Optimization and Learning in Energy Efficient Cognitive Radio System

Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized. Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity. In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Optimization models for resource management in two-tier cellular networks

Macro-femtocell network is the most promising two-tier architecture for the cellular network operators because it can improve their current network capacity without additional costs. Nevertheless, the incorporation of femtocells to the existing cellular networks needs to be finely tuned in order to enhance the usage of the limited wireless resources, because the femtocells operate in the same spectrum as the macrocell. In this thesis, we address the resource optimization problem for the OFDMA two-tier networks for scenarios where femtocells are deployed using hybrid access policy. The hybrid access policy is a technique that could provide different levels of service to authorized users and visitors to the femtocell. This method reduces interference received by femtocell subscribers by granting access to nearby public users. These approaches should find a compromise between the level of access granted to public users and the impact on the subscribers satisfaction. This impact should be reduced in terms of performance or through economic compensation. In this work, two specific issues of an OFDMA two-tier cellular network are addressed. The first is the trade-off between macrocell resource usage efficiency and the fairness of the resource distribution among macro mobile users and femtocells. The second issue is the compromise between interference mitigation and granting access to public users without depriving the subscriber downlink transmissions. We tackle these issues by developing several resource allocation models for non-dense and dense femtocell deployment using Linear Programming and one evolutionary optimization method. In addition, the proposed resource allocation models determine the best suitable serving base station together with bandwidth and transmitted power per user in order to enhance the overall network capacity. The first two parts of this work cope with the resource optimization for non-dense deployment using orthogonal and co-channel allocation. Both parts aim at the maximization of the sum of the weighted user data rates. In the first part, several set of weights are introduced to prioritize the use of femtocells for subscribers and public users close to femtocells. In addition, macrocell power control is incorporated to enhance the power distribution among the active downlink transmissions and to improve the tolerance to the environmental noise. The second part enables the spectral reuse and the power adaptation is a three-folded solution that enhances the power distribution over the active downlink transmissions, improves the tolerance to the environmental noise and a given interference threshold, and achieves the target Quality of Service (QoS). To reduce the complexity of the resource optimization problem for dense deployment, the third part of this work divides the optimization problem into subproblems. The main idea is to divide the user and FC sets into disjoint sets taking into account their locations. Thus, the optimization problem can be solved independently in each OFDMA zone. This solution allows the subcarriers reuse among inner macrocell zones and femtocells located in outer macrocell zones and also between femtocells belonging to different clusters if they are located in the same zone. Macrocell power control is performed to avoid the cross-tier interference among macrocell inner zones and inside femtocells located in outer zones. Another well known method used to reduce the complexity of the resource optimization problem is the femtocell clustering. However, finding the optimal cluster configuration together with the resource allocation is a complex optimization problem due to variable number related to the possible cluster configurations. Therefore, the part four of this work deals with a heuristic cluster based resource allocation model and a motivation scheme for femtocell clustering through the allocation of extra resources for subscriber and “visitor user” transmissions. The cluster based resource allocation model maximizes the network throughput while keeping balanced clusters and minimizing the inter-cluster interference. Finally, the proposed solutions are evaluated through extensive numerical simulations and the numerical results are presented to provide a comparison with the related works found in the literature

Smart Surface Radio Environments

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Metasurface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G

The doctoral research abstracts. Vol:11 2017 / Institute of Graduate Studies, UiTM

Foreword: Congratulation to IGS on the continuous effort to publish the 11th issue of the Doctoral Research Abstracts which highlights the research in various disciplines from science and technology, business and administration to social science and humanities. This research abstract issue features the abstracts from 91 PhD doctorates who will receive their scrolls in this 86th UiTM momentous convocation ceremony. This is a special year for the Institute of Graduate Studies where we are celebrating our 20th anniversary. The 20th anniversary is celebrated with pride with an increase in the number of PhD graduates. In this 86th convocation, the number of PhD graduates has increased by 30% compared to the previous convocation. Each research produces an innovation and this year, 91 research innovations have been successfully recognized to have made contributions to the body of knowledge. This is in line with this year UiTM theme that is “Inovasi Melonjak Persaingan Global (Innovation Soars Global Competition)”. Embarking on PhD research may not have been an easy decision for many of you. It often comes at a point in life when the decision to further one’s studies is challenged by the comfort of status quo. I would like it to be known that you have most certainly done UiTM proud by journeying through the scholarly world with its endless challenges and obstacles, and by persevering right till the very end. Again, congratulations to all PhD graduates. As you leave the university as alumni we hope a new relationship will be fostered between you and UiTM to ensure UiTM soars to greater heights. I wish you all the best in your future endeavor. Keep UiTM close to your heart and be our ambassadors wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Energy efficient wireless sensor network topologies and routing for structural health monitoring.

