{"product_id":"massive-mimo-for-future-wireless-communication-systems-isbn-9781394228300","title":"Massive MIMO for Future Wireless Communication Systems","description":"\u003cp\u003e\u003cb\u003eAuthoritative resource discussing the development of advanced massive multiple input multiple output (MIMO) techniques and algorithms for application in 6G\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e analyzes applications and technology trends for massive multiple input multiple output (MIMO) in 6G and beyond, presenting a unified theoretical framework for analyzing the fundamental limits of massive MIMO that considers several practical constraints. In addition, this book develops advanced signal-processing algorithms to enable massive MIMO applications in realistic environments. \u003c\/p\u003e\u003cp\u003eThe book looks closer at applying techniques to massive MIMO in order to meet practical network constraints in 6G networks, such as interference, pathloss, delay, and traffic outage, and provides new insights into real-world deployment scenarios, applications, management, and associated benefits of robust, provably secure, and efficient security and privacy schemes for massive MIMO wireless communication networks. \u003c\/p\u003e\u003cp\u003eTo aid in reader comprehension, this book includes a glossary of terms, resources for further reading via a detailed bibliography, and useful figures and summary tables throughout. \u003c\/p\u003e\u003cp\u003eWith contributions from industry experts and researchers across the world and edited by two leaders in the field, \u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e includes information on: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSignal processing algorithms for cell-free massive MIMO systems and advanced mathematical tools to analyze multiuser dynamics in wireless channels\u003c\/li\u003e\n\u003cli\u003eBit error rate (BER) performance comparisons of different detectors in conventional cell-free massive MIMO systems\u003c\/li\u003e\n\u003cli\u003eEnhancement of massive MIMO using deep learning-based channel estimation and cell-free massive MIMO for wireless federated learning\u003c\/li\u003e\n\u003cli\u003eLow-complexity, self-organizing, and energy-efficient massive MIMO architectures, including the prospects and challenges of Terahertz MIMO systems\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e is an essential resource on the subject for industry and academic researchers, advanced students, scientists, and engineers in the fields of MIMO, antennas, sensing and channel measurements, and modeling technologies. \u003c\/p\u003e\u003cp\u003eAbout the Editors xvii\u003c\/p\u003e \u003cp\u003eList of Contributors xix\u003c\/p\u003e \u003cp\u003ePreface xxv\u003c\/p\u003e \u003cp\u003eAcknowledgments xxxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Fundamentals of Wireless Communications: Massive MIMO Essentials for 6G and Beyond 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWebert Montlouis and Agbotiname Lucky Imoize\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Digital and Analog Sources 4\u003c\/p\u003e \u003cp\u003e1.3 Deterministic and Random Waveforms 5\u003c\/p\u003e \u003cp\u003e1.4 Propagation of Electromagnetic Waves 6\u003c\/p\u003e \u003cp\u003e1.5 Information Measures 7\u003c\/p\u003e \u003cp\u003e1.6 Channel and Information 8\u003c\/p\u003e \u003cp\u003e1.7 Modulation and Demodulation 9\u003c\/p\u003e \u003cp\u003e1.8 Massive MIMO 11\u003c\/p\u003e \u003cp\u003e1.9 Security and Privacy of Wireless Systems 15\u003c\/p\u003e \u003cp\u003e1.10 Conclusion 18\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Security and Privacy of Future Wireless Communication Systems 23\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbdulwaheed Musa, Abdullateef Ola Adebayo, Peace Oluwasijibomi Balogun, and Segun Jacob\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 Overview of the Current State of Massive MIMO Wireless Communication Systems 25\u003c\/p\u003e \u003cp\u003e2.3 Related Reviews 30\u003c\/p\u003e \u003cp\u003e2.4 Security and Privacy Challenges of Future Wireless Communication Systems 35\u003c\/p\u003e \u003cp\u003e2.5 Physical Layer Security and Technologies for Massive MIMO 39\u003c\/p\u003e \u003cp\u003e2.6 Privacy-Enhancing Technologies 44\u003c\/p\u003e \u003cp\u003e2.7 Emerging Technologies 46\u003c\/p\u003e \u003cp\u003e2.8 Potential Threats and Challenges of Future Wireless Communication Systems 