Fingerprint Based Localization In Massive Mimo Systems Using Machine Learning And Deep Learning Methods
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Fingerprint Based Localization In Massive Mimo Systems Using Machine Learning And Deep Learning Methods
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Author : Seyedeh Samira Moosavi
language : en
Publisher:
Release Date : 2021
Fingerprint Based Localization In Massive Mimo Systems Using Machine Learning And Deep Learning Methods written by Seyedeh Samira Moosavi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
As wireless communication networks are growing into 5G, an enormous amount of data will be produced and shared on the new platform, which can be employed in promoting new services. Location information of mobile terminals (MTs) is remarkably useful among them, which can be used in different use cases of inquiry and information services, community services, personal tracking, as well as location-aware communications. Nowadays, although the Global Positioning System (GPS) offers the possibility to localize MTs, it has poor performance in urban areas where a direct line-of-sight (LoS) to the satellites is blocked by many tall buildings. Besides, GPS has a high power consumption. Consequently, the ranging based localization techniques, which are based on radio signal information received from MTs such as time-of-arrival (ToA), angle-of-arrival (AoA), and received signal strength (RSS), are not able to provide satisfactory localization accuracy. Therefore, it is a notably challenging problem to provide precise and reliable location information of MTs in complex environments with rich scattering and multipath propagation. Fingerprinting (FP)-based machine learning methods are widely used for localization in complex areas due to their high reliability, cost-efficiency, and accuracy and they are flexible to be used in many systems. In 5G networks, besides accommodating more users at higher data rates with better reliability while consuming less power, high accuracy localization is also required in 5G networks. To meet such a challenge, massive multiple-input multiple-output (MIMO) systems have been introduced in 5G as a powerful and potential technology to not only improve spectral and energy efficiency using relatively simple processing but also provide an accurate locations of MTs using a very large number of antennas combined with high carrier frequencies. There are two types of massive MIMO (M-MIMO), distributed and collocated. Here, we aim to use the FP-based method in M-MIMO systems to provide an accurate and reliable localization system in a 5G wireless network. We mainly focus on the two extremes of the M-MIMO paradigm. A large collocated antenna array (i.e., collocated M-MIMO ) and a large geographically distributed antenna array (i.e., distributed M-MIMO). Then, we extract signal and channel features from the received signal in M-MIMO systems as fingerprints and propose FP-based models using clustering and regression to estimate MT's location. Through this procedure, we are able to improve localization performance significantly and reduce the computational complexity of the FP-based method.
Mimo Communications
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Author : Ahmed Kishk
language : en
Publisher: BoD – Books on Demand
Release Date : 2023-12-20
Mimo Communications written by Ahmed Kishk and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Technology & Engineering categories.
Multiple-input, multiple-output (MIMO) communication technology has become a critical enabler for high-speed wireless communication systems. This edited volume, MIMO Communications – Fundamental Theory, Propagation Channels, and Antenna Systems, is a comprehensive resource for researchers, graduate students, and practicing engineers in wireless communication. The volume is divided into four parts that cover the foundations of wireless communications, antenna techniques, channel modeling, autonomous driving and radars. Experts in the field have authored chapters covering various topics, including capacity analysis of MIMO channels, antenna array design and beamforming techniques, channel modeling and estimation, and the applications of autonomous driving and radars. This book provides a detailed and accessible introduction to the latest research and practical applications in MIMO communication technology. It is an essential resource for anyone interested in learning about MIMO communication technology or looking to deepen their understanding of existing systems.
Machine Learning Deep Learning And Computational Intelligence For Wireless Communication
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Author : E. S. Gopi
language : en
Publisher: Springer Nature
Release Date : 2021-05-28
Machine Learning Deep Learning And Computational Intelligence For Wireless Communication written by E. S. Gopi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Technology & Engineering categories.
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.
Network Security Empowered By Artificial Intelligence
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Author : Yingying Chen
language : en
Publisher: Springer Nature
Release Date : 2024-06-25
Network Security Empowered By Artificial Intelligence written by Yingying Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-25 with Computers categories.
