On Efficiency And Intelligence Of Next Generation Wireless Networks

The ever-increasing demand for data-hungry wireless services and rapid proliferation of wireless devices in sub-6 GHz band have pushed the current wireless technologies to a breaking point, necessitating efficient and intelligent strategies to utilize scarce communication resources. This thesis aims at leveraging novel communication frameworks, artificial intelligence techniques, and synergies between them in bringing efficiency and intelligence to the next generation of wireless networks.In the first chapter of this thesis, we propose a novel spectrum sharing scheme to address spectrum shortage, a fundamental issue in current and future wireless networks. Our proposed scheme enables transparent spectrum utilization for a small cognitive radio network by leveraging two interference management techniques that are not reliant on inter-network coordination, fine-grained synchronization, and knowledge about other occupants of the spectrum. We further extend this idea in the second chapter of this thesis and enable concurrent device-to-device and cellular communications in cellular networks where the base station and wireless devices exploit interference management techniques to avoid causing interference to each other, making concurrent spectrum utilization possible for both cellular and device-to-device communications. In the third chapter, to enhance spectral efficiency, connectivity, and throughput of Wireless Local Area Networks (WLAN), we propose a non-orthogonal multiplexing scheme (NOMA). In our proposed scheme, the access point (AP) is equipped with a novel precoder design and user grouping which are tailored based on the requirements of power-domain NOMA. Also, a novel successive interference cancellation technique is designed for users which does not require channel estimation to decode the signals and is more resilient to interference compared to the existing techniques. The second part of this thesis focuses on taking advantage of artificial intelligence for solving communication and networking challenges and also taking advantage of novel communication frameworks to let future wireless networks indulge intelligence-oriented networking and resource management. In the fourth chapter, we propose a new solution to solve a long-standing issue ahead of multi-user multiple-input multiple-output (MU-MIMO) communications in WLANs, which is the large sounding overhead for acquiring the channel state information (CSI). Our learning-based solution includes an automated mechanism that enables access points to collect, clear, and balance dataset, and also deep neural networks to compress CSI and reduce the airtime overhead for channel acquisition. However, with provisioning concurrent MU-MIMO and orthogonal frequency division multiple access (OFDMA) in the new generation of WLANs, not only the sounding overhead problem becomes more acute, but it also marries with a complex resource allocation problem which makes designing a practical enabler of MU-MIMO-OFDMA transmissions necessary for WLANs. In the fifth chapter of this thesis, we propose DeepMux, which comprises a deep-learning-based channel sounding and a deep-learning-based resource allocation both of which reside in access points and impose no computational/communication burden on users, enabling efficient downlink MU-MIMO-OFDMA transmissions in WLANs. We finally design a communication framework for accelerating federated learning in future intelligent transportation systems, where heterogeneous capabilities and mobility of users along with limited available bandwidth for communications are huge obstacles toward making the network intelligent in a distributed manner. With the aid of a deadline-driven scheduler and asynchronous uplink multi-user MIMO, our proposed solution reduces data loss at vehicles in a dynamic vehicular environment, making a concrete step toward the practical adoption of federated learning in future transportation systems.

The ever-evolving wireless technology industry is demanding new technologies and standards to ensure a higher quality of experience for global end-users. This developing challenge has enabled researchers to identify the present trend of machine learning as a possible solution, but will it meet business velocity demand? Next-Generation Wireless Networks Meet Advanced Machine Learning Applications is a pivotal reference source that provides emerging trends and insights into various technologies of next-generation wireless networks to enable the dynamic optimization of system configuration and applications within the fields of wireless networks, broadband networks, and wireless communication. Featuring coverage on a broad range of topics such as machine learning, hybrid network environments, wireless communications, and the internet of things; this publication is ideally designed for industry experts, researchers, students, academicians, and practitioners seeking current research on various technologies of next-generation wireless networks.

Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies. The scope and depth of this book are balanced for both beginners to advanced users. Additional references are provided for readers who wish to learn more details about certain subjects. Applications of NGMA outside of communications, including data and computing assisted by machine learning, protocol designs, and others, are also covered. Written by four leading experts in the field, Next Generation Multiple Access includes information on: Foundation and application scenarios for non-orthogonal multiple access (NOMA) systems, including modulation, detection, power allocation, and resource management NOMA’s interaction with alternate applications such as satellite communication systems, terrestrial-satellite communication systems, and integrated sensing Collision resolution, compressed sensing aided massive access, latency management, deep learning enabled massive access, and energy harvesting Holographic-pattern division multiple access, over-the-air transmission, multi-dimensional multiple access, sparse signal detection, and federated meta-learning assisted resource management Next Generation Multiple Access is an essential reference for those who are interested in discovering practical solutions using NGMA technology, including researchers, engineers, and graduate students in the disciplines of information engineering, telecommunications engineering, and computer engineering.

INTELLIGENT SURFACES EMPOWERED 6G WIRELESS NETWORK Integrate intelligent surfaces into the wireless networks of the future. The next generation of wireless technology (6G) promises to transform wireless communication and human interconnectivity like never before. Intelligent surface, which adopts significant numbers of small reflective surfaces to reconfigure wireless connections and improve network performance, has recently been recognized as a critical component for enabling future 6G. The next phase of wireless technology demands engineers and researchers are familiar with this technology and are able to cope with the challenges. Intelligent Surfaces Empowered 6G Wireless Network provides a thorough overview of intelligent surface technologies and their applications in wireless networks and 6G. It includes an introduction to the fundamentals of intelligent surfaces, before moving to more advanced content for engineers who understand them and look to apply them in the 6G realm. Its detailed discussion of the challenges and opportunities posed by intelligent surfaces empowered wireless networks makes it the first work of its kind. Intelligent Surfaces Empowered 6G Wireless Network readers will also find: An editorial team including the original pioneers of intelligent surface technology. Detailed coverage of subjects including MIMO, terahertz, NOMA, energy harvesting, physical layer security, computing, sensing, machine learning, and more. Discussion of hardware design, signal processing techniques, and other critical aspects of IRS engineering. Intelligent Surfaces Empowered 6G Wireless Network is a must for students, researchers, and working engineers looking to understand this vital aspect of the coming 6G revolution.

