Machine Learning For Mobile Communications

Author : Yonina C. Eldar,Andrea Goldsmith,Deniz Gündüz,H. Vincent Poor
Publisher : Cambridge University Press
Page : 560 pages
File Size : 44,6 Mb
Release : 2022-06-30
Category : Technology & Engineering
ISBN : 9781108967730

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Machine Learning and Wireless Communications by Yonina C. Eldar,Andrea Goldsmith,Deniz Gündüz,H. Vincent Poor Pdf

How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Author : Fa-Long Luo
Publisher : John Wiley & Sons
Page : 490 pages
File Size : 45,9 Mb
Release : 2020-02-10
Category : Technology & Engineering
ISBN : 9781119562252

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Machine Learning for Future Wireless Communications by Fa-Long Luo Pdf

A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Author : Krishna Kant Singh,Akansha Singh,Korhan Cengiz,Dac-Nhuong Le
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 45,5 Mb
Release : 2020-07-08
Category : Computers
ISBN : 9781119640363

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Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks by Krishna Kant Singh,Akansha Singh,Korhan Cengiz,Dac-Nhuong Le Pdf

Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.

Author : Ruisi He,Zhiguo Ding
Publisher : Telecommunications
Page : 491 pages
File Size : 46,7 Mb
Release : 2019-08
Category : Technology & Engineering
ISBN : 9781785616570

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Applications of Machine Learning in Wireless Communications by Ruisi He,Zhiguo Ding Pdf

This detailed and comprehensive reference considers how to combine the disciplines of wireless communications and machine learning. Coverage includes channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications and wireless multimedia communications.

Author : Sinh Cong Lam,Chiranji Lal Chowdhary,Tushar Hrishikesh Jaware,Subrata Chowdhury
Publisher : CRC Press
Page : 214 pages
File Size : 40,7 Mb
Release : 2024-06-17
Category : Technology & Engineering
ISBN : 9781040034392

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Machine Learning for Mobile Communications by Sinh Cong Lam,Chiranji Lal Chowdhary,Tushar Hrishikesh Jaware,Subrata Chowdhury Pdf

Machine Learning for Mobile Communications will take readers on a journey from basic to advanced knowledge about mobile communications and machine learning. For learners at the basic level, this book volume discusses a wide range of mobile communications topics from the system level, such as system design and optimization, to the user level, such as power control and resource allocation. The authors also review state-of-the-art machine learning, one of the biggest emerging trends in both academia and industry. For learners at the advanced level, this book discusses solutions for long-term problems with future mobile communications such as resource allocation, security, power control, and spectral efficiency. The book brings together some of the top mobile communications and machine learning experts throughout the world, who contributed their knowledge and experience regarding system design and optimization. This book: Discusses the 5G new radio system design and architecture as specified in 3GPP documents Highlights the challenges including security and privacy, energy, and spectrum efficiency from the perspective of 5G new radio systems Identifies both theoretical and practical problems that can occur in mobile communication systems Covers machine learning techniques such as autoencoder and Q-learning in a comprehensive manner Explores how to apply machine learning techniques to mobile systems to solve modern problems This book is for senior undergraduate and graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

Author : K. Suganthi,R. Karthik,G. Rajesh,Peter Ho Chiung Ching
Publisher : CRC Press
Page : 296 pages
File Size : 55,8 Mb
Release : 2021-09-14
Category : Technology & Engineering
ISBN : 9781000441819

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Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems by K. Suganthi,R. Karthik,G. Rajesh,Peter Ho Chiung Ching Pdf

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Author : Yonina C. Eldar,Andrea Goldsmith,Deniz Gündüz,H. Vincent Poor
Publisher : Cambridge University Press
Page : 559 pages
File Size : 43,5 Mb
Release : 2022-08-04
Category : Computers
ISBN : 9781108832984

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Machine Learning and Wireless Communications by Yonina C. Eldar,Andrea Goldsmith,Deniz Gündüz,H. Vincent Poor Pdf

Discover connections between these transformative and impactful technologies, through comprehensive introductions and real-world examples.

