Electricity production and distribution is facing two major changes. First, production is shifting from classical energy sources such as coal and nuclear power toward renewable resources such as solar and wind. Second, consumption in the low voltage grid is expected to grow significantly due to the expected introduction of electrical vehicles. Thus, with the increasing penetration of distributed energy resources, the smart grid needs more and deeper monitoring and control to maintain stable operation. In this paper, we proposed advanced measurement devices, management framework, and secure communication infrastructure, which allows full observability of the energy flows in the distribution grid. Furthermore, using proposed infrastructure, the prosumers are able to participate pro-actively and coordinate with the distribution system operator and other stakeholders in the grid. This paper presents novel solutions and analyses of these aspects for the real testbed (Elektro Primorska region) scenario, where smart grid ICT solutions are provided through shared cellular LTE networks. Specifically, we highlighted the security and communication requirements such as, e.g., end-to-end security, dynamic credential distribution, and highly reliable low latency communication. The paper presents a solution for secure monitoring and management of smart distribution grid via mobile cellular netowork that was developed and piloted in a real operating environment in the FP7 project SUNSEED, in which we provided technical coordination.
COBISS.SI-ID: 30453031
5G machine type communication (MTC) networks will be formed of dense, heterogeneous clusters of wireless devices serving different applications verticals such as urban service enablers, body area networks, industrial and home automation, entertainment, etc. They will use a large number of existing and emerging wireless technologies served by advanced 5G gateways or eNodeB IoT and controlled through software interfaces by control and application programs, reducing the need for on site, manual reconfigurations. In this paper, we focus on the software interfaces that enable the control of 5G MTC networks and propose a functional split in upstream and downstream functions. We provide a reference implementation using RESTful functionality and an example control application that performs radio localization. The provision of reliable low latency communications represents one of the key challenges for the 5G MTC networks with the emphasys on the application areas of industrial automation, smart grids and autonomous driving.
COBISS.SI-ID: 30593831
The contribution presents a novel model for prediction of site diversity system performance in millimeter-wave satellite communications. The model predicts the joint exceedance probability of rain attenuation based on a new family of Archimedean copulas, called the Hyperbolic Cosecant Copula. The proposed methodology can be used also for the prediction of joint first order statistics of rain attenuation for dual and multiple site diversity systems. Moreover, in addition to the common approaches, where the dependency of rain attenuation induced on multiple links is based solely on the distance between ground stations, elevation and baseline angle are also taken into account for the modeling of the dependence parameter. Tests have been performed on an extensive dataset of site diversity experiments with various system configurations and it is shown that the proposed model outperforms the the ITU-R Recommendation P.618-12 as well as the state-of-the-art models such as the models based on the Archimedean Clayton Copula and the Gaussian Copula. Research in site diversity reception is important for the next generation high-throughput satellite systems, which will operate at very high frequencies that are highly susceptible to atmospheric signal attenuation.
COBISS.SI-ID: 30651175
We have developed a methodology that guides researchers in the process of developing effective machine-type communication (MTC) wireless systems with the devices that have restricted capabilities. It enables experimental evaluation and replication of the existing theoretical results. The methodology consists of six sequential steps, namely, (i) formulation of the discrete problem, (ii) development of the theoretical formalism, (iii) design of the algorithm, (iv) definition of evaluation criteria, (v) definition of the experimental set-up and (vi) performance of experimental evaluation. As a case study of using the proposed methodology, we present the development and evaluation of an efficient interference mitigation systems using devices that support only discrete transmit power levels. The proposed methodology is particularly useful for the developers of new applications for the Internet of Things concept which is largely based on effective machine-type communications between devices with restricted capabilities.
COBISS.SI-ID: 30267943
In this paper, the influence of typical objects to the mmWave propagation channel are analysed for different railway scenarios with various configurations. Propagation measurements are conducted in the mmWave band for the 12 most common railway materials. The corresponding electromagnetic parameters are obtained and a 3D ray tracing (RT) simulator is calibrated. Results indicate that the calibrated RT can be used to generate the close-to-real mmWave channel for railway scenarios. The influence of typical objects and corresponding material compositions are also compared and significant objects are determined for each scenario. The results of this work not only imply how the propagation environment impacts on the propagation channel, but also makes suggestions to efficiently reconstruct railway environment models for an accurate RT based channel model. The results are particularly important in the context of the provision of 5G mobile communication services in railway scenarios, and are the result of several years of cooperation with a research team from China based on our publication from 2014 (COBISS ID 27108391) in the most prestigious magazine in the field. With the same group of authors, another contribution (COBISS ID 31180327) was published in the same magazine in 2018, complementing two previous articles in magazines (1A1 and 1A2) and 5 conference papers.
