Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Innovative Solutions for Navigation and Mission Management of Unmanned Aircraft Systems

The last decades have witnessed a significant increase in Unmanned Aircraft Systems (UAS) of all shapes and sizes. UAS are finding many new applications in supporting several human activities, offering solutions to many dirty, dull, and dangerous missions, carried out by military and civilian users. However, limited access to the airspace is the principal barrier to the realization of the full potential that can be derived from UAS capabilities. The aim of this thesis is to support the safe integration of UAS operations, taking into account both the user's requirements and flight regulations. The main technical and operational issues, considered among the principal inhibitors to the integration and wide-spread acceptance of UAS, are identified and two solutions for safe UAS operations are proposed: A. Improving navigation performance of UAS by exploiting low-cost sensors. To enhance the performance of the low-cost and light-weight integrated navigation system based on Global Navigation Satellite System (GNSS) and Micro Electro-Mechanical Systems (MEMS) inertial sensors, an efficient calibration method for MEMS inertial sensors is required. Two solutions are proposed: 1) The innovative Thermal Compensated Zero Velocity Update (TCZUPT) filter, which embeds the compensation of thermal effect on bias in the filter itself and uses Back-Propagation Neural Networks to build the calibration function. Experimental results show that the TCZUPT filter is faster than the traditional ZUPT filter in mapping significant bias variations and presents better performance in the overall testing period. Moreover, no calibration pre-processing stage is required to keep measurement drift under control, improving the accuracy, reliability, and maintainability of the processing software; 2) A redundant configuration of consumer grade inertial sensors to obtain a self-calibration of typical inertial sensors biases. The result is a significant reduction of uncertainty in attitude determination. In conclusion, both methods improve dead-reckoning performance for handling intermittent GNSS coverage. B. Proposing novel solutions for mission management to support the Unmanned Traffic Management (UTM) system in monitoring and coordinating the operations of a large number of UAS. Two solutions are proposed: 1) A trajectory prediction tool for small UAS, based on Learning Vector Quantization (LVQ) Neural Networks. By exploiting flight data collected when the UAS executes a pre-assigned flight path, the tool is able to predict the time taken to fly generic trajectory elements. Moreover, being self-adaptive in constructing a mathematical model, LVQ Neural Networks allow creating different models for the different UAS types in several environmental conditions; 2) A software tool aimed at supporting standardized procedures for decision-making process to identify UAS/payload configurations suitable for any type of mission that can be authorized standing flight regulations. The proposed methods improve the management and safe operation of large-scale UAS missions, speeding up the flight authorization process by the UTM system and supporting the increasing level of autonomy in UAS operations

DRONE DELIVERY OF CBNRECy – DEW WEAPONS Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD)

Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD) is our sixth textbook in a series covering the world of UASs and UUVs. Our textbook takes on a whole new purview for UAS / CUAS/ UUV (drones) – how they can be used to deploy Weapons of Mass Destruction and Deception against CBRNE and civilian targets of opportunity. We are concerned with the future use of these inexpensive devices and their availability to maleficent actors. Our work suggests that UASs in air and underwater UUVs will be the future of military and civilian terrorist operations. UAS / UUVs can deliver a huge punch for a low investment and minimize human casualties.https://newprairiepress.org/ebooks/1046/thumbnail.jp

Unmanned Aircraft Systems in the Cyber Domain

Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions. This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp

Expanding Australia\u27s defence capabilities for technological asymmetric advantage in information, cyber and space in the context of accelerating regional military modernisation: A systemic design approach