Author : Com?a, Ioan-Sorin,Trestian, Ramona
Publisher : IGI Global
Page : 356 pages
File Size : 40,7 Mb
Release : 2019-01-25
Category : Technology & Engineering
ISBN : 9781522574590

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Next-Generation Wireless Networks Meet Advanced Machine Learning Applications by Com?a, Ioan-Sorin,Trestian, Ramona Pdf

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.

Author : E. S. Gopi
Publisher : Springer Nature
Page : 643 pages
File Size : 43,6 Mb
Release : 2021-05-28
Category : Technology & Engineering
ISBN : 9789811602894

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Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication by E. S. Gopi Pdf

This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2020) held during October 22nd to 24th 2020, at the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine Learning, Deep learning and Computational intelligence algorithms (b)Wireless communication systems and (c) Mobile data applications and are included in the book. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, power control, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry.

Author : Ruisi He,Zhiguo Ding
Publisher : Unknown
Page : 474 pages
File Size : 46,6 Mb
Release : 2019
Category : Data mining
ISBN : 1523127287

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Applications of Machine Learning in Wireless Communications by Ruisi He,Zhiguo Ding Pdf

In such an era of big data where data mining and data analysis technologies are effective approaches for wireless system evaluation and design, the applications of machine learning in wireless communications have received a lot of attention recently. Machine learning provides feasible and new solutions for the complex wireless communication system design. It has been a powerful tool and popular research topic with many potential applications to enhance wireless communications, e.g. radio channel modelling, channel estimation and signal detection, network management and performance improvement, access control, resource allocation. However, most of the current researches are separated into different fields and have not been well organized and presented yet. It is therefore difficult for academic and industrial groups to see the potentialities of using machine learning in wireless communications. It is now appropriate to present a detailed guidance of how to combine the disciplines of wireless communications and machine learning.

Author : Nur Zincir-Heywood,Marco Mellia,Yixin Diao
Publisher : John Wiley & Sons
Page : 402 pages
File Size : 44,7 Mb
Release : 2021-09-03
Category : Technology & Engineering
ISBN : 9781119675518

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Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning by Nur Zincir-Heywood,Marco Mellia,Yixin Diao Pdf

COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.

Author : Éric Renault,Paul Mühlethaler,Selma Boumerdassi
Publisher : Springer
Page : 400 pages
File Size : 42,8 Mb
Release : 2019-05-10
Category : Computers
ISBN : 9783030199456

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Machine Learning for Networking by Éric Renault,Paul Mühlethaler,Selma Boumerdassi Pdf

This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2253 pages
File Size : 45,6 Mb
Release : 2020-11-27
Category : Computers
ISBN : 9781799877486

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Research Anthology on Artificial Intelligence Applications in Security by Management Association, Information Resources Pdf

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Author : Mingzhe Chen
Publisher : Springer Nature
Page : 189 pages
File Size : 44,8 Mb
Release : 2024-06-12
Category : Electronic
ISBN : 9783031512667

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Communication Efficient Federated Learning for Wireless Networks by Mingzhe Chen Pdf

Author : Revathi Gopalakrishnan,Avinash Venkateswarlu
Publisher : Packt Publishing Ltd
Page : 263 pages
File Size : 52,5 Mb
Release : 2018-12-31
Category : Computers
ISBN : 9781788621427

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Machine Learning for Mobile by Revathi Gopalakrishnan,Avinash Venkateswarlu Pdf

Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease Key FeaturesBuild smart mobile applications for Android and iOS devicesUse popular machine learning toolkits such as Core ML and TensorFlow LiteExplore cloud services for machine learning that can be used in mobile appsBook Description Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices. What you will learnBuild intelligent machine learning models that run on Android and iOSUse machine learning toolkits such as Core ML, TensorFlow Lite, and moreLearn how to use Google Mobile Vision in your mobile appsBuild a spam message detection system using Linear SVMUsing Core ML to implement a regression model for iOS devicesBuild image classification systems using TensorFlow Lite and Core MLWho this book is for If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus