arXiv subjects

Yevgeni Koucheryavy

Publications and source records attributed to Yevgeni Koucheryavy.

At least 19 recordsLinked to original sources

arXiv2024

The Impact of Traffic Characteristics on System and User Performance in 5G/6G Cellular Systems

The statistical characteristics of the propagation environment and traffic arrival process are known to affect the user performance in 5G/6G millimeter wave (mmWave) and subterahertz (sub-THz) systems. While the former topic has received considerable attention recently, little is known about the impact of traffic statistics. In this study, we characterize the effects of correlation and variability in the session arrival process on the performance of 5G/6G mmWave/sub-THz systems. To this end, we use the tools of stochastic geometry and queuing theory to model the service process at base stations (BS) and specifics of the mmWave/sub-THz radio part. The metrics considered include the system resource utilization and session loss probability. Our results show that the normalized autocorrelation function (NACF), coefficient of variation (CoV), and variance of the resource request distribution have a significant impact on the considered parameters. For the same arrival rate, high values of lag-1 NACF and CoV may lead the system out of the operational regime, affecting the loss probability and resource utilization by up to an order of magnitude. Even a slight deviation from the uncorrelated Poisson process decreases the utilization by 10-20% and increases the session loss probability multiple times. Radio and environmental characteristics may further increase the variability in resource request distribution and decrease resource utilization. In general, the use of the commonly accepted Poisson assumption leads to a severe underestimation of the actual performance of 5G/6G mmWave/sub-THz systems. Therefore, both traffic arrival and propagation statistics are equally important for accurate performance assessment of such systems.

cs.NI↗

arXiv2024

Remote Detection of Applications for Improved Beam Tracking in mmWave/sub-THz 5G/6G Systems

Beam tracking is an essential functionality of millimeter wave (mmWave, 30-100 GHz) and sub-terahertz (sub-THz, 100-300 GHz) 5G/6G systems. It operates by performing antenna sweeping at both base station (BS) and user equipment (UE) sides using the Synchronization Signal Blocks (SSB). The optimal frequency of beam tracking events is not specified by 3GPP standards and heavily depends on the micromobility properties of the applications currently utilized by the user. In absence of explicit signalling for the type of application at the air interface, in this paper, we propose a way to remotely detect it at the BS side based on the received signal strength pattern. To this aim, we first perform a multi-stage measurement campaign at 156 GHz, belonging to the sub-THz band, to obtain the received signal strength traces of popular smartphone applications. Then, we proceed applying conventional statistical Mann-Whitney tests and various machine learning (ML) based classification techniques to discriminate applications remotely. Our results show that Mann-Whitney test can be used to differentiate between fast and slow application classes with a confidence of 0.95 inducing class detection delay on the order of 1 s after application initialization. With the same time budget, random forest classifiers can differentiate between applications with fast and slow micromobility with 80% accuracy using received signal strength metric only. The accuracy of detecting a specific application however is lower, reaching 60%. By utilizing the proposed technique one can estimate the optimal values of the beam tracking intervals without adding additional signalling to the air interface.

eess.SP↗

arXiv2024

Internet of Paint (IoP): Channel Modeling and Capacity Analysis for Terahertz Electromagnetic Nanonetworks Embedded in Paint

This work opens a new chapter in the 100,000 year-old concept of paint, by leveraging innovations in nano-technology in the sub-THz frequency range. More specifically, the groundbreaking concept of Internet of Paint (IoP) is introduced along with a comprehensive channel model and a capacity analysis for nano-scale radios embedded in paint and communicating through paint. Nano-network devices, integrated within a paint medium, communicate via a multipath strategy, encompassing direct waves, reflections from interfaces, and lateral wave propagation. The evaluation incorporates three distinct paint types to assess path losses, received powers, and channel capacity. Analysis of path loss indicates a slight non-linear increase with both frequency and Line of Sight (LoS) distance between transceivers. Notably, paints with high refractive indexes result in the highest path loss. Moreover, burying transceivers at similar depths near the Air-Paint interface showcases promising performance of lateral waves with increasing LoS distance. Increasing paint layer depth leads to amplified attenuation, while total received power exhibits promising results when in close proximity to the Air-Paint interface but steeply declines with burial depth. Additionally, a substantial reduction in channel capacity is observed with LoS distance and burial depth, so transceivers need to be close together and in proximity of the A-P interface to communicate effectively. Comparing paint and air mediums, IoP demonstrates approximately two orders of magnitude reduction in channel capacity compared to air-based communication channels. This paper provides valuable insights into the potential of IoP communication within paint mediums and offers a foundation for further advancements in this emerging field.

