Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

User mobility prediction and management using machine learning

The next generation mobile networks (NGMNs) are envisioned to overcome current user mobility limitations while improving the network performance. Some of the limitations envisioned for mobility management in the future mobile networks are: addressing the massive traffic growth bottlenecks; providing better quality and experience to end users; supporting ultra high data rates; ensuring ultra low latency, seamless handover (HOs) from one base station (BS) to another, etc. Thus, in order for future networks to manage users mobility through all of the stringent limitations mentioned, artificial intelligence (AI) is deemed to play a key role automating end-to-end process through machine learning (ML). The objectives of this thesis are to explore user mobility predictions and management use-cases using ML. First, background and literature review is presented which covers, current mobile networks overview, and ML-driven applications to enable user’s mobility and management. Followed by the use-cases of mobility prediction in dense mobile networks are analysed and optimised with the use of ML algorithms. The overall framework test accuracy of 91.17% was obtained in comparison to all other mobility prediction algorithms through artificial neural network (ANN). Furthermore, a concept of mobility prediction-based energy consumption is discussed to automate and classify user’s mobility and reduce carbon emissions under smart city transportation achieving 98.82% with k-nearest neighbour (KNN) classifier as an optimal result along with 31.83% energy savings gain. Finally, context-aware handover (HO) skipping scenario is analysed in order to improve over all quality of service (QoS) as a framework of mobility management in next generation networks (NGNs). The framework relies on passenger mobility, trains trajectory, travelling time and frequency, network load and signal ratio data in cardinal directions i.e, North, East, West, and South (NEWS) achieving optimum result of 94.51% through support vector machine (SVM) classifier. These results were fed into HO skipping techniques to analyse, coverage probability, throughput, and HO cost. This work is extended by blockchain-enabled privacy preservation mechanism to provide end-to-end secure platform throughout train passengers mobility

Portfolio peak algorithms achieving superior performance for maximizing throughput in WiMAX networks

The Mobile WiMAX IEEE 802.16 standards ensure provision of last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. The WiMAX standards are published by the Institute of Electric and Electronic Engineers (IEEE) and specify the standards of services and transmissions. However, the way how to run these services and when the transmission should be started are not specified in the IEEE standards and it is up to computer scientists to design scheduling algorithms that can best meet the standards. Finding the best way to implement the WiMAX standards through designing efficient scheduler algorithms is a very important component in wireless systems and the scheduling period presents the most common challenging issue in terms of throughput and time delay. The aim of the research presented in this thesis was to design and develop an efficient scheduling algorithm to provide the QoS support for real-time and non-real-time services with the WiMAX Network. This was achieved by combining a portfolio of algorithms, which will control and update transmission with the required algorithm by the various portfolios for supporting QoS such as; the guarantee of a maximum throughput for real-time and non-real-time traffic. Two algorithms were designed in this process and will be discussed in this thesis: Fixed Portfolio Algorithms and Portfolio Peak Algorithm. In order to evaluate the proposed algorithms and test their efficiency for IEEE 802.16 networks, the authors simulated the algorithms in the NS2 simulator. Evaluation of the proposed Portfolio algorithms was carried out through comparing its performance with those of the conventional algorithms. On the other hand, the proposed Portfolio scheduling algorithm was evaluated by comparing its performance in terms of throughput, delay, and jitter. The simulation results suggest that the Fixed Portfolio Algorithms and the Portfolio Peak Algorithm achieve higher performance in terms of throughput than all other algorithms. Keywords: WiMAX, IEEE802.16, QoS, Scheduling Algorithms, Fixed Portfolio Algorithms, and Portfolio Peak Algorithms.The Mobile WiMAX IEEE 802.16 standards ensure provision of last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. The WiMAX standards are published by the Institute of Electric and Electronic Engineers (IEEE) and specify the standards of services and transmissions. However, the way how to run these services and when the transmission should be started are not specified in the IEEE standards and it is up to computer scientists to design scheduling algorithms that can best meet the standards. Finding the best way to implement the WiMAX standards through designing efficient scheduler algorithms is a very important component in wireless systems and the scheduling period presents the most common challenging issue in terms of throughput and time delay. The aim of the research presented in this thesis was to design and develop an efficient scheduling algorithm to provide the QoS support for real-time and non-real-time services with the WiMAX Network. This was achieved by combining a portfolio of algorithms, which will control and update transmission with the required algorithm by the various portfolios for supporting QoS such as; the guarantee of a maximum throughput for real-time and non-real-time traffic. Two algorithms were designed in this process and will be discussed in this thesis: Fixed Portfolio Algorithms and Portfolio Peak Algorithm. In order to evaluate the proposed algorithms and test their efficiency for IEEE 802.16 networks, the authors simulated the algorithms in the NS2 simulator. Evaluation of the proposed Portfolio algorithms was carried out through comparing its performance with those of the conventional algorithms. On the other hand, the proposed Portfolio scheduling algorithm was evaluated by comparing its performance in terms of throughput, delay, and jitter. The simulation results suggest that the Fixed Portfolio Algorithms and the Portfolio Peak Algorithm achieve higher performance in terms of throughput than all other algorithms. Keywords: WiMAX, IEEE802.16, QoS, Scheduling Algorithms, Fixed Portfolio Algorithms, and Portfolio Peak Algorithms

2022 - The Third Annual Fall Symposium of Student Scholars

The full program book from the Fall 2022 Symposium of Student Scholars, held on November 17, 2022. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1026/thumbnail.jp

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

XXV Congreso Argentino de Ciencias de la Computación - CACIC 2019: libro de actas

Trabajos presentados en el XXV Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de Río Cuarto los días 14 al 18 de octubre de 2019 organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y Facultad de Ciencias Exactas, Físico-Químicas y Naturales - Universidad Nacional de Río CuartoRed de Universidades con Carreras en Informátic

XXV Congreso Argentino de Ciencias de la Computación - CACIC 2019: libro de actas

Trabajos presentados en el XXV Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de Río Cuarto los días 14 al 18 de octubre de 2019 organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y Facultad de Ciencias Exactas, Físico-Químicas y Naturales - Universidad Nacional de Río CuartoRed de Universidades con Carreras en Informátic

XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI

XX Workshop de Investigadores en Ciencias de la Computación - WICC 2018 : Libro de actas

Actas del XX Workshop de Investigadores en Ciencias de la Computación (WICC 2018), realizado en Facultad de Ciencias Exactas y Naturales y Agrimensura de la Universidad Nacional del Nordeste, los dìas 26 y 27 de abril de 2018.Red de Universidades con Carreras en Informática (RedUNCI