COBISS.SI-ID: 30993447
Data-driven research uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw wireless network data traces. These data-driven approaches are becoming indispensable for the management and optimization of increasingly complex heterogeneous next-generation software-defined networks.
COBISS.SI-ID: 29528103
The contribution describes the main outcomes of the FP7 ABSOLUTE project in terms of network and system architecture, regulations, and implementation of aerial base stations, portable land mobile units, satellite backhauling, S-MIM satellite messaging, and multimode user equipment. The ABSOLUTE project focused on designing, prototyping, and demonstrating a high-capacity IP mobile data network with low latency and large coverage suitable for many forms of multimedia delivery including public safety scenarios. The ABSOLUTE project combines aerial, terrestrial, and satellites communication networks for providing a robust standalone communication systems. The solutions developed and prototyped in the frame of the ABSOLUTE project are suitable for optimizing the coverage of mobile networks, which we demonstrated also in FP7 project SUNSEED and H2020 project eWINE, as well as for the planning and ad hoc deployment of a temporary communication system in emergency situations.
COBISS.SI-ID: 29534247
This paper addresses a user-centric approach to network and user traffic modelling that has been validated and used in the process of introducing, optimizing and planning new services at the Slovenian national telecom operator and service provider, Telekom Slovenije d.d. The proposed approach is based on the end-users and their user-group profiles that are founded on the real measurements from the observed telecommunication network consisting of more than thousand MSANs and more than 300 thousand subscribers. The proposed approach has been successfully validated showing that for the observed period the modeled link load deviates less than 5% from the measurements. Furthermore, in the presented case study the proposed approach is used successfully in the process of introducing and optimization of Fast Channel Change service. This paper summarizes results of longer term cooperation with Telekom Slovenije on the modeling and optimization of the real telecommunication network. The methods and findings are directly applicable to the network of any operator. The significance of the results has been confirmed by the award for the best article in 2015 by the IEEE ComSoc Technical Committee on Communications Systems Integration and Modeling.
COBISS.SI-ID: 28767783
The inefficient divergence handling is one of the processing bottlenecks in today's Graphical Processing Units (GPUs) with single-instruction multiple thread (SIMT) architecture. The radio ray-tracing algorithms are frequently accelerated by such architectures. Intersecting scene objects while traversing acceleration structures with rays concurrently by multiple threads typically gives divergent flow patterns. The problem is usually hidden by the programmer's view of independent threads. A loop optimization technique having the potential to increase efficiency of the core architectural blocks while processing embedded divergences has been investigated. An optimization of concurrent loops was proposed, allowing better alignment of thread flows via iteration scheduling. Processing speedups can generally be observed in the total running time if kernels are compute-bound, as demonstrated by several examples. The studied iteration scheduling policies do not impose alterations to the core SIMT concept and design, thus preserving the benefits of data level parallelism while speeding up tasks such as radio coverage computation. The proposed accelleration of computation is directly applicable to real networks and is particularly important in the light of densification of cellular networks and near real-time coverage adaptation to changing transmission demands.
COBISS.SI-ID: 28013351
Existing indoor localization solutions provide various levels of precision, which also depends on the complexity of the indoor radio environment. In this paper, we proposed two methods for reducing the localization error in indoor nonline-of-sight (NLoS) conditions using raw channel impulse response (CIR) information obtained from ultra-wide band (UWB) radios requiring no prior knowledge about the radio environment. The methods are based on NLoS channel classification and ranging error regression models, both using convolutional neural networks (CNNs). We first show that NLoS channel classification using raw CIR data outperforms existing approaches that are based on derived input signal features. We further demonstrate that the predicted NLoS channel state and predicted ranging error information significantly improve indoor localization performance. We also evaluate the computational performance and suitability of the proposed CNN-based algorithms on various computing platforms with a range of different capabilities and show that in a distributed localization system, they can also be used on computationally restricted devices. Indoor localization is one of the key enablers for various application and service areas in next generation communications. By providing a better insight in the location and context of users it will enable location dependent applications and time and space optimization of network resources.
COBISS.SI-ID: 31291943