With the growing popularity of wireless networks in recent years, the need to increase network capacity and efficiency has become more prominent in society. This has led to the development and implementation of heterogeneous networks. Resource Allocation in Next-Generation Broadband Wireless Access Networks is a comprehensive reference source for the latest scholarly research on upcoming 5G technologies for next generation mobile networks, examining the various features, solutions, and challenges associated with such advances. Highlighting relevant coverage across topics such as energy efficiency, user support, and adaptive multimedia services, this book is ideally designed for academics, professionals, graduate students, and professionals interested in novel research for wireless innovations.

Enabling Technologies for Next Generation Wireless Communications provides up-to-date information on emerging trends in wireless systems, their enabling technologies and their evolving application paradigms. This book includes the latest trends and developments toward next generation wireless communications. It highlights the requirements of next generation wireless systems, limitations of existing technologies in delivering those requirements and the need to develop radical new technologies. It focuses on bringing together information on various technological developments that are enablers vital to fulfilling the requirements of future wireless communication systems and their applications. Topics discussed include spectrum issues, network planning, signal processing, transmitter, receiver, antenna technologies, channel coding, security and application of machine learning and deep learning for wireless communication systems. The book also provides information on enabling business models for future wireless systems. This book is useful as a resource for researchers and practitioners worldwide, including industry practitioners, technologists, policy decision-makers, academicians, and graduate students.

Enabling Technologies for Next Generation Wireless Communications provides up-to-date information on emerging trends in wireless systems, their enabling technologies and their evolving application paradigms. This book includes the latest trends and developments toward next generation wireless communications. It highlights the requirements of next generation wireless systems, limitations of existing technologies in delivering those requirements and the need to develop radical new technologies. It focuses on bringing together information on various technological developments that are enablers vital to fulfilling the requirements of future wireless communication systems and their applications. Topics discussed include spectrum issues, network planning, signal processing, transmitter, receiver, antenna technologies, channel coding, security and application of machine learning and deep learning for wireless communication systems. The book also provides information on enabling business models for future wireless systems. This book is useful as a resource for researchers and practitioners worldwide, including industry practitioners, technologists, policy decision-makers, academicians, and graduate students.

This comprehensive text/reference examines the various challenges to secure, efficient and cost-effective next-generation wireless networking. Topics and features: presents the latest advances, standards and technical challenges in a broad range of emerging wireless technologies; discusses cooperative and mesh networks, delay tolerant networks, and other next-generation networks such as LTE; examines real-world applications of vehicular communications, broadband wireless technologies, RFID technology, and energy-efficient wireless communications; introduces developments towards the ‘Internet of Things’ from both a communications and a service perspective; discusses the machine-to-machine communication model, important applications of wireless technologies in healthcare, and security issues in state-of-the-art networks.

Optical networks have been in commercial deployment since the early 1980s as a result of advances in optical, photonic, and material technologies. Although the initial deployment was based on silica ?ber with a single wavelength modulated at low data rates, it was quickly demonstrated that ?ber can deliver much more bandwidth than any other transmission medium, twisted pair wire, coaxial cable, or wireless. Since then, the optical network evolved to include more exciting technologies, gratings, optical ?lters, optical multiplexers, and optical ampli?ers so that today a single ?ber can transport an unprecedented aggregate data rate that exceeds Tbps, and this is not the upper limit yet. Thus, the ?ber optic network has been the network of choice, and it is expected to remain so for many generationsto come, for both synchronousand asynchronouspayloads; voice, data, video, interactive video, games, music, text, and more. In the last few years, we have also witnessed an increase in network attacks as a result of store andforwardcomputer-basednodes. These attackshave manymaliciousobjectives:harvestsomeone else’s data, impersonate another user, cause denial of service, destroy ?les, and more. As a result, a new ?eld in communicationis becomingimportant,communicationnetworksand informationse- rity. In fact, the network architect and system designer is currently challenged to include enhanced features such as intruder detection, service restoration and countermeasures, intruder avoidance, and so on. In all, the next generation optical network is intelligent and able to detect and outsmart malicious intruders.

The text provides a comprehensive study of the application of advanced artificial intelligence (AI) in next-generation wireless communications with a focus on theory, standardization, and core development. It further highlights AI-enabled intelligent architecture for sixth-generation (6G) networks to realize smart resource management, automatic network adjustment, and intelligent service layers. The book covers artificially assisted non-orthogonal multiple access schemes for 6G communication. This book: Discusses the use of AI in various aspects of wireless communications, including channel modeling, signal detection, channel coding design, and resource management Explores technical challenges in the ubiquitous fifth-generation (5G) wireless networks and the prospects of introducing artificial intelligence-based techniques in the envisioned 6G wireless networks Presents potential issues in AI-enabled approaches in wireless communications Covers AI-enabled energy efficiency optimization and cross-layer optimization in the next-generation wireless networks Explains artificially empowered security and privacy schemes in next-generation wireless networks and next-generation mobile management It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.