This book introduces cutting-edge methods on security in spectrum management, mobile networks and next-generation wireless networks in the era of artificial intelligence (AI) and machine learning (ML). This book includes four parts: (a) Architecture Innovations and Security in 5G Networks, (b) Security in Artificial Intelligence-enabled Intrusion Detection Systems. (c) Attack and Defense in Artificial Intelligence-enabled Wireless Systems, (d) Security in Network-enabled Applications. The first part discusses the architectural innovations and security challenges of 5G networks, highlighting novel network structures and strategies to counter vulnerabilities. The second part provides a comprehensive analysis of intrusion detection systems and the pivotal role of AI and machine learning in defense and vulnerability assessment. The third part focuses on wireless systems, where deep learning is explored to enhance wireless communication security. The final part broadens the scope, examining the applications of these emerging technologies in network-enabled fields. The advancement of AI/ML has led to new opportunities for efficient tactical communication and network systems, but also new vulnerabilities. Along this direction, innovative AI-driven solutions, such as game-theoretic frameworks and zero-trust architectures are developed to strengthen defenses against sophisticated cyber threats. Adversarial training methods are adopted to augment this security further. Simultaneously, deep learning techniques are emerging as effective tools for securing wireless communications and improving intrusion detection systems. Additionally, distributed machine learning, exemplified by federated learning, is revolutionizing security model training. Moreover, the integration of AI into network security, especially in cyber-physical systems, demands careful consideration to ensure it aligns with the dynamics of these systems. This book is valuable for academics, researchers, and students in AI/ML, network security, and related fields. It serves as a resource for those in computer networks, AI, ML, and data science, and can be used as a reference or secondary textbook.
Emerging Trends In Computing And Expert Technology
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Author : D. Jude Hemanth
language : en
Publisher: Springer Nature
Release Date : 2019-11-07
Emerging Trends In Computing And Expert Technology written by D. Jude Hemanth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Technology & Engineering categories.
This book presents high-quality research papers that demonstrate how emerging technologies in the field of intelligent systems can be used to effectively meet global needs. The respective papers highlight a wealth of innovations and experimental results, while also addressing proven IT governance, standards and practices, and new designs and tools that facilitate rapid information flows to the user. The book is divided into five major sections, namely: “Advances in High Performance Computing”, “Advances in Machine and Deep Learning”, “Advances in Networking and Communication”, “Advances in Circuits and Systems in Computing” and “Advances in Control and Soft Computing”.
Advances In Smart Grid And Renewable Energy
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Author : Karma Sonam Sherpa
language : en
Publisher: Springer Nature
Release Date : 2021-01-04
Advances In Smart Grid And Renewable Energy written by Karma Sonam Sherpa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-04 with Technology & Engineering categories.
This book comprises select proceedings of the international conference ETAEERE 2020, and primarily focuses on renewable energy resources and smart grid technologies. The book provides valuable information on the technology and design of power grid integration on microgrids of green energy sources. Some of the topics covered include solar PV array, hybrid microgrid, daylight harvesting, green computing, photovoltaic applications, nanogrid applications, AC/DC/AC converter for wind energy systems, solar photovoltaic panels, PEM fuel cell system, and biogas run dual-fueled diesel engine. The contents of this book will be useful for researchers and practitioners working in the areas of smart grids and renewable energy generation, distribution, and management.
5g And 6g Enhanced Broadband Communications
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Author : Isiaka Ajewale Alimi
language : en
Publisher: BoD – Books on Demand
Release Date : 2025-01-08
5g And 6g Enhanced Broadband Communications written by Isiaka Ajewale Alimi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-08 with Technology & Engineering categories.
This book explores the transformative impact of 5G and the promising advancements of 6G, offering a comprehensive overview of their technological underpinnings, practical applications, and broader implications. From ultrahigh speeds to unprecedented connectivity, discover how these technologies transform industries and pave the way for innovative applications. Written by leading experts in the field, this book combines theoretical insights with real-world examples, ensuring a comprehensive grasp for researchers, engineers, students, and industry professionals. Stay informed and prepared for the future with this definitive guide to the evolution of broadband communications.