Introduction. The aim of the project was to conduct a systemic design study to evaluate Australia\u27sopportunities and barriers for achieving a technological advantage in light of regional military technological advancement. It focussed on the three domains of (1) cybersecurity technology, (2) information technology, and (3) space technology. Research process. Employing a systemic design approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 828 professionals across STEM, space, aerospace, defence/ law enforcement, and ICT, aimed to assess the impact, deployment likelihood, and developmental timelines of the identified technologies. Finally, five experts were interviewed to help elaborate on the findings in the survey and translate them into implications for the ADF. Findings. Key findings revealed significant overlaps in technology clusters, highlighting ten specific technologies or trends as potential force multipliers for the ADF. Among these, cybersecurity of critical infrastructure and optimisation and other algorithmic technologies were recognised for their immediate potential and urgency, suggesting a prioritisation for development investment. The analysis presented a clear imperative for urgent and prioritised technological investments, specifically in cybersecurity and information technologies, followed by space technologies. The research also suggested partnerships that Australia should develop to keep ahead in terms of regional military modernisation. Implications. To maintain a competitive edge, there is an urgent need for investment in the development and application of these technologies, as nearly all disruptive technologies identified for their potential impact, deployment/utilization likelihood, extensive use, and novelty for defence purposes are needed in the near-term (less than 5 years – cybersecurity and information technologies) or medium-term (less than 10 years – space technologies). In line with this, technology investments should be prioritized as follows: Priority 1 includes Cyber Security of critical infrastructure and optimization algorithms; Priority 2 encompasses Unmanned and autonomous systems and weapons, Deep/Machine Learning, and Space-based command and communications systems; and Priority 3 involves Industry 4.0 technologies, Quantum technology, Electromagnetic and navigation warfare systems, Hypersonic weapons, and Directed energy weapons. At the policy level, underfunding, bureaucratic inertia and outdated procurement models needed to be addressed to enhance agility of innovation. More critically, Australia needed to come up with creative ways to recruit, train and retain human capital to develop, manage and use these sophisticated technologies. Finally, in order to maintain a lead over competitors (China, Russia, Iran, North Korea) in the regional military technology competition, the survey and interviews indicate that Australia should continue its military technology alliances with long-standing partners (US, Europe, Israel), broaden its collaborations with more recent partners (Japan, Singapore, South Korea), and establish partnerships with new ones (India, Malaysia, Vietnam, Pacific Island nations). Conclusion. This study sheds light on the future direction for the ADF and Defence in general, underscoring the importance of strategic investments in up-and-coming technologies. By pinpointing strategic voids, potential partnerships, and sovereign technologies with high potential, this report acts as a roadmap for bolstering Australia’s defence capabilities and safeguarding its strategic interests amidst regional technological changes

A Survey on Security and Privacy of 5G Technologies: Potential Solutions, Recent Advancements, and Future Directions

Security has become the primary concern in many telecommunications industries today as risks can have high consequences. Especially, as the core and enable technologies will be associated with 5G network, the confidential information will move at all layers in future wireless systems. Several incidents revealed that the hazard encountered by an infected wireless network, not only affects the security and privacy concerns, but also impedes the complex dynamics of the communications ecosystem. Consequently, the complexity and strength of security attacks have increased in the recent past making the detection or prevention of sabotage a global challenge. From the security and privacy perspectives, this paper presents a comprehensive detail on the core and enabling technologies, which are used to build the 5G security model; network softwarization security, PHY (Physical) layer security and 5G privacy concerns, among others. Additionally, the paper includes discussion on security monitoring and management of 5G networks. This paper also evaluates the related security measures and standards of core 5G technologies by resorting to different standardization bodies and provide a brief overview of 5G standardization security forces. Furthermore, the key projects of international significance, in line with the security concerns of 5G and beyond are also presented. Finally, a future directions and open challenges section has included to encourage future research.European CommissionNational Research Tomsk Polytechnic UniversityUpdate citation details during checkdate report - A

Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond

As the standardization of 5G solidifies, researchers are speculating what 6G will be. The integration of sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing for the exploitation of dense cell infrastructures to construct a perceptive network. In this IEEE Journal on Selected Areas in Commmunications (JSAC) Special Issue overview, we provide a comprehensive review on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider the multiple facets of ISAC and the resulting performance gains. By introducing both ongoing and potential use cases, we shed light on the industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information theoretical limits to physical layer performance tradeoffs, and the cross-layer design tradeoffs. Next, we discuss the signal processing aspects of ISAC, namely ISAC waveform design and receive signal processing. As a step further, we provide our vision on the deeper integration between S&C within the framework of perceptive networks, where the two functionalities are expected to mutually assist each other, i.e., via communication-assisted sensing and sensing-assisted communications. Finally, we identify the potential integration of ISAC with other emerging communication technologies, and their positive impacts on the future of wireless networks

Study of new technological implications to improve food productivity and security in Ghana : case insights into the use of drones in cocoa farming

