Margarita Gapeyenko

Analysis of human-body blockage in urban millimeter-wave cellular communications

The use of extremely high frequency (EHF) or millimeter-wave (mmWave) band has attracted significant attention for the next generation wireless access networks. As demonstrated by recent measurements, mmWave frequencies render themselves quite sensitive to “blocking” caused by obstacles like foliage, humans, vehicles, etc. However, there is a dearth of analytical models for characterizing such blocking and the consequent effect on the signal reliability. In this paper, we propose a novel, general, and tractable model for characterizing the blocking caused by humans (assuming them to be randomly located in the environment) to mmWave propagation as a function of system parameters like transmitter-receiver locations and dimensions, as well as density and dimensions of humans. Moreover, the proposed model is validated using a ray-launcher tool. Utilizing the proposed model, the blockage probability is shown to increase with human density and separation between the transmitter-receiver pair. Furthermore, the developed analysis is shown to demonstrate the existence of a transmitter antenna height that maximizes the received signal strength, which in turn is a function of the transmitter-receiver distance and their dimensions.

Direct Connection on the Move: Characterization of User Mobility in Cellular-Assisted D2D Systems

Next-generation device-to-device (D2D) communication technology, in which a cellular network assists proximal users at all stages of their interaction, is rapidly developing. Previous research has thoroughly characterized D2D performance aspects from discovery to connection establishment, security, and service continuity; however, prospective D2Denabled applications and services envision highly opportunistic device contacts as a consequence of unpredictable human user mobility. Therefore, mobilitys impact on D2D communication requires careful investigation to understand the practical operational efficiency of future cellular-assisted D2D systems. This article offers a first-hand tutorial on various implications of D2D mobility across different user movement patterns and mobility-related parameters and proposes an assessment methodology for D2D-enabled systems. The rigorous system-level evaluation conducted for this study delivers important conclusions on the effects of user mobility in emerging D2D-centric systems.

Assisted Handover Based on Device-to-Device Communications in 3GPP LTE Systems

The ever increasing demand in mobile data traffic, fueled by the fast proliferation of bandwidth-hungry wireless applications and services, has imposed new challenges on data rate requirements in emerging 5G systems. To meet these demanding expectations, the mainstream direction for the network operators is to deploy a higher density of various cellular infrastructure. Along these lines, this paper seeks to augment future handover operation by employing the recent Device-to-Device (D2D) communications technology. The underlying rationale behind our proposal is to equip the mobile users with better-quality direct links and thus improve the resulting service perception under the typical 3GPP LTE handover procedures. The proposed D2D-assisted handover scheme is able to efficiently offer the attractive energy efficiency, data rate, and packet delivery ratio benefits. By utilizing the tools from stochastic geometry, we derive the main performance metrics of interest for our solution, such as the distribution of signal-to-noise ratio experienced by a user entering the zone of overlapping coverage and the amount of time it remains in contact with a chosen D2D partner. The gains on top of the standard LTE handover procedures for all the considered parameters are further confirmed by extensive system-level simulations in video streaming and multimedia content downloading scenarios.

Characterizing Spatial Correlation of Blockage Statistics in Urban mmWave Systems

Millimeter-wave (mmWave) systems suffer from a significant loss in performance when the line-of- sight (LoS) path between the transmitter and the receiver is obstructed due to blockage caused by humans or other obstacles. However, due to blocker or user motion, the mmWave receiver may transition between the LoS and non-LoS (nLoS) states. Following the recent 3GPP requirements on spatial consistency for channel modeling, this paper aims to analyze the spatial correlation of blockage statistics and characterize their evolution due to user mobility in a static field of blockers in urban mmWave systems. In particular, we derive conditional probabilities of residing in LoS or nLoS state at a given time t1, provided that a user was in LoS/nLoS state at a prior time t0. We demonstrate that for realistic values of user speed, the angle of motion, height of transmitter and receiver, as well as the density of blockers, there always is a significant correlation between user channel states at time t0 and t1, across the time scales relevant for mmWave resource scheduling. Hence, our model can serve as an important tool for optimizing system performance in the presence of blockage.

Dynamic Multi-Connectivity Performance in Ultra-Dense Urban mmWave Deployments

Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.