Multipath Exploitation For Emitter Localization Using Ray Tracing Fingerprints And Machine Learning
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Author : Marcelo Nogueira de Sousa
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-01-01
Multipath Exploitation For Emitter Localization Using Ray Tracing Fingerprints And Machine Learning written by Marcelo Nogueira de Sousa and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-01 with Technology & Engineering categories.
The precise localization of radio frequency (RF) transmitters in outdoor environments has been an important research topic in various fields for several years. Nowadays, the functionalities of many electronic devices are based on the position data of a radiofrequency transmitter using a Wireless Sensor Network (WSN). Spatially separated sensor scan measure the signal from the transmitter and estimate its location using parameters such as Time Of Arrival (ToA), Time Difference Of Arrival (TDOA), Received Signal Strength (RSS) or Direction Of Arrival (DOA). However, certain obstacles in the environment can cause reflection, diffraction, or scattering of the signal. This so called multipath effect affects the measurements for the precise location of the transmitter. Previous studies have discarded multipath information and have not considered it valuable for locating the transmitter. Some studies used ray tracing (RT) to create position fingerprints, without reference measurements, in a simulated scenario. Others tested this concept with real measurement data, but this proved to be a more cumbersome method due to practical problems in the outdoor environment. This thesis exploits the concept of Channel Impulse Response (CIR) to address the problem of precision in outdoor localization environments affected by multipath. The study aims to fill the research gap by combining multipath information from simulation with real measurements in a machine learning framework. The research question was whether the localization could be improved by combining real measurements with simulations. We propose a method that uses the multipath fingerprint information from RT simulation with reference transmitters to improve the location estimation. To validate the effectiveness of the proposed method, we implemented a TDoA location system enhanced with multipath fingerprints in an outdoor scenario. This thesis investigated suburban and rural areas using well-defined reflective components to characterize the localization multipath pattern. The results confirm the possibility of using multipath effects with real measurements to enhance the localization in outdoor situations. Instead of rejecting the multipath information, we can use them as an additional source of information.
Sustainable Communication Networks And Application
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Author : P. Karrupusamy
language : en
Publisher: Springer Nature
Release Date : 2019-11-06
Sustainable Communication Networks And Application written by P. Karrupusamy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with Technology & Engineering categories.
This book presents state-of-the-art theories and technologies and discusses developments in the two major fields: engineering and sustainable computing. In this modern era of information and communication technologies [ICT], there is a growing need for new sustainable and energy-efficient communication and networking technologies. The book highlights significant current and potential international research relating to theoretical and practical methods toward developing sustainable communication and networking technologies. In particular, it focuses on emerging technologies such as wireless communications, mobile networks, Internet of things [IoT], sustainability, and edge network models. The contributions cover a number of key research issues in software-defined networks, blockchain technologies, big data, edge/fog computing, computer vision, sentiment analysis, cryptography, energy-efficient systems, and cognitive platforms.
Trust Security And Privacy For Big Data
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Author : Mamoun Alazab
language : en
Publisher: CRC Press
Release Date : 2022-06-30
Trust Security And Privacy For Big Data written by Mamoun Alazab and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Computers categories.
Data has revolutionized the digital ecosystem. Readily available large datasets foster AI and machine learning automated solutions. The data generated from diverse and varied sources including IoT, social platforms, healthcare, system logs, bio-informatics, etc. contribute to and define the ethos of Big Data which is volume, velocity and variety. Data lakes formed by the amalgamation of data from these sources requires powerful, scalable and resilient storage and processing platforms to reveal the true value hidden inside this data mine. Data formats and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart cars, power grids etc., but also highlight the security and privacy issues in this age of big data. Security and privacy in big data is facing many challenges, such as generative adversary networks, efficient encryption and decryption algorithms, encrypted information retrieval, attribute-based encryption, attacks on availability, and reliability. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas. The book provides timely and comprehensive information for researchers and industry partners in communications and networking domains to review the latest results in security and privacy related work of Big Data. It will serve computer science and cybersecurity communities including researchers, academicians, students, and practitioners who have interest in big data trust privacy and security aspects. It is a comprehensive work on the most recent developments in security of datasets from varied sources including IoT, cyber physical domains, big data architectures, studies for trustworthy computing, and approaches for distributed systems and big data security solutions etc.