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Journal of Telecommunications and Information Technology (JTIT) - 2/2018

Sławomir Kula
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Christian Hoppe and Tadeus Uhl
Video Streaming over IP using the DASH Technique
Modern Internet serves as a high-performance platform for an ever-increasing number of services. Some of them – video services in particular – are of the broadband variety. So, it is not surprising that segments of networks can rapidly become congested, which may lead to a deterioration in quality. It is hoped that the new MPEG-DASH technique will alleviate congestion. This paper contains an analysis of the new technology’s impact on the quality of service in IP networks. It also explains a new numerical tool QoSCalc(DASH) that has been used to analyze the DASH method in different scenarios. The results are presented graphically and interpreted.
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Grzegorz Wilczewski
Stereoscopic 3DTV Video Quality Metric: the Compressed Average Image Intensity
This paper presents a newly designed stereoscopic video quality metric. Overall insights towards the creation of mechanisms utilized within the genuine metric are presented herein. Delivery of the core information and motivation behind the features implemented, as well as functionality of the Compressed Average Image Intensity (CAII) quality metric are of utmost importance. The mechanisms created might be characterized as an objective, reliable and versatile quality evaluation tool for advanced analysis of the content delivery chain within stereoscopic video services.
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Pallavi Agrawal and Madhu Shandilya
Model-Based Method for Acoustic Echo Cancelation and Near-End Speaker Extraction: Non-negative Matrix Factorization
Rapid escalation of wireless communication and hands-free telephony creates a problem with acoustic echo in full-duplex communication applications. In this paper a simulation of model-based acoustic echo cancelation and near-end speaker extraction using statistical methods relying on nonnegative matrix factorization (NMF) is proposed. Acoustic echo cancelation using the NMF algorithm is developed and its implementation is presented, along with all positive, real time elements and factorization techniques. Experimental results are compared against the widely used existing adaptive algorithms which have a disadvantage in terms of long impulse response, increased computational load and wrong convergence due to change in near-end enclosure. All these shortcomings have been eliminated in the statistical method of NMF that reduces echo and enhances audio signal processing.
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Gurpreet Kaur, Mohit Srivastava and Amod Kumar
Genetic Algorithm for Combined Speaker and Speech Recognition using Deep Neural Networks
Huge growth is observed in the speech and speaker recognition field due to many artificial intelligence algorithms being applied. Speech is used to convey messages via the language being spoken, emotions, gender and speaker identity. Many real applications in healthcare are based upon speech and speaker recognition, e.g. a voice-controlled wheelchair helps control the chair. In this paper, we use a genetic algorithm (GA) for combined speaker and speech recognition, relying on optimized Mel Frequency Cepstral Coefficient (MFCC) speech features, and classification is performed using a Deep Neural Network (DNN). In the first phase, feature extraction using MFCC is executed. Then, feature optimization is performed using GA. In the second phase training is conducted using DNN. Evaluation and validation of the proposed work model is done by setting a real environment, and efficiency is calculated on the basis of such parameters as accuracy, precision rate, recall rate, sensitivity, and specificity. Also, this paper presents an evaluation of such feature extraction methods as linear predictive coding coefficient (LPCC), perceptual linear prediction (PLP), mel frequency cepstral coefficients (MFCC) and relative spectra filtering (RASTA), with all of them used for combined speaker and speech recognition systems. A comparison of different methods based on existing techniques for both clean and noisy environments is made as well.
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Krzysztof Bronk, Adam Lipka and Rafał Niski
Link Quality Assessment Algorithm for Heterogeneous Self-organizing Maritime Communications Network
The article introduces a method of performing a radio link quality assessment based on the Link Quality Indicator (LQI) which will be calculated for every system that is available. The method presented has been developed during the netBaltic project completed in Poland and generally applies to the so-called maritime zone A, i.e. the sea area where ships are still within the range of shore-based radio communication systems, particularly 3G/LTE cellular networks. The algorithm was developed based on the results of measurements obtained during two separate campaigns. That measurement data served as a basis for the method’s initial assumptions and was utilized during the method’s verification.
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Valery Tikhvinskiy, Grigory Bochechka, Andrey Gryazev and Altay Aitmagambetov
Comparative Analysis of QoS Management and Technical Requirements in 3GPP Standards for Cellular IoT Technologies
Optimization of 3GPP standards that apply to cellular technologies and their adaptation to LPWAN has not led to positive results only enabling to compete on the market with the growing number non-cellular greenfield LPWAN technologies – LoRa, Sigfox and others. The need to take into consideration, during the 3GPP standard optimization phase, the low-cost segment of narrow-band IoT devices relying on such new technologies as LTE-M, NB-IoT and EC-GSM, has also led to a loss of a number of technical characteristics and functions that offered low latency and guaranteed the quality of service. The aim of this article is therefore to review some of the most technical limitations and restrictions of the new 3GPP IoT technologies, as well as to indicate the direction for development of future standards applicable to cellular IoT technologies.
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Grażyna Kadamus and Małgorzata Langer
Measurements and Statistical Analysis for Assessment of Availability of Mobile Network Services
Availability is an essential feature of telecommunication services. It influences the quality of experience (QoE) associated with individual networks and with the services offered. Therefore, it needs to be allowed for at each level of network design, and has to be controlled at the operation stage. This is achieved by means of various mathematical and numerical tools. In this project listening quality and speech level, which are quality-related features of mobile network services, are measured and analyzed with the Monte Carlo simulation method. Measurements are taken with assistance of the Diversity Benchmarker, a reliable device designed for mobile network testing. Finally, results obtained are compared to assess the applicability of the Monte Carlo method.