Achieving End-to-End Reliability of Mission-Critical Traffic in Softwarized 5G Networks

Network softwarization is a major paradigm shift, which enables programmable and flexible system operation in challenging use cases. In the fifth-generation (5G) mobile networks, the more advanced scenarios envision transfer of high-rate mission-critical traffic. Achieving end-to-end reliability of these stringent sessions requires support from multiple radio access technologies and calls for dynamic orchestration of resources across both radio access and core network segments. Emerging 5G systems can already offer network slicing, multi-connectivity, and end-to-end quality provisioning mechanisms for critical data transfers within a single software-controlled network. Whereas these individual enablers are already in active development, a holistic perspective on how to construct a unified, service-ready system as well as understand the implications of critical traffic on serving other user sessions is not yet available. Against this background, this paper first introduces a softwarized 5G architecture for end-to-end reliability of the mission-critical traffic. Then, a mathematical framework is contributed to model the process of critical session transfers in a softwarized 5G access network, and the corresponding impact on other user sessions is quantified. Finally, a prototype hardware implementation is completed to investigate the practical effects of supporting mission-critical data in a softwarized 5G core network, as well as substantiate the key system design choices.

An Analytical Representation of the 3GPP 3D Channel Model Parameters for mmWave Bands

Accurate performance prediction for the emerging 3GPP New Radio (NR) technology over millimeter-wave (mmWave) bands is crucial for the upcoming deployments of 5G and beyond cellular networks, utilizing NR. 3GPP has recently presented a 3D multipath cluster-based mmWave channel model for 5G NR, which captures the salient propagation characteristics of the mmWave bands, allowing for better prediction of mmWave system performance. However, it is difficult to directly employ the 3GPP models for analytical system characterization, as most of the parameters are computed through iterative algorithms. In the paper, we address this problem by presenting a statistical approximation for the important parameters of the 3GPP 3D cluster-based channel model, particularly, zenith angle of arrival and power share of every cluster. We then show how the constructed approximation can be used to analytically derive the performance indicators for mmWave NR systems, including outage probability. We compare the results obtained with our proposed statistical approximation model with those given by state-of-the-art simplified single cluster analytical models as well as illustrate the improvements in the accuracy of results.

Technologies for Efficient Amateur Drone Detection in 5G Millimeter-Wave Cellular Infrastructure

Unmanned aerial vehicles, also called drones, are recently gaining increased research attention across various fields due to their flexibility and application potential. The steady increase in the number of amateur drones demands more stringent regulations on their allowed route, mass, and load. However, these regulations may be violated accidentally or deliberately. In these cases, spying with drones, transfer of dangerous payloads, or losing reliable drone control can represent a new hazard for people, governments, and business sector. The technologies to detect, track, and disarm possible aerial threats are therefore in prompt demand. To this end, ubiquitous cellular networks, and especially 5G infrastructures based on the use of millimeter-wave radio modules, may be efficiently leveraged to offer the much needed drone detection capabilities. In this work, we propose to exploit 5G millimeter-wave deployments to detect violating amateur drones. We argue that the prospective 5G infrastructure may provide all the necessary technology elements to support efficient detection of small-sized drones. We therefore outline a novel technology and system design perspective, including such considerations as the density of base stations, their directional antennas, and the available bandwidth, among others, as well as characterize their impact with our ray-based modeling methods.

Toward Massive Ray-Based Simulations of mmWave Small Cells on Open Urban Maps

High-rate access in outdoor urban areas using extremely high frequency (EHF) bands, known as millimeter-wave (mmWave) spectrum, requires a dense deployment of wireless small cells in order to provide continuous coverage to serve bandwidth-hungry users. At the same time, to be able to collect a sufficient amount of data for constructing detailed EHF propagation models, a considerable number of various landscape maps across different scenarios have to be considered. This letter develops a shoot-and-bounce ray (SBR)-based methodology capable of characterizing the mmWave propagation in urban outdoor conditions. In particular, our methodology aims to capture a large number of small cells within accurate, real city maps and then to utilize an algorithm of automatic transmitter placement. Hence, our contribution is to provide a suitable tool that is able to handle massive ray-based simulations within a reasonable time frame. In particular, we demonstrate and verify that a shift from simulating three-dimensional (3-D) to evaluating 2-D environments significantly reduces computation time while only slightly decreasing the simulation accuracy.