuation model. Its LOS branch combines free-space loss, two-ray term, and compact data-based height/range calibration. Its non-LOS (NLOS) branch combines a COST 231-Hata basis with local environment-specific linear calibration. The proposed model reaches 1.93 dB overall root mean square error, with 1.74 dB in LOS and 3.54 dB in NLOS on over 500 unique locations in 14 unseen cities (2,590 samples in total). The result provides attenuation data for FR3 UxNB deployments and a physical anchor for future FR3 modeling efforts.

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Millimeter-Wave UAV Channel Model with Height-Dependent Path Loss and Shadowing in Urban Scenarios

Uncrewed Aerial Vehicles (UAVs) serving as Aerial Base Stations (ABSs) are expected to extend 6G millimeter-Wave (mmWave) coverage and improve link reliability in urban areas. However, UAV-based Air-to-Ground (A2G) channels are highly dependent on height and urban geometry. This paper proposes an ABS height-dependent mmWave channel model and investigates whether urban geometry, beyond the standard built-up parameters, significantly affects LoS probability (PLoS) and Large-Scale Fading (LSF). Using MATLAB ray tracing at 26 GHz, we simulate approximately 10K city realizations for four urban layouts that share identical built-up parameters but differ in their spatial organization. We extract elevation-based PLoS using a sigmoid model and derive height-dependent Path-Loss Exponents (PLEs) and shadow-fading trends using exponential fits. Results show that PLE for Non-Line-of-Sight (NLoS) decreases toward 2.5-3 at high altitudes, Line-of-Sight (LoS) PLE remains near 2, and shadow fading reduces with height. We also find that geometric layout introduces a modest but consistent change in PLE (+/- 0.2), even when built-up parameters are fixed. The proposed unified model aligns well with ray-tracing statistics and offers a practical, height-dependent LSF model suitable for ABS planning in complex urban scenarios.

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Corridor Design and Separation Definition in Advanced Air Mobility: Systematic Literature Review

Advanced Air Mobility (AAM) uses electric vertical take-off and landing (eVTOL) vehicles to address urban congestion and emissions. However, corridor design, operation management, and separation standards remain underexamined for safe high-density operations. This paper applies the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically review relevant literature from IEEE Xplore and Web of Science, focusing on publications from 2010 to 2024. A Context, Intervention, Mechanism, and Outcome (CIMO) framework guided the development of research questions. After screening 2,039 journal and conference papers, 62 articles met the inclusion criteria. The findings reveal a lack of integrated corridor design approaches, limited operational strategies, and reliance on standards originally designed for conventional aviation. A unified corridor design and separation definition frameworks and taxonomies are proposed to address these shortcomings, informing future investigations and operational frameworks for safe, efficient eVTOL operation deployment in urban settings.

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Transmitter Noise Propagation in Millimeter-Wave and Sub-Terahertz: From Limits to Design Guidelines

This paper presents a comprehensive link budget analysis for millimeter wave (mm-Wave) and sub-Terahertz (sub-THz) communication systems with primary focus on transmitter (TX) noise propagation, an often overlooked impairment that can dominate in scenarios where path loss is insufficient to suppress TX noise below receiver thermal and atmospheric molecular noise levels. Unlike traditional thermal noise limited analyses, this work demonstrates that TX noise is amplified by component noise figures that degrade significantly with frequency, rising from single digits to more than $15\,\mathrm{dB}$ in the sub-THz range. In the scenarios analyzed, this propagated TX noise reduces the achievable Signal-to-Noise Ratio (SNR) by approximately $15$ to $25\,\mathrm{dB}$ at short distances, creating fundamental SNR ceilings at ranges below about $10\,\mathrm{cm}$. We develop a systematic framework quantifying TX noise dominance conditions as functions of distance, frequency, and component parameters, revealing fundamental performance constraints for short-range next generation wireless systems. Our findings indicate that the TX noise figure should be as low as possible for short-range communication, and both TX noise and atmospheric molecular noise should be considered for medium- and long-range links.

