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Introduction to Multiple Antenna Communications and Reconfigurable Surfaces
| Introduction to Multiple Antenna Communications and Reconfigurable Surfaces |
| Autore | Björnson Emil |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Now Publishers, 2024 |
| Descrizione fisica | 1 online resource (687 pages) |
| Disciplina | 621.384 |
| Altri autori (Persone) | DemirÖzlem Tuğfe |
| Collana | NowOpen Series. |
| Soggetto topico | WAP (wireless) technology |
| Soggetto non controllato | Wireless Communications, MIMO, Multiple Antenna Communication, Reconfigurable Surfaces, OFDM, Wideband Communications |
| ISBN | 1-63828-315-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Introduction to Multiple Antenna Communications and Reconfigurable Surfaces -- Copyright -- Contents -- Preface -- How to Use This Book -- Acknowledgments -- Chapter 1: Introduction and Motivation -- Transmitted and Received Signal Power -- Signal-to-Noise Ratio -- Fraunhofer Distance -- Antenna Directivity Gains -- Revisiting the Signal-to-Noise Ratio -- Three Main Benefits of Having Multiple Antennas -- Beamforming Gain -- Spatial Multiplexing -- Spatial Diversity -- Exercises -- Chapter 2: Theoretical Foundations -- Complex Numbers and Algebra -- Vector Analysis -- Matrix Analysis -- Probability Theory -- Gaussian Distribution -- Complex Gaussian Distribution -- Covariance and Conditional Distribution -- Multivariate Complex Gaussian Distribution -- Rayleigh, Exponential, and χ2 Distribution -- Cumulative Distribution Function -- Random Process -- Signal Modeling -- Complex Baseband Representation -- From Continuous Time to Discrete Time -- Basic Wireless Channel Modeling -- Discrete Memoryless Channel Model -- Performance Metrics -- Basic Capacity Results -- Estimation Theory -- MMSE Estimation of Complex Gaussian Variables -- LMMSE Estimation of Arbitrarily Distributed Variables -- Monte Carlo Methods for Statistical Inference -- Estimating the Mean Value -- Estimating the Error Probability -- Empirical Cumulative Distribution Function -- Detection Theory -- Bayesian Detection -- Neyman-Pearson Detection -- Frequency Domain and Discrete Fourier Transform -- Interpretation of Signal Frequencies -- Finite Impulse Response Filters -- Temporal and Spatial Frequencies -- Exercises -- Chapter 3: Capacity of Point-to-Point MIMO Channels -- Impact of Power and Bandwidth on the Capacity -- Capacity of SIMO Channels -- Alternative Combining Vectors -- Capacity of MISO Channels -- Capacity of MIMO Channels.
Geometric Interpretation of MIMO Transmission -- Duality and Alternative Capacity Expressions -- Arbitrary Precoding and Successive Interference Cancellation -- Exercises -- Chapter 4: Line-of-Sight Point-to-Point MIMO Channels -- Basic Properties of Antenna Arrays -- Modeling of Line-of-Sight SIMO Channels -- Uniform Linear Array at the Receiver -- SIMO Channel Capacity with ULA -- Array Factor and Spatial Filtering -- Acquiring Channel State Information -- Maximum Likelihood Channel Estimation -- Modeling of Line-of-Sight MISO Channels -- MISO Channel Capacity with ULA -- Beamwidth of the Transmitted Signal -- Grid of Orthogonal Beams -- Impact of Aperture Length and Antenna Spacing -- Modeling of Line-of-Sight MIMO Channels -- MIMO Channel Capacity with ULAs and Planar Wavefronts -- MIMO Channel Capacity with Distributed Antennas -- MIMO Channel Capacity in the Radiative Near-Field -- Three-Dimensional Far-Field Channel Modeling -- Array Response Vector with a ULA in Three Dimensions -- Array Response Vector with a Uniform Planar Array -- Horizontal and Vertical Beamwidths with UPAs -- Effective Array Response with Directive Antennas -- Effective Isotropic Radiated Power -- MIMO Channels with Arbitrary ULAs -- Polarization of Electromagnetic Waves -- Channel Capacity with Dual-Polarized Antennas -- Impact of Finite Cross-Polar Discrimination -- MIMO Channel Capacity with Dual-Polarized ULAs -- Exercises -- Chapter 5: Non-Line-of-Sight Point-to-Point MIMO Channels -- Basics of Multipath Propagation and Rayleigh Fading -- Rich Multipath Propagation: Rayleigh Fading -- Independent Rayleigh Fading in SIMO and MISO Channels -- Independent Rayleigh Fading in MIMO Channels -- Slow and Fast Fading Versus the Channel Coherence Time -- Definitions of Slow and Fast Fading -- Capacity Concept with Slow Fading -- ϵ-Outage Capacity. Receive Diversity in SIMO Systems -- Transmit Diversity in MISO Systems -- Joint Transmit and Receive Diversity in MIMO Systems -- Capacity Concept with Fast