physics.app-ph↗

arXiv2023

Low Complexity Algorithms for Mission Completion Time Minimization in UAV-Based ISAC Systems

The inherent support of sixth-generation (6G) systems enabling integrated sensing and communications (ISAC) paradigm greatly enhances the application area of intelligent transportation systems (ITS). One of the mission-critical applications enabled by these systems is disaster management, where ISAC functionality may not only provide localization but also provide users with supplementary information such as escape routes, time to rescue, etc. In this paper, by considering a large area with several locations of interest, we formulate and solve the optimization problem of delivering task parameters of the ISAC system by optimizing the UAV speed and the order of visits to the locations of interest such that the mission time is minimized. The formulated problem is a mixed integer non-linear program which is quite challenging to solve. To reduce the complexity of the solution algorithms, we propose two circular trajectory designs. The first algorithm finds the optimal UAV velocity and radius of the circular trajectories. The second algorithm finds the optimal connecting points for joining the individual circular trajectories. Our numerical results reveal that, with practical simulation parameters, the first algorithm provides a time saving of at least $20\%$, while the second algorithm cuts down the total completion time by at least $7$ times.

eess.SP↗

arXiv2023

Multi-Task Model Personalization for Federated Supervised SVM in Heterogeneous Networks

Federated systems enable collaborative training on highly heterogeneous data through model personalization, which can be facilitated by employing multi-task learning algorithms. However, significant variation in device computing capabilities may result in substantial degradation in the convergence rate of training. To accelerate the learning procedure for diverse participants in a multi-task federated setting, more efficient and robust methods need to be developed. In this paper, we design an efficient iterative distributed method based on the alternating direction method of multipliers (ADMM) for support vector machines (SVMs), which tackles federated classification and regression. The proposed method utilizes efficient computations and model exchange in a network of heterogeneous nodes and allows personalization of the learning model in the presence of non-i.i.d. data. To further enhance privacy, we introduce a random mask procedure that helps avoid data inversion. Finally, we analyze the impact of the proposed privacy mechanisms and participant hardware and data heterogeneity on the system performance.

cs.LG↗

arXiv2022

Comparative Analysis of Terahertz Propagation Under Dust Storm Conditions on Mars and Earth

Reliable Terahertz (THz) links are necessary for outdoor point-to-point communication with the exponential growth of wireless data traffic. This study presents a modified Monte Carlo simulation procedure for estimating THz link attenuation due to multiple scattering by dust particles on the THz beam propagation path. Scattering models are developed for beams through dust, based on Mie and Rayleigh approximations for corresponding frequencies for Earth (0.24 THz) and Mars (1.64 THz). The simulation results are compared, considering parameters such as the number of Monte-Carlo photon (MCP) packets, visibility, dust particle placement density along the beam, frequency, and distance between the transmitter and the receiver. Moreover, a channel capacity model was proposed, considering THz link attenuation due to dust storms, spreading loss and molecular absorption loss for Earth and Mars outdoor environments. Simulation results for Earth show that link attenuation increases with dust particle placement density, distance and frequency, and attenuation decreases with visibility. On Mars, similar results are obtained, except that the attenuation is variate around a constant value with the frequency increase. Channel capacity is estimated for Earth and Mars environments considering time and distance-dependent scenarios. Time windows that show a sudden drop of dust particles along the beam provide opportunities to communicate with high reliability. Moreover, increasing the distance between the transmitter and receiver severely reduces the channel capacity measurement in strong dust storm conditions in both environments. Our study has found that weak dust storms have relatively little effect on Mars, but much larger effects on Earth.

cs.IT↗

arXiv2022

SURIMI: Supervised Radio Map Augmentation with Deep Learning and a Generative Adversarial Network for Fingerprint-based Indoor Positioning