The applicability of wireless sensor networks (WSNs) has dramatically increased from the era of smart farming and environmental monitoring to the recent commercially successful internet of things (IoT) applications. Simultaneously, diversity in WSN applications has led to the application of specific performance requirements, such as fault tolerance, reliability, robustness and survivability. One important application is structural health monitoring (SHM) in airplanes. Airborne Wireless Sensor Network (AWSN) have received considerable attention in recent times, owing to the many issues that are intrinsic to traditional wire-based airplane monitoring systems, such as complicated cable routing, long wiring, wiring degradation over time, installation overhead, etc. This project examines the SHM of aircraft wing and WSN design (ZigBee), and aspects such as node deployment and power efficient routing, vis-à-vis energy harvesting. Node deployment and power efficient routing protocol are related problems, and so this thesis proposes solutions using optimization techniques for Ant Colony Optimization (ACO), and power transmission profiling using Computer Simulation Technology software (CST). There are three wing models; namely NACA64A410 model, Empty NACA64A410 model for the Wing, and Empty Prismatic model of the wing was specified and simulated in CST software. A simulation was carried out between the frequencies of 100 MHz to 5 GHz, and identified significant variations in the Sij parameter between the frequency range 2.4GHz and 2.5GHz. Critical analysis of the obtained results revealed the presence of a significant impact from wing shape and the wing’s inner structure on possible radio wave propagation in the aircraft wing. The different material composition of aircraft wings was also examined to establish the influence of aircraft wing material on radio wave propagation in an aircraft wing. The three materials tested were Perfect Electrical Conductor (PEC), Aluminium, and Carbon Fibre Composites (CFCs). For power transmission profiling (Sij parameter), 130 nodes were deployed in regular and periodic compartments, created by ribs and spars, usually at vantage points and rib openings, so that a direct line of sight could be established. However, four sink nodes were also placed at the wing root, as presented in NC37 and NC38 simulations for aluminium and CFC wing models respectively. The evaluation of signal propagation in aluminium and CFC aircraft wing models revealed CFC wing models allow less transmission than aluminium wing models. A multiple Travelling Salesman (mTSP) problem was formulated and solved, using Ant Colony Optimization in MATLAB to identify optimal topology and optimal routes to support radio propagation in ZigBee networks. Then solving the mTSP problem for different regular deployments of nodes in the wing geometry, it was found that an edgewise communication route was the shortest route for a large number of nodes, wherein 4 fixed sink nodes were placed at the wing root. For a realistic wing model, the different possible configuration of ZigBee units were deduced using rational reasoning, based on results from empty wing models. Besides the determined S-parameter, aircraft wing materials and optimal nodes, the residual energy of each sensor node is also considered an essential criterion to improve the efficiency of ZigBee communications on the aircraft wing. Therefore, a novel hybrid protocol called the Energy-Opportunistic Weighted Minimum Energy (EOWEME) protocol can be formulated and implemented in MATLAB. The comparative results revealed the energy saving of EOWEME protocol is 20% higher compared to the Ad Hoc On-Demand Distance Vector (AODV) routing protocol. However, the need for further energy savings resulted in development of an improved EOWEME protocol when incorporating the clustering concept and the previously determined S-parameter, a number of nodes, and their radiation patterns. Critical evaluation of this improved EOWEME protocol showed a maximum of 10% higher energy savings than the previous EOWEME protocol. To summarize key insights and the results of this thesis, it is apparent that the thesis addresses SHM in aircraft wings, using WSNs from a holistic perspective with the following major contributions, • CST simulations identify power transfer (S-parameter) profiling in various wing models, with no internal structural elements to identify realistic wing with spars, and bars. With an average S-parameter of -107 dB at around 3 m, the communication or transmission range of 1 m was identified to minimize loss of transmitted power. A range less than 1m would cause issues such as interference, reflection etc. • Using a transmission range of 1 m, WSN nodes were assessed for shortest route commensurate with energy efficient packet transmission to sink node from the farthest node; i.e. near the wing tip. The shortest routes converged to travel along the length of the wing in the case of an empty wing model, however it was also observed in a realistic wing model, where internal structural elements constrained node deployment. An average distance of nearly 13 m required data transmitted from the farthest nodes to reach the sink nodes. Increasing the nodes however increased the distance required to up to 20 m in the case of 240 nodes. • A new routing protocol, EOWEME was formulated, showing 20% greater energy savings than AODV in the realistic wing model.PhD in Aerospac

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Communication between nodes for autonomic and distributed management