Fading -- Ergodic Capacity of i.i.d. Rayleigh Fading SIMO Channels -- Ergodic Capacity of i.i.d. Rayleigh Fading MIMO Channels -- Block Fading and Channel Estimation -- Pilot-Based Channel Estimation -- Ergodic Rate with Imperfect CSI at the Receiver -- Ergodic Rate with Imperfect CSI Available Everywhere -- Sparse Multipath Propagation and Dual Polarization -- Clustered Multipath Propagation -- Beamspace Representation -- Fading Channels with Dual-Polarized Antennas -- Exercises -- Chapter 6: Capacity of Multi-User MIMO Channels -- A Practical Issue with Point-to-Point MIMO Systems -- Capacity Definition in Uplink and Downlink -- Max-Min Fairness -- Maximum Sum Rate -- Uplink Communications -- Orthogonal Multiple Access -- Non-Orthogonal Multiple Access -- Uplink Multi-User MIMO with Non-Linear Processing -- Uplink Multi-User MIMO with Linear Processing -- Alternative Linear Uplink Processing Schemes -- Power Control for Max-Min Fairness -- Downlink Communications -- Orthogonal Multiple Access -- Non-Orthogonal Multiple Access -- Downlink Multi-User MIMO with Non-Linear Processing -- Downlink Multi-User MIMO with Linear Processing -- Alternative Linear Downlink Processing Schemes -- Power Allocation for Max-Min Fairness -- Exercises -- Chapter 7: Wideband MIMO Channels and Practical Aspects -- Basics of Multicarrier Modulation -- Orthogonal Frequency-Division Multiplexing (OFDM) -- Capacity of SISO-OFDM Channels -- Capacity of MIMO-OFDM Channels -- Digital Beamforming Architecture -- Clustered Multipath Propagation and Hybrid Beamforming -- One Dominant Cluster: Analog Beamforming is Sufficient -- A Few Dominant Clusters: Hybrid Beamforming is Sufficient. Practical Implementations and Terminology -- Evolution of Cellular Technology -- MIMO-Related Terminology -- Exercises -- Chapter 8: Localization and Sensing with MIMO -- Direction-of-Arrival Estimation -- Conventional Non-Parametric Beamforming Method -- Non-Parametric Capon Beamforming -- Joint Azimuth and Elevation DOA Estimation -- Parametric Subspace-Based Methods -- Localization -- TOA-Based Localization -- TDOA-Based Localization -- DOA-Based Localization -- Target Detection -- Radar Range Equation -- Target Detection with the Swerling 1 Target Model -- Target Detection with the Swerling 2 Target Model -- Different Types of Radar Antenna Arrays -- Integrated Sensing and Communication -- Exercises -- Chapter 9: Reconfigurable Surfaces -- Basic Physics of Reflecting Surfaces -- Beam Pattern from a Reflecting Surface -- Reconfigurable Reflection from Heterogeneous Surfaces -- Terminology and Implementation Aspects -- Narrowband Communication using Reconfigurable Surfaces -- Line-of-Sight Channel Modeling and Surface Placement -- Acquiring Channel State Information and Feedback Signaling -- Wideband Communication using Reconfigurable Surfaces -- Impulse Response of a Metaatom -- OFDM-Based Channel Model with a Reconfigurable Surface -- Wideband Capacity Maximization -- MIMO Applications of Reconfigurable Surfaces -- Enhanced Point-to-Point MIMO Communication -- Enhanced Multi-User MIMO Communication -- Enhanced Target Detection -- Exercises -- Appendix -- Mathematical Notation -- Specific Notation -- Abbreviations -- References -- Index -- About the Authors. |
| Record Nr. | UNINA-9910800148703321 |
Björnson Emil
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| Now Publishers, 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mobile Edge Computing [[electronic resource]]
| Mobile Edge Computing [[electronic resource]] |
| Autore | Zhang Yan |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (123 p.) |
| Collana | Simula SpringerBriefs on Computing |
| Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology |
| Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
| ISBN | 3-030-83944-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
| Record Nr. | UNISA-996464547003316 |
|
Zhang Yan
|
||
| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Mobile Edge Computing
| Mobile Edge Computing |
| Autore | Zhang Yan |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (123 p.) |
| Collana | Simula SpringerBriefs on Computing |
| Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology Informàtica a la perifèria Sistemes de comunicacions mòbils Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
| ISBN | 3-030-83944-3 |
| Classificazione | COM000000COM051460TEC007000TEC061000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
| Record Nr. | UNINA-9910502647303321 |
|
Zhang Yan
|
||
| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