Indoor Positioning based on Machine Learning has drawn increasing attention both in the academy and the industry as meaningful information from the reference data can be extracted. Many researchers are using supervised, semi-supervised, and unsupervised Machine Learning models to reduce the positioning error and offer reliable solutions to the end-users. In this article, we propose a new architecture by combining Convolutional Neural Network (CNN), Long short-term memory (LSTM) and Generative Adversarial Network (GAN) in order to increase the training data and thus improve the position accuracy. The proposed combination of supervised and unsupervised models was tested in 17 public datasets, providing an extensive analysis of its performance. As a result, the positioning error has been reduced in more than 70% of them.

eess.SP↗

arXiv2022

Performance of Offloading Strategies in Collocated Deployments of Millimeter Wave NR-U Technology

5G New Radio (NR) technology operating in millimeter wave (mmWave) band is expected to be utilized in areas with high and fluctuating traffic demands such as city squares, shopping malls, etc. The latter may result in quality of service (QoS) violations. To deal with this challenge, 3GPP has recently proposed NR unlicensed (NR-U) technology that may utilize 60 GHz frequency band. In this paper, we investigate the deployment of NR-U base stations (BS) simultaneously operating in licensed and unlicensed mmWave bands in presence of competing WiGig traffic, where NR-U users may use unlicensed band as long as session rate requirements are met. To this aim, we utilize the tools of stochastic geometry, Markov chains, and queuing systems with random resource requirements to simultaneously capture NR-U/WiGig coexistence mechanism and session service dynamics in the presence of mmWave-specific channel impairments. We then proceed comparing performance of different offloading strategies by utilizing the eventual session loss probability as the main metric of interest. Our results show non-trivial behaviour of the collision probability in the unlicensed band as compared to lower frequency systems. The baseline strategy, where a session is offloaded onto unlicensed band only when there are no resources available in the licensed one, leads to the best performance. The offloading strategy, where sessions with heavier-than-average requirements are immediately directed onto unlicensed band results in just $2-5\%$ performance loss. The worst performance is observed when sessions with smaller-than-average requirements are offloaded onto unlicensed band.

cs.NI↗

arXiv2022

User Association and Multi-connectivity Strategies in Joint Terahertz and Millimeter Wave 6G Systems

Terahertz (THz) wireless access is considered as a next step towards sixth generation (6G) cellular systems. By utilizing even higher frequency bands than 5G millimeter wave (mmWave) New Radio (NR), they will operate over extreme bandwidth delivering unprecedented rates at the access interface. However, by relying upon pencil-wide beams, these systems will not only inherit mmWave propagation challenges such as blockage phenomenon but introduce their own issues associated with micromobility of user equipment (UE). In this paper, we analyze and compare user association schemes and multi-connectivity strategies for joint 6G THz/mmWave deployments. Differently, from stochastic geometry studies, we develop a unified analytically tractable framework that simultaneously accounts for specifics of THz and mmWave radio part design and traffic service specifics at mmWave and THz base stations (BS). Our results show that (i) for negligible blockers density, $λ_B\leq{}0.1$ bl./$m^2$, the operator needs to enlarge the coverage of THz BS by accepting sessions that experience outage in case of blockage (ii) for $λ_B>0.1$ bl./$m^2$, only those sessions that does not experience outage in case of blockage need to be accepted at THz BS, (iii) THz/mmWave multi-connectivity improves the ongoing session loss probability by $0.1-0.4$ depending on the system parameters.

cs.NI↗

arXiv2022

DECT-2020 New Radio: The Next Step Towards 5G Massive Machine-Type Communications

Massive machine type communications (mMTC) is one of the cornerstone services that have to be supported by 5G systems. 3GPP has already introduced LTE-M and NB-IoT, often referred to as cellular IoT, in 3GPP Releases 13, 14, and 15 and submitted these technologies as part of 3GPP IMT-2020 (i.e., 5G) technology submission to ITU-R. Even though NB-IoT and LTE-M have shown to satisfy 5G mMTC requirements defined by ITU-R, it is expected that these cellular IoT solutions will not address all aspects of IoT and ongoing digitalization, including the support for direct communication between "things" with flexible deployments, different business models, as well as support for even higher node densities and enhanced coverage. In this paper, we introduce the DECT-2020 standard recently published by ETSI for mMTC communications. We evaluate its performance and compare it to the existing LPWAN solutions showing that it outperforms those in terms of supported density of nodes while still keeping delay and loss guarantees at the required level.