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Szabolcs Szilágyi, Ferenc Fejes and Róbert Katona
Throughput Performance Comparison of MPT-GRE and MPTCP in the Fast Ethernet IPv4/IPv6 Environment
This paper presents the MPT-GRE software, a novel multipath communication technology founded on the Generic Routing Encapsulation (GRE) protocol in UDP tunneling RFC specification. It enables the creation of a GRE protocolbased UDP tunnel built on several communication channels. On the other hand, MPTCP is one of the most typical representatives among multipath communication technologies, basing its operation on the utilization of TCP subflows. The authors compare the path-aggregation capabilities of these two technologies using four Fast Ethernet channels. The tests were carried out with the iperf3 network bandwidth measurement tool, and while transferring data using the FTP protocol over both IPv4 and IPv6.
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P. Vimala and G. Yamuna
Pilot Design for Sparse Channel Estimation in Orthogonal Frequency Division Multiplexing Systems
Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band wireless communication systems. Coherent OFDM systems achieve its advantages over a multipath fading channel, if channel impulse response is estimated precisely at the receiver. Pilot-aided channel estimation in wide band OFDM systems adopts the recently explored compressive sensing technique to decrease the transmission overhead of pilot subcarriers, since it exploits the inherent sparsity of the wireless fading channel. The accuracy of compressive sensing techniques in sparse channel estimation is based on the location of pilots among OFDM subcarriers. A sufficient condition for the optimal pilot selection from Sylow subgroups is derived. A Sylow subgroup does not exist for most practical OFDM systems. Therefore, a deterministic pilot search algorithm is described to select pilot locations based on minimizing coherence, along with minimum variance. Simulation results reveal the effectiveness of the proposed algorithm in terms of bit error rate, compared to the existing solutions.
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Marco Morocho-Yaguana, Patricia Ludeña-González, Francisco Sandoval, Betty Poma-Vélez and Alexandra Erreyes-Dota
An Optimized Propagation Model based on Measurement Data for Indoor Environments
Propagation is an essential factor ensuring good coverage of wireless communications systems. Propagation models are used to predict losses in the path between transmitter and receiver nodes. They are usually defined for general conditions. Therefore, their results are not always adapted to the behavior of real signals in a specific environment. The main goal of this work is to propose a new model adjusting the loss coefficients based on empirical data, which can be applied in an indoor university campus environment. The Oneslope, Log-distance and ITU models are described to provide a mathematical base. An extensive measurement campaign is performed based on a strict methodology considering different cases in typical indoor scenarios. New loss parameter values are defined to adjust the mathematical model to the behavior of real signals in the campus environment. The experimental results show that the model proposed offers an attenuation average error of 2.5% with respect to the losses measured. In addition, comparison of the proposed model with existing solutions shows that it decreases the average error significantly for all scenarios under evaluation.
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Alessandro Calcaterra, Fabrizio Frezza, Patrizio Simeoni and Nicola Tedeschi
Numerical Evaluation of Electromagnetic-wave Penetration at Normal Incidence through an Inhomogeneous-wave Approach
This paper presents numerical scenarios concerning penetration in a lossy medium that can be obtained by radiating inhomogeneous electromagnetic waves. Former papers approached this problem, both analytically and numerically, finding requirements and limits of the so-called “deeppenetration” condition, which consists of a wave transmitted in a lossy medium having an attenuation vector whose direction forms the angle of ninety degrees with the normal to the separation surface. The deep-penetration condition always requires an oblique incidence, therefore is not practical in many applications. For this reason, we are interested here in finding whether an inhomogeneous wave guarantees larger penetration than the one obtainable with homogeneous waves, even when the incident wave is normal to the separation surface between two media, i.e. when the deep-penetration condition is not satisfied. We are also interested in verifying numerically whether the lossy-prism structure may achieve larger penetration than the one obtainable through traditional leakywave antennas, and we also wish to propose a lossy-prism design more realistic than the one previously presented in the literature.
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Ismail El Ouargui, Said Safi and Miloud Frikel
Minimum Array Elements for Resolution of Several Direction of Arrival Estimation Methods in Various Noise-Level Environments
The resolution of a Direction of Arrival (DOA) estimation algorithm is determined based on its capability to resolve two closely spaced signals. In this paper, authors present and discuss the minimum number of array elements needed for the resolution of nearby sources in several DOA estimation methods. In the real world, the informative signals are corrupted by Additive White Gaussian Noise (AWGN). Thus, a higher signal-to-noise ratio (SNR) offers a better resolution. Therefore, we show the performance of each method by applying the algorithms in different noise level environments.
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Artur Maździarz
Alarm Correlation in Mobile Telecommunications Networks based on k-means Cluster Analysis Method
Event correlation and root cause analysis play a fundamental role in the process of troubleshooting all technical faults and malfunctions. An in-depth, complicated multiprotocol analysis can be greatly supported or even replaced by a troubleshooting methodology based on data analysis approaches. The mobile telecommunications domain has been experiencing rapid development recently. Introduction of new technologies and services, as well as multivendor environment distributed across the same geographical area create a lot of challenges in network operation routines. Maintenance tasks have been recently becoming more and more complicated, time consuming and require big data analyses to be performed. Most network maintenance activities are completed manually by experts using raw network management information available in the network management system via multiple applications and direct database queries. With these circumstances considered, identification of network failures is a very difficult, if not an impossible task. This explains why effective yet simple tools and methods providing network operators with carefully selected, essential information are needed. Hence, in this paper efficient approximated alarm correlation algorithm based on the k-means cluster analysis method is proposed.
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