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Cryo-CMOS Antenna for Wireless Communications within a Quantum Computer Cryostat

Scaling quantum computers from a few qubits to large numbers remains one of the critical challenges in realizing practical quantum advantage. Multi-core quantum architectures have emerged as a promising solution, enabling scalability through distributed quantum processing units (QPUs) interconnected via classical and quantum links. However, the bottleneck of wired connections persists, as densely packed wired interconnects, both vertically across temperature stages and horizontally within the same layer, introduce spatial constraints, power dissipation, and latency, which could hinder performance as the number of QPUs increases. To overcome these limitations, this work proposes a cryo-compatible on-chip differential dipole antenna operating at 28 GHz to enable short-range wireless communication within a quantum computer cryostat. Temperature-dependent material properties are incorporated to accurately capture antenna behavior at 4 K. Moreover, by embedding the antenna in a realistic cryostat structure, we evaluate the feasibility of antenna operation within the cryogenic environment. The proposed antenna achieves a reflection coefficient of -20.8 dB in free space and -18.38 dB within the cryostat, demonstrating efficient impedance matching.

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Towards Scalable Multi-Chip Wireless Networks with Near-Field Time Reversal

The concept of Wireless Network-on-Chip (WNoC) has emerged as a potential solution to address the escalating communication demands of modern computing systems due to its low-latency, versatility, and reconfigurability. However, for WNoC to fulfill its potential, it is essential to establish multiple high-speed wireless links across chips. Unfortunately, the compact and enclosed nature of computing packages introduces significant challenges in the form of Co-Channel Interference (CCI) and Inter-Symbol Interference (ISI), which not only hinder the deployment of multiple spatial channels, but also severely restrict the symbol rate of each individual channel. In this paper, we posit that Time Reversal (TR) could be effective in addressing both impairments in this static scenario, thanks to its spatiotemporal focusing capabilities even in the near-field. Through comprehensive full-wave simulations and bit error rate analysis in multiple chip layouts with multiple frequency bands, we provide evidence that TR can increase the symbol rate by an order of magnitude, enabling the deployment of multiple concurrent links and achieving aggregate speeds exceeding 100 Gb/s. Finally, we evaluate the impact of reducing the sampling rate of the TR filter on the achievable speeds, paving the way to practical TR-based wireless communications at the chip scale.

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28 GHz Wireless Channel Characterization for a Quantum Computer Cryostat at 4 Kelvin

The scalability of quantum computing systems is constrained by the wiring complexity and thermal load introduced by dense wiring for control, readout and synchronization at cryogenic temperatures. To address this challenge, we explore the feasibility of wireless communication within a cryostat for a multi-core quantum computer, focusing on wireless channel characterization at cryogenic temperatures. We propose to place on-chip differential dipole antennas within the cryostat, designed to operate at 28 GHz in temperatures as low as 4 K. We model the antennas inside a realistic cryostat and, using full-wave electromagnetic simulations, we analyze impedance matching, spatial field distribution, and energy reverberation due to metallic structures. The wireless channel is characterized through measured channel impulse response (CIR) across multiple receiver antenna positions. The results demonstrate potential for reliable shortrange communication with high Signal-to-Noise Ratio (SNR) and limited sensitivity to positional variation, at the cost of nonnegligible delay spread, due to significant multipath effects.

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Communication Technologies for Intelligent Transportation Systems: From Railways to UAVs and Beyond

This white paper aims to comprehensively analyze and consolidate the state of the art in communication technologies supporting modern and future Information and Communication Technology (ICT). Its primary objective is to establish a common understanding of how communication solutions enable automation, safety, and efficiency across multiple transport domains, including railways, road vehicles, aircraft, and unmanned aerial vehicles. The document seeks to identify key communication requirements and technological enablers necessary for interoperable and reliable ITS operation. It also assesses the limitations of current systems and proposes pathways for integrating emerging technologies such as 5G, Sixth Generation (6G), and Artificial Intelligence (AI)-driven network control. The white paper also intends to support harmonization between different transport modes through a unified framework for communication modeling, testing, and standardization. It highlights the importance of accurate channel modeling and empirical validation to design efficient, robust, and scalable systems. Another objective is to explore the use of reconfigurable intelligent surfaces, integrated sensing and communication, and digital twin concepts within ITS. The document emphasizes the role of spectrum management and standardization efforts in ensuring interoperability among diverse communication systems. Finally, the paper seeks to stimulate collaboration among academia, industry, and standardization bodies to advance the design of resilient and adaptive communication infrastructures for future transportation systems.