cs.NI↗

arXiv2022

Lightweight Hybrid CNN-ELM Model for Multi-building and Multi-floor Classification

Machine learning models have become an essential tool in current indoor positioning solutions, given their high capabilities to extract meaningful information from the environment. Convolutional neural networks (CNNs) are one of the most used neural networks (NNs) due to that they are capable of learning complex patterns from the input data. Another model used in indoor positioning solutions is the Extreme Learning Machine (ELM), which provides an acceptable generalization performance as well as a fast speed of learning. In this paper, we offer a lightweight combination of CNN and ELM, which provides a quick and accurate classification of building and floor, suitable for power and resource-constrained devices. As a result, the proposed model is 58\% faster than the benchmark, with a slight improvement in the classification accuracy (by less than 1\%

eess.SP↗

arXiv2021

A Tutorial on Mathematical Modeling of Millimeter Wave and Terahertz Cellular Systems

Millimeter wave (mmWave) and terahertz (THz) radio access technologies (RAT) are expected to become a critical part of the future cellular ecosystem providing an abundant amount of bandwidth in areas with high traffic demands. However, extremely directional antenna radiation patterns that need to be utilized at both transmit and receive sides of a link to overcome severe path losses, dynamic blockage of propagation paths by large static and small dynamic objects, macro- and micromobility of user equipment (UE) makes provisioning of reliable service over THz/mmWave RATs an extremely complex task. This challenge is further complicated by the type of applications envisioned for these systems inherently requiring guaranteed bitrates at the air interface. This tutorial aims to introduce a versatile mathematical methodology for assessing performance reliability improvement algorithms for mmWave and THz systems. Our methodology accounts for both radio interface specifics as well as service process of sessions at mmWave/THz base stations (BS) and is capable of evaluating the performance of systems with multiconnectivity operation, resource reservation mechanisms, priorities between multiple traffic types having different service requirements. The framework is logically separated into two parts: (i) parameterization part that abstracts the specifics of deployment and radio mechanisms, and (ii) queuing part, accounting for details of the service process at mmWave/THz BSs. The modular decoupled structure of the framework allows for further extensions to advanced service mechanisms in prospective mmWave/THz cellular deployments while keeping the complexity manageable and thus making it attractive for system analysts.

cs.NI↗

arXiv2021

Climate Change Sensing through Terahertz Communications: A Disruptive Application of 6G Networks

Climate change resulting from the misuse and over-exploitation of natural resources has affected and continues to impact the planet's ecosystem. This pressing issue is leading to the development of novel technologies to sense and measure damaging gas emissions. In parallel, the accelerating evolution of wireless communication networks is resulting in wider deployment of mobile telecommunication infrastructure. With 5G technologies already being commercially deployed, the research community is starting research into new technologies for 6G. One of the visions for 6G is the use of the terahertz (THz) spectrum. In this paper, we propose and explore the use of THz spectrum simultaneously for ultrabroadband communication and atmospheric sensing by leveraging the absorption of THz signals. Through the use of machine learning, we present preliminary results on how we can analyze signal path loss and power spectral density to infer the concentration of different climate-impacting gases. Our vision is to demonstrate how 6G infrastructure can provide sensor data for climate change sensing, in addition to its primary purpose of wireless communication.

eess.SP↗

arXiv2021

A Review on Bio-Cyber Interfaces for Intrabody Molecular Communications Systems

The recent advancements in bio-engineering and wireless communications systems have motivated researchers to propose novel applications for telemedicine, therapeutics and human health monitoring. For instance, through wireless medical telemetry a healthcare worker can remotely measure biological signals and control certain processes in the organism required for the maintenance of the patient's health state. This technology can be further extended to use Bio-Nano devices to promote a real-time monitoring of the human health and storage of the gathered data in the cloud. This brings new challenges and opportunities for the development of biosensing network, which will depend on the extension of the current intrabody devices functionalities. In this paper we will cover the recent progress made on implantable micro-scale devices and introduce the perspective of improve them to foster the development of new theranostics based on data collected at the nanoscale level.