47\u003c\/p\u003e \u003cp\u003e2.9 Open Research Issues and the Future of Security and Privacy 48\u003c\/p\u003e \u003cp\u003e2.10 Limitations of the Study 50\u003c\/p\u003e \u003cp\u003e2.11 Lessons Learned 50\u003c\/p\u003e \u003cp\u003e2.12 Conclusion and Future Scope 51\u003c\/p\u003e \u003cp\u003eReferences 52\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Applications of Massive MIMO in Wireless Communication Systems 59\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbdulwaheed Musa, Peace Oluwasijibomi Balogun, and Abdullateef Ola Adebayo\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 59\u003c\/p\u003e \u003cp\u003e3.2 Evolution from MIMO to Massive MIMO and Role in 5G 61\u003c\/p\u003e \u003cp\u003e3.3 Related Works 64\u003c\/p\u003e \u003cp\u003e3.4 Fundamental Limits 67\u003c\/p\u003e \u003cp\u003e3.5 Benefits of Massive MIMO for 6G and Beyond 74\u003c\/p\u003e \u003cp\u003e3.6 Design and Implementation Challenges for Massive MIMO in 6G 76\u003c\/p\u003e \u003cp\u003e3.7 Enabling Technologies for Massive MIMO in 6G 77\u003c\/p\u003e \u003cp\u003e3.8 Applications of Massive MIMO in Wireless Communication Systems 79\u003c\/p\u003e \u003cp\u003e3.9 Recent Advances and Future Outlook for Massive MIMO in 6G 84\u003c\/p\u003e \u003cp\u003e3.10 Limitations of the Study 87\u003c\/p\u003e \u003cp\u003e3.11 Lessons Learned 88\u003c\/p\u003e \u003cp\u003e3.12 Conclusion and Future Scope 89\u003c\/p\u003e \u003cp\u003eReferences 90\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Cell-Free Massive MIMO Technology and Applications in 6G 95\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJoumana Kassam, Daniel Castanheira, Adão Silva, Rui Dinis, and Atílio Gameiro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 95\u003c\/p\u003e \u003cp\u003e4.2 Conventional Cell-Free mMIMO Systems 99\u003c\/p\u003e \u003cp\u003e4.3 Scalable User-Centric Cell-Free mMIMO Systems 107\u003c\/p\u003e \u003cp\u003e4.4 Radio Stripes Cell-Free Systems 113\u003c\/p\u003e \u003cp\u003e4.5 Conclusions and Future Work 116\u003c\/p\u003e \u003cp\u003eAcknowledgment 117\u003c\/p\u003e \u003cp\u003eReferences 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Localization in Massive MIMO Networks: From Far-Field to Near-Field 123\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eParisa Ramezani, Özlem Tuğfe Demir, and Emil Björnson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 123\u003c\/p\u003e \u003cp\u003e5.2 Far-Field DoA Estimation 125\u003c\/p\u003e \u003cp\u003e5.3 Near-Field DoA and Range Estimation 135\u003c\/p\u003e \u003cp\u003e5.4 Conclusions 146\u003c\/p\u003e \u003cp\u003eReferences 148\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Energy-Efficient Uplink Transmission in RIS-Aided M-MIMO IoT Systems 151\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDavid William Marques Guerra, José Carlos Marinello, Ekram Hossain, and Taufik Abrão\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 151\u003c\/p\u003e \u003cp\u003e6.2 Related Works 157\u003c\/p\u003e \u003cp\u003e6.3 System Model for RIS-Aided M-MIMO 160\u003c\/p\u003e \u003cp\u003e6.4 Definitions on Riemannian Manifolds 166\u003c\/p\u003e \u003cp\u003e6.5 Energy-Efficient Uplink Transmission in RIS M-MIMO IoT Systems 168\u003c\/p\u003e \u003cp\u003e6.6 Conclusion and Research Directions 183\u003c\/p\u003e \u003cp\u003eReferences 184\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Energy Efficiency in RIS-Aided Massive MIMO and XL-MIMO Communication Systems 189\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWilson Souza Junior, João Henrique Inacio de Souza, José Carlos Marinello, and Taufik Abrão\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 189\u003c\/p\u003e \u003cp\u003e7.2 General System Model for RIS-Aided M-MIMO 201\u003c\/p\u003e \u003cp\u003e7.3 Energy Efficiency in RIS-Aided M-MIMO 212\u003c\/p\u003e \u003cp\u003e7.4 Energy Efficiency in Demand-Adaptive XL-MIMO Systems 232\u003c\/p\u003e \u003cp\u003e7.5 Conclusions and Perspective 244\u003c\/p\u003e \u003cp\u003eReferences 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 NOMA-Aided Massive MIMO for Next-Generation Networks 251\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVinoth Babu Kumaravelu, Helen Sheeba J., Dipinkrishnan R., Arthi Murugadass, Poongundran Selvaprabhu, Rajeshkumar V., Vetriveeran Rajamani, Anand Sreekantan Thampy, Agbotiname Lucky Imoize, and Webert Montlouis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 251\u003c\/p\u003e \u003cp\u003e8.2 Related Work 254\u003c\/p\u003e \u003cp\u003e8.3 System Model 262\u003c\/p\u003e \u003cp\u003e8.4 Simulations and Discussions 267\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 275\u003c\/p\u003e \u003cp\u003eReferences 275\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Efficient Hybrid Precoding for Millimeter-Wave Massive MIMO-NOMA Systems: A Low-Complexity Approach 281\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSamarendra Nath Sur, Arun Kumar Singh, Agbotiname Lucky Imoize, Joseph Bamidele Awotunde, Debdatta Kandar, and Vinoth Babu Kumaravelu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 281\u003c\/p\u003e \u003cp\u003e9.2 Overview of Basic Precoding Scheme 284\u003c\/p\u003e \u003cp\u003e9.3 Related Work 289\u003c\/p\u003e \u003cp\u003e9.4 Mathematical Model 294\u003c\/p\u003e \u003cp\u003e9.5 Results 296\u003c\/p\u003e \u003cp\u003e9.6 Challenges of Hybrid Precoding and Future Research Scope 299\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 300\u003c\/p\u003e \u003cp\u003eReferences 301\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Intelligent Reflecting Surfaces and Next-Generation Wireless Systems 309\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eYashuai Cao, Hetong Wang, Tiejun Lv, and Wei Ni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 309\u003c\/p\u003e \u003cp\u003e10.2 Related Work 313\u003c\/p\u003e \u003cp\u003e10.3 Intelligent Reflecting Surfaces Hardware and Architectures 314\u003c\/p\u003e \u003cp\u003e10.4 Intelligent Reflecting Surfaces and the Path Loss Model 317\u003c\/p\u003e \u003cp\u003e10.5 IRS-Empowered Slot Scheduling and Cost-Efficient Reflection Optimization 320\u003c\/p\u003e \u003cp\u003e10.6 Two-Timescale Reflection Pattern Design 328\u003c\/p\u003e \u003cp\u003e10.7 Results and Discussions 336\u003c\/p\u003e \u003cp\u003e10.8 Conclusion 340\u003c\/p\u003e \u003cp\u003e10.9 Future Work 341\u003c\/p\u003e \u003cp\u003eReferences 341\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 ABER Performance Evaluation of RIS-Aided Millimeter Wave Massive MIMO System Under 3GPP 5G Channels 347\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVishnu Vardhan Gudla, Vinoth Babu Kumaravelu, Anjana B. S., Poongundran Selvaprabhu, Nivetha Baskar, Helen Sheeba John Kennedy, Samarendra Nath Sur, Webert Montlouis, Agbotiname Lucky Imoize, and Arthi Murugadass\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 347\u003c\/p\u003e \u003cp\u003e11.2 Related Work 353\u003c\/p\u003e \u003cp\u003e11.3 System Model 356\u003c\/p\u003e \u003cp\u003e11.4 Channel Model 358\u003c\/p\u003e \u003cp\u003e11.5 Simulations and Discussions 360\u003c\/p\u003e \u003cp\u003e11.6 Conclusions 365\u003c\/p\u003e \u003cp\u003eReferences 366\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Massive MIMO for Non-terrestrial Wireless Communication Systems 371\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eUnwana Macaulay Ekpe, Agbotiname Lucky Imoize, and Webert Montlouis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 371\u003c\/p\u003e \u003cp\u003e12.2 The Role of Satellites in Future Non-terrestrial Networks 376\u003c\/p\u003e \u003cp\u003e12.3 Signal Processing for Non-terrestrial Network-Based Massive MIMO Systems 381\u003c\/p\u003e \u003cp\u003e12.4 Single-Cell Massive MIMO Linear Precoding Techniques 385\u003c\/p\u003e \u003cp\u003e12.5 Multi-cell Massive MIMO Linear Precoding Techniques 388\u003c\/p\u003e \u003cp\u003e12.6 Security Considerations in a Non-terrestrial Network 392\u003c\/p\u003e \u003cp\u003e12.7 Standards and Interoperability Requirements in a Non-terrestrial Network 395\u003c\/p\u003e \u003cp\u003e12.8 Conclusion and Recommendations 399\u003c\/p\u003e \u003cp\u003eReferences 400\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Artificial Intelligence and Machine Learning for Channel Estimation in Massive MIMO Wireless Communication Systems 403\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eThiruvengadam Sundarrajan Jayaraman, Velmurugan Periyakarupan Gurusamy Sivabalan, Vinoth Babu Kumaravelu, Agbotiname Lucky Imoize, and Helen Sheeba John Kennedy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 403\u003c\/p\u003e \u003cp\u003e13.2 Related Work 406\u003c\/p\u003e \u003cp\u003e13.3 Channel Estimation Using LS and MMSE Estimators 410\u003c\/p\u003e \u003cp\u003e13.5 FL in Cell-Free Massive MIMO: An Overview 429\u003c\/p\u003e \u003cp\u003e13.6 Protection of Privacy of User Data in Cell-Free Massive