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Spatially Consistent Air-to-Ground Channel Modeling and Simulation via 3D Shadow Projections

We present an approach for spatially-consistent semi-deterministic Air-to-Ground (A2G) channel modeling in Unmanned Aerial Vehicle-assisted networks. We use efficient 3D building shadow projections to determine Line-of-Sight (LOS) regions, enabling fast generation of LOS maps. By integrating LOS-aware deterministic path loss with stochastic shadow fading, the approach produces spatially consistent A2G radio maps suitable for environment- and mobility-aware channel evaluation and performance prediction. Simulation results in ITU-compliant Manhattan grid environments demonstrate the model's ability to reflect key urban propagation characteristics, such as LOS blockage patterns and outage behavior. The proposed approach provides an efficient alternative to ray tracing or fully stochastic models, with particular relevance for user mobility, link planning, and radio map generation in 6G non-terrestrial networks.

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Trajectory-Aware Air-to-Ground Channel Characterization for Low-Altitude UAVs Using MaMIMO Measurements

This paper presents a comprehensive measurement-based trajectory-aware characterization of low-altitude Air-to-Ground (A2G) channels in a suburban environment. A 64-element Massive Multi-Input Multi-Output (MaMIMO) array was used to capture channels for three trajectories of an Uncrewed Aerial Vehicle (UAV), including two horizontal zig-zag flights at fixed altitudes and one vertical ascent, chosen to emulate AUE operations and to induce controlled azimuth and elevation sweeps for analyzing geometry-dependent propagation dynamics. We examine large-scale power variations and their correlation with geometric features, such as elevation, azimuth, and 3D distance, followed by an analysis of fading behavior through distribution fitting and Rician K-factor estimation. Furthermore, temporal non-stationarity is quantified using the Correlation Matrix Distance (CMD), and angular stationarity spans are utilized to demonstrate how channel characteristics change with the movement of the UAV. We also analyze Spectral Efficiency (SE) in relation to K-factor and Root Mean Square (RMS) delay spread, highlighting their combined influence on link performance. The results show that the elevation angle is the strongest predictor of the received power, with a correlation of more than 0.77 for each trajectory, while the Nakagami model best fits the small-scale fading. The K-factor increases from approximately 5 dB at low altitudes to over 15 dB at higher elevations, indicating stronger LoS dominance. Non-stationarity patterns are highly trajectory- and geometry-dependent, with azimuth most affected in horizontal flights and elevation during vertical flight. These findings offer valuable insights for modeling and improving UAV communication channels in 6G Non-Terrestrial Networks (NTNs).

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CASH: Context-Aware Smart Handover for Reliable UAV Connectivity on Aerial Corridors

Urban Air Mobility (UAM) envisions aerial corridors for Unmanned Aerial Vehicles (UAVs) to reduce ground traffic congestion by supporting 3D mobility, such as air taxis. A key challenge in these high-mobility aerial corridors is ensuring reliable connectivity, where frequent handovers can degrade network performance. To resolve this, we present a Context-Aware Smart Handover (CASH) protocol that uses a forward-looking scoring mechanism based on UAV trajectory to make proactive handover decisions. We evaluate the performance of the proposed CASH against existing handover protocols in a custom-built simulator. Results show that CASH reduces handover frequency by up to 78% while maintaining low outage probability. We then investigate the impact of base station density and safety margin on handover performance, where their optimal setups are empirically obtained to ensure reliable UAM communication.

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Spatially Consistent Air-to-Ground Channel Modeling with Probabilistic LOS/NLOS Segmentation

In this paper, we present a spatially consistent A2G channel model based on probabilistic LOS/NLOS segmentation to parameterize the deterministic path loss and stochastic shadow fading model. Motivated by the limitations of existing Unmanned Aerial Vehicle (UAV) channel models that overlook spatial correlation, our approach reproduces LOS/NLOS transitions along ground user trajectories in urban environments. This model captures environment-specific obstructions by means of azimuth and elevation-dependent LOS probabilities without requiring a full detailed 3D representation of the surroundings. We validate our framework against a geometry-based simulator by evaluating it across various urban settings. The results demonstrate its accuracy and computational efficiency, enabling further realistic derivations of path loss and shadow fading models and thorough outage analysis.