eess.SY↗

arXiv2021

On performance of PBFT for IoT-applications with constrained devices

Cyber-physical systems and the Internet of things (IoT) is becoming an integral part of the digital society. The use of IoT services improves human life in many ways. Protection against cyber threats is an important aspect of the functioning of IoT devices. Malicious activities lead to confidential data leakages and incorrect performance of devices are becoming critical. Therefore, development of effective solutions that can protect both IoT devices data and data exchange networks turns in to a real challenge. This study provides a critical analysis of the feasibility of using blockchain technology to protect constrained IoT devices data, justifies the choice of Practical Byzantine Fault Tolerance (PBFT) consensus algorithm for implementation on such devices, and simulates the main distributed ledger scenarios using PBFT. The simulation results demonstrate the efficiency of the blockchain technology for constrained devices and make it possible to evaluate the applicability limits of the chosen consensus algorithm.

cs.CR↗

arXiv2021

Peer Offloading with Delayed Feedback in Fog Networks

Comparing to cloud computing, fog computing performs computation and services at the edge of networks, thus relieving the computation burden of the data center and reducing the task latency of end devices. Computation latency is a crucial performance metric in fog computing, especially for real-time applications. In this paper, we study a peer computation offloading problem for a fog network with unknown dynamics. In this scenario, each fog node (FN) can offload their computation tasks to neighboring FNs in a time slot manner. The offloading latency, however, could not be fed back to the task dispatcher instantaneously due to the uncertainty of the processing time in peer FNs. Besides, peer competition occurs when different FNs offload tasks to one FN at the same time. To tackle the above difficulties, we model the computation offloading problem as a sequential FN selection problem with delayed information feedback. Using adversarial multi-arm bandit framework, we construct an online learning policy to deal with delayed information feedback. Different contention resolution approaches are considered to resolve peer competition. Performance analysis shows that the regret of the proposed algorithm, or the performance loss with suboptimal FN selections, achieves a sub-linear order, suggesting an optimal FN selection policy. In addition, we prove that the proposed strategy can result in a Nash equilibrium (NE) with all FNs playing the same policy. Simulation results validate the effectiveness of the proposed policy.

eess.SP↗

arXiv2020

Handling Spontaneous Traffic Variations in 5G+ via Offloading onto mmWave-Capable UAV `Bridges'

Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public and civil applications, such as goods delivery, medicine, surveillance, and telecommunications. For the latter, UAVs with onboard communication equipment may help temporarily offload traffic onto the neighboring cells in fifth-generation networks and beyond (5G+). In this paper, we propose and evaluate the use of UAVs traveling over the area of interest to relieve congestion in 5G+ systems under spontaneous traffic fluctuations. To this end, we assess two inherently different offloading schemes, named routed and controlled UAV `bridging'. Using the tools of renewal theory and stochastic geometry, we analytically characterize these schemes in terms of the fraction of traffic demand that can be offloaded onto the UAV `bridge' as our parameter of interest. This framework accounts for the unique features of millimeter-wave (mmWave) radio propagation and city deployment types with potential line-of-sight (LoS) link blockage by buildings. We also introduce enhancements to the proposed schemes that significantly improve the offloading gains. Our findings offer evidence that the UAV `bridges' may be used for efficient traffic offloading in various urban scenarios.

cs.NI↗

arXiv2020

Capacity and Outage of Terahertz Communications with User Micro-mobility and Beam Misalignment

User equipment mobility is one of the primary challenges for the design of reliable and efficient wireless links over millimeter-wave and terahertz bands. These high-rate communication systems use directional antennas and therefore have to constantly maintain alignment between transmitter and receiver beams. For terahertz links, envisioned to employ radiation patterns of no more than few degrees wide, not only the macro-scale user mobility (human walking, car driving, etc.) but also the micro-scale mobility - spontaneous shakes and rotations of the device - becomes a severe issue. In this paper, we propose a mathematical framework for the first-order analysis of the effects caused by micro-mobility on the capacity and outage in terahertz communications. The performance of terahertz communications is compared with and without micro-mobility illustrating the difference of up to 1 Tbit/s or 75%. In response to this gap, it is finally shown how the negative effects of the micro-mobility can be partially addressed by a proper adjustment of the terahertz antenna arrays and the period of beam realignment procedure.

cs.NI↗