MIMO Using FL 431\u003c\/p\u003e \u003cp\u003e13.7 Results and Discussions 432\u003c\/p\u003e \u003cp\u003e13.8 Conclusions 437\u003c\/p\u003e \u003cp\u003eReferences 437\u003c\/p\u003e \u003cp\u003eIndex 441\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eWebert Montlouis\u003c\/b\u003e (Fellow, IEEE) received the PhD degree in electrical and computer engineering from Northeastern University, Boston, MA, USA. He is currently with Johns Hopkins University, Baltimore, MD. He has served as Chief Scientist at the Applied Physics Laboratory (APL) and faculty in the Electrical and Computer Engineering department. He has been the chair of the IEEE Massive MIMO standard development working group. He is also the co-Chair of the Massive MIMO working group. Dr, Montlouis served as general co-Chair of the first IEEE Massive MIMO workshop and served as session chair for many IEEE conferences. His research interests are in the areas Multi-Channel System Architecture, Sensing, Next Generation Radar Systems, Wireless Communications 5G and Beyond, Quantum Information Science, Digital signal Processing and Biomedical Signal Processing. He is a Fellow of the IEEE and a member of the IEEE Signal Processing and Communications Societies. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAgbotiname Lucky Imoize\u003c\/b\u003e is a Lecturer in the Department of Electrical and Electronics Engineering at the University of Lagos, Nigeria. Previously, he was a Research Scholar at the Ruhr University Bochum, Germany. He is a Fulbright fellow and a Senior Member of the IEEE.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAuthoritative resource discussing the development of advanced massive multiple input multiple output (MIMO) techniques and algorithms for application in 6G\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e analyzes applications and technology trends for massive multiple input multiple output (MIMO) in 6G and beyond, presenting a unified theoretical framework for analyzing the fundamental limits of massive MIMO that considers several practical constraints. In addition, this book develops advanced signal-processing algorithms to enable massive MIMO applications in realistic environments. \u003c\/p\u003e\u003cp\u003eThe book looks closer at applying techniques to massive MIMO in order to meet practical network constraints in 6G networks, such as interference, pathloss, delay, and traffic outage, and provides new insights into real-world deployment scenarios, applications, management, and associated benefits of robust, provably secure, and efficient security and privacy schemes for massive MIMO wireless communication networks. \u003c\/p\u003e\u003cp\u003eTo aid in reader comprehension, this book includes a glossary of terms, resources for further reading via a detailed bibliography, and useful figures and summary tables throughout. \u003c\/p\u003e\u003cp\u003eWith contributions from industry experts and researchers across the world and edited by two leaders in the field, \u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e includes information on: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSignal processing algorithms for cell-free massive MIMO systems and advanced mathematical tools to analyze multiuser dynamics in wireless channels\u003c\/li\u003e\n\u003cli\u003eBit error rate (BER) performance comparisons of different detectors in conventional cell-free massive MIMO systems\u003c\/li\u003e\n\u003cli\u003eEnhancement of massive MIMO using deep learning-based channel estimation and cell-free massive MIMO for wireless federated learning\u003c\/li\u003e\n\u003cli\u003eLow-complexity, self-organizing, and energy-efficient massive MIMO architectures, including the prospects and challenges of Terahertz MIMO systems\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eMassive MIMO for Future Wireless Communication Systems\u003c\/i\u003e is an essential resource on the subject for industry and academic researchers, advanced students, scientists, and engineers in the fields of MIMO, antennas, sensing and channel measurements, and modeling technologies.\u003c\/p\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47989579776229,"sku":"NP9781394228300","price":140.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781394228300.jpg?v=1761784677","url":"https:\/\/k12savings.com\/products\/massive-mimo-for-future-wireless-communication-systems-isbn-9781394228300","provider":"K12savings","version":"1.0","type":"link"}