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Effect of Realistic Oscillator Phase Noise on the Performance of Cell-Free Massive MIMO Systems

As the demand for 6G technologies continues to grow, the radio access infrastructure is expected to become increasingly dense. Cell-free (CF) Massive MIMO systems provide remarkable flexibility by enabling coherent service to users through multiple Access Points (APs). This innovative paradigm necessitates precise and stable phase synchronization. This paper examines the standardized 5G New Radio (NR) framework, focusing on subcarrier spacing, OFDM symbol duration, and allocation, while investigating the impact of Phase Noise (PN) on the performance of scalable massive MIMO cell-free systems. Unlike existing studies that typically employ a simplified model of a free-running oscillator characterized by a Wiener process, we present a realistic phase noise model inspired by actual hardware, designed to accurately capture the Local Oscillator (LO) phase drift. Furthermore, our PN model extends its applicability beyond cell-free systems, making it relevant for any RF system operating within the sub-6 GHz band. This model provides a robust foundation for the practical design of cell-free systems, encompassing numerology and pilot allocation strategies. Our findings reveal that even cost-effective low-cost Local Oscillators can achieve sufficient stability, resulting in negligible degradation of uplink Spectral Efficiency (SE) within the standardized 5G Transmission Time Interval of 1 ms. These results affirm the viability of cell-free massive MIMO systems based on 5G standards and their potential integration into future 6G networks.

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Empirical Line-of-Sight Probability Modeling for UAVs in Random Urban Layouts

Accurate Probability of Line-of-Sight (PLoS) modeling is important in evaluating the performance of Unmanned Aerial Vehicle (UAV)-based communication systems in urban environments, where real-time communication and low latency are often major requirements. Existing PLoS models often rely on simplified Manhattan grid layouts using International Telecommunication Union (ITU)-defined built-up parameters, which may not reflect the randomness of real cities. Therefore, this paper introduces the Urban LoS Simulator (ULS) to model PLoS for three random city layouts with varying building sizes and shapes constructed using ITU built-up parameters. Based on the ULS simulated data, we obtained the empirical PLoS for four standard urban environments across three different city layouts. Finally, we analyze how well Manhattan grid-based models replicate PLoS results from random and real-world layouts, providing insights into their applicability for time-critical communication systems in urban IoT networks.

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Path Loss Modelling for UAV Communications in Urban Scenarios with Random Obstacles

Path Loss (PL) is vital to evaluate the performance of Unmanned Aerial Vehicles (UAVs) as Aerial Base Stations (ABSs), particularly in urban environments with complex propagation due to various obstacles. Accurately modeling PL requires a generalized Probability of Line-of-Sight (PLoS) that can consider multiple obstructions. While the existing PLoS models mostly assume a simplified Manhattan grid with uniform building sizes and spacing, they overlook the real-world variability in building dimensions. Furthermore, such models do not consider other obstacles, such as trees and streetlights, which may also impact the performance, especially in millimeter-wave (mmWave) bands. This paper introduces a Manhattan Random Simulator (MRS) to estimate PLoS for UAV-based communications in urban areas by incorporating irregular building shapes, non-uniform spacing, and additional random obstacles to create a more realistic environment. Lastly, we present the PL differences with and without obstacles for standard urban environments and derive the empirical PL for these environments.

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Elevating the future of mobility: UAV-enabled Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) increasingly rely on connectivity for efficient traffic management and enhanced user experience. The existing ITS solutions operate mainly within a 2D domain, thus missing the potential benefits of aerial platforms. This paper envisions 3D ITS by integrating aerial platforms, such as Unmanned Aerial Vehicles (UAVs), to simultaneously improve network coverage and support multi-modal transportation, including Advanced Air Mobility (AAM). Using stochastic models, we investigate how UAV-based Aerial Base Stations (ABSs) can address the limitations of traditional Terrestrial Base Stations (TBSs) by offering superior coverage, particularly in urban environments. Our results demonstrate that ABSs have 106.67% more coverage area than TBS, higher Signal-to-Noise Ratio (SNR) distribution, and are suitable for high-throughput ITS applications.

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