Since the early 1980’s, in developed countries such as Japan and the United States of America, several technological applications have been used experimentally to boost food production and enhance farming practices, especially in areas which are not geographically accessible for traditional farming practices and machineries.One such technology which has been extensively experimented with and deployed is the Unmanned Aerial Vehicle (UAV), which is an example of technological expertise pioneered by the military. Their growing adaptation in precision agriculture means that UAV have been used on farms in developed countries for crops grown on both small- and large land acreage for the purposes of identifying nutrient deficiencies, diseases, water and soil status, weeds, damage, and plant diagnostics.The study focuses on the adaptation and implementation of UAV in Ghana’s cocoa farming and the position of stakeholders in terms of their acceptance, as the country is currently the world’s second largest producer and exporter of cocoa. The study applies Disruptive Innovation theory and stakeholder theory as a joint conceptual framework by which to examine how new and long-established farms create, sustain, and continuously introduce creative and novel technology in order to maximise food production while assessing stakeholders’ attitudes and roles in the implementation of innovation.Conducted in Nkawie in the Ashanti region of Ghana, the study adopts a qualitative approach, using semi-structured interviews to elicit and collate the views of stakeholders on the implementation of UAV in cocoa farming in Ghana, ultimately analysing the resulting by use of NVivo software. The findings show that traditional practices and superstitious beliefs, lack of credit facilities can impede the acceptance of new innovation.The study identifies a comprehensive pool of stakeholders in the supply chain whose input significantly influences the implementation of UAV. Other key stakeholders maintained that limited support for local drone innovator community, access to funding, and corrupt practices hinder the implementation of this technology, although general awareness of its benefit to cocoa farming cannot be disputed. Despite the difficult conditions that arose during data collection due to COVID restrictions in the study area, 36 participant agreed to participate in the study through interviews. This study makes a specific contribution to the body of literature and policy framework on the drivers and barriers of UAV adoption and implementation in emerging economies such as Ghana in the cocoa farming industr

Federated learning empowered ultra-dense next-generation wireless networks

The evolution of wireless networks, from first-generation (1G) to fifth generation (5G), has facilitated real-time services and intelligent applications powered by artificial intelligence (AI) and machine learning (ML). Nevertheless, prospective applications like autonomous driving and haptic communications necessitate the exploration of beyond fifth-generation (B5G) and sixth-generation (6G) networks, leveraging millimeter-wave (mmWave) and terahertz (THz) technologies. However, these high-frequency bands experience significant atmospheric attenuation, resulting in high signal propagation loss, which necessitates a fundamental reconfiguration of network architectures and paves the way for the emergence of ultra-dense networks (UDNs). Equipped with massive multiple-input multiple-output (mMIMO) and beamforming technologies, UDNs mitigate propagation losses by utilising narrow line-of-sight (LoS) beams to direct radio waves toward specific receiving points, thereby enhancing signal quality. Despite these advancements, UDNs face critical challenges, which include worsened mobility issues in dynamic UDNs due to the susceptibility of LoS links to blockages, data privacy concerns at the network edge when implementing centralised ML training, and power consumption challenges stemming from the deployment of dense small base stations (SBSs) and the integration of cutting edge techniques like edge learning. In this context, this thesis begins by investigating the prevailing issue of beam blockage in UDNs and introduces novel frameworks to address this emerging challenge. The main theme of the first three contributions is to tackle beam blockages and frequent handovers (HOs) through innovative sensing-aided wireless communications. This approach seeks to enhance the situational awareness of UDNs regarding their surroundings by using a variety of sensors commonly found in urban areas, such as vision and radar sensors. While all these contributions share the common goal of proposing sensing-aided proactive HO (PHO) frameworks that intelligently predict blockage events in advance and performs PHO, each of them presents distinctive framework features, contributing significantly to the improvement of UDN operations. To provide further details, the first contribution adhered to conventional centralised model training, while the other contributions employed federated learning (FL), a decentralised collaborative training approach primarily designed to safeguard data privacy. The utilisation of FL technology offers several advantages, including enhanced data privacy, scalability, and adaptability. Simulation results from all these frameworks have demonstrated the remarkable performance of the proposed latency-aware frameworks in improving UDNs’ reliability, maintaining user connectivity, and delivering high levels of quality of experience (QoE) and throughput when compared to existing reactive HO procedures lacking proactive blockage prediction. The fourth contribution is centred on optimising energy management in UDNs and introduces FedraTrees, a lightweight algorithm that integrates decision tree (DT)-based models into the FL setup. FedraTrees challenges the conventional belief that FL is exclusively suited for Neural Network (NN) models by enabling the incorporation of DT models within the FL context. While FedraTrees offers versatility across various applications, this thesis specifically applies it to energy forecasting tasks with the aim of achieving the energy efficiency requirement of UDNs. Simulation results demonstrate that FedraTrees performs remarkably in predicting short-term energy patterns and surpasses the state-of-the-art long short-term memory (LSTM)-based federated averaging (FedAvg) algorithm in terms of reducing computational and communication resources demands