Doutoramento conjunto MAPi em InformáticaOver the last decade, the most widespread approaches for traditional management were based on the Simple Network Management Protocol (SNMP) or Common Management Information Protocol (CMIP). However, they both have several problems in terms of scalability, due to their centralization characteristics. Although the distributed management approaches exhibit better performance in terms of scalability, they still underperform regarding communication costs, autonomy, extensibility, exibility, robustness, and cooperation between network nodes. The cooperation between network nodes normally requires excessive overheads for synchronization and dissemination of management information in the network. For emerging dynamic and large-scale networking environments, as envisioned in Next Generation Networks (NGNs), exponential growth in the number of network devices and mobile communications and application demands is expected. Thus, a high degree of management automation is an important requirement, along with new mechanisms that promote it optimally and e ciently, taking into account the need for high cooperation between the nodes. Current approaches for self and autonomic management allow the network administrator to manage large areas, performing fast reaction and e ciently facing unexpected problems. The management functionalities should be delegated to a self-organized plane operating within the network, that decrease the network complexity and the control information ow, as opposed to centralized or external servers. This Thesis aims to propose and develop a communication framework for distributed network management which integrates a set of mechanisms for initial communication, exchange of management information, network (re) organization and data dissemination, attempting to meet the autonomic and distributed management requirements posed by NGNs. The mechanisms are lightweight and portable, and they can operate in di erent hardware architectures and include all the requirements to maintain the basis for an e cient communication between nodes in order to ensure autonomic network management. Moreover, those mechanisms were explored in diverse network conditions and events, such as device and link errors, di erent tra c/network loads and requirements. The results obtained through simulation and real experimentation show that the proposed mechanisms provide a lower convergence time, smaller overhead impact in the network, faster dissemination of management information, increase stability and quality of the nodes associations, and enable the support for e cient data information delivery in comparison to the base mechanisms analyzed. Finally, all mechanisms for communication between nodes proposed in this Thesis, that support and distribute the management information and network control functionalities, were devised and developed to operate in completely decentralized scenarios.Durante a última década, protocolos como Simple Network Management Protocol (SNMP) ou Common Management Information Protocol (CMIP) foram as abordagens mais comuns para a gestão tradicional de redes. Essas abordagens têm vários problemas em termos de escalabilidade, devido às suas características de centralização. Apresentando um melhor desempenho em termos de escalabilidade, as abordagens de gestão distribuída, por sua vez, são vantajosas nesse sentido, mas também apresentam uma série de desvantagens acerca do custo elevado de comunicação, autonomia, extensibilidade, exibilidade, robustez e cooperação entre os nós da rede. A cooperação entre os nós presentes na rede é normalmente a principal causa de sobrecarga na rede, uma vez que necessita de colectar, sincronizar e disseminar as informações de gestão para todos os nós nela presentes. Em ambientes dinâmicos, como é o caso das redes atuais e futuras, espera-se um crescimento exponencial no número de dispositivos, associado a um grau elevado de mobilidade dos mesmos na rede. Assim, o grau elevado de funções de automatiza ção da gestão da rede é uma exigência primordial, bem como o desenvolvimento de novos mecanismos e técnicas que permitam essa comunicação de forma optimizada e e ciente. Tendo em conta a necessidade de elevada cooperação entre os elementos da rede, as abordagens atuais para a gestão autonómica permitem que o administrador possa gerir grandes áreas de forma rápida e e ciente frente a problemas inesperados, visando diminuir a complexidade da rede e o uxo de informações de controlo nela gerados. Nas gestões autonómicas a delegação de operações da rede é suportada por um plano auto-organizado e não dependente de servidores centralizados ou externos. Com base nos tipos de gestão e desa os acima apresentados, esta Tese tem como principal objetivo propor e desenvolver um conjunto de mecanismos necessários para a criação de uma infra-estrutura de comunicação entre nós, na tentativa de satisfazer as exigências da gestão auton ómica e distribuída apresentadas pelas redes de futura geração. Nesse sentido, mecanismos especí cos incluindo inicialização e descoberta dos elementos da rede, troca de informação de gestão, (re) organização da rede e disseminação de dados foram elaborados e explorados em diversas condições e eventos, tais como: falhas de ligação, diferentes cargas de tráfego e exigências de rede. Para além disso, os mecanismos desenvolvidos são leves e portáveis, ou seja, podem operar em diferentes arquitecturas de hardware e contemplam todos os requisitos necessários para manter a base de comunicação e ciente entre os elementos da rede. Os resultados obtidos através de simulações e experiências reais comprovam que os mecanismos propostos apresentam um tempo de convergência menor para descoberta e troca de informação, um menor impacto na sobrecarga da rede, disseminação mais rápida da informação de gestão, aumento da estabilidade e a qualidade das ligações entre os nós e entrega e ciente de informações de dados em comparação com os mecanismos base analisados. Finalmente, todos os mecanismos desenvolvidos que fazem parte da infrastrutura de comunicação proposta foram concebidos e desenvolvidos para operar em cenários completamente descentralizados