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2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities : Lake Buena Vista, FL, 21-23 May 2007
2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities : Lake Buena Vista, FL, 21-23 May 2007
Pubbl/distr/stampa IEEE
Disciplina 621.3845
Soggetto topico Wireless communication systems
Wireless communication systems - Design and construction
Mobile communication systems
ISBN 1-5090-8750-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Visualizing Software for Understanding and Analysis
2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities
Record Nr. UNISA-996215962403316
IEEE
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities : Lake Buena Vista, FL, 21-23 May 2007
2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities : Lake Buena Vista, FL, 21-23 May 2007
Pubbl/distr/stampa IEEE
Disciplina 621.3845
Soggetto topico Wireless communication systems
Wireless communication systems - Design and construction
Mobile communication systems
ISBN 1-5090-8750-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Visualizing Software for Understanding and Analysis
2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities
Record Nr. UNINA-9910145107703321
IEEE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
2013 82nd ARFTG Microwave Measurement Conference : Columbus, Ohio, USA, 18-21 November 2013
2013 82nd ARFTG Microwave Measurement Conference : Columbus, Ohio, USA, 18-21 November 2013
Pubbl/distr/stampa IEEE
Disciplina 621.381/3
Soggetto topico Microwave measurements
Microwave circuits
Millimeter waves
Millimeter wave devices
Wireless communication systems - Design and construction
ISBN 1-4799-2935-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti 82nd ARFTG Microwave Measurement Conference
Record Nr. UNISA-996279467303316
IEEE
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
2013 82nd ARFTG Microwave Measurement Conference : Columbus, Ohio, USA, 18-21 November 2013
2013 82nd ARFTG Microwave Measurement Conference : Columbus, Ohio, USA, 18-21 November 2013
Pubbl/distr/stampa IEEE
Disciplina 621.381/3
Soggetto topico Microwave measurements
Microwave circuits
Millimeter waves
Millimeter wave devices
Wireless communication systems - Design and construction
ISBN 1-4799-2935-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti 82nd ARFTG Microwave Measurement Conference
Record Nr. UNINA-9910135182003321
IEEE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Analytical modeling of wireless communication systems / / Carla-Fabiana Chiasserini, Marco Gribaudo, Daniele Manini
Analytical modeling of wireless communication systems / / Carla-Fabiana Chiasserini, Marco Gribaudo, Daniele Manini
Autore Chiasserini Carla-Fabiana
Edizione [1st edition]
Pubbl/distr/stampa London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016
Descrizione fisica 1 online resource (155 p.)
Disciplina 621.384
Collana Stochastic Models in Computer Science and Telecommunication Networks Set
Soggetto topico Wireless communication systems
Wireless communication systems - Design and construction
ISBN 1-119-30774-0
1-119-30773-2
1-119-30772-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface; Introduction; List of Acronyms; PART 1: Sensor Networks; PART 2: Vehicular Networks; PART 3: Cellular Networks; Bibliography; Index; Other titles from ISTE in Networks and Telecommunications; EULA; 1: Fluid Models and Energy Issues; 2: Hybrid Automata for Transient Delay Analysis; 3: Safety Message Broadcasting; 4: Modeling Information Sharing; 5: Multi-RAT Algorithms; 1.1. The fluid-based approach; 1.2. Network scenario; 1.3. The sensor network model; 1.4. Results; 2.1. Event detection in WSNs; 2.2. Model for single-hop network topologies
2.3. Solution technique2.4. Model for multi-hop network topologies; 2.5. Model validation and exploitation results; 2.6. Discussion; 3.1. System description; 3.2. Dissemination of safety messages; 3.3. Assumptions and notations; 3.4. Model outline; 3.5. Computation of the block probability; 3.6. Computation of the probability of first reception; 3.7. Performance evaluation; 4.1. System scenario; 4.2. Modeling information exchange in IVN; 4.3. Computation of the probability of successful information retrieval; 4.4. Model validation and exploitation; 5.1. RAT network; 5.2. Network model
5.3. Model solution5.4. Performance evaluation; 1.1.1. Sensor density and traffic generation; 1.1.2. Data routing; 1.1.3. Local and relay traffic rates; 1.1.4. Channel contention and data transmission; 1.1.5. Mean packet delivery delay; 1.1.6. Sensor active/sleep behavior; 1.3.1. A minimum energy routing strategy: computing u(r'|r); 1.3.2. Channel contention and data transmission: computing s(r) and PR(r); 1.3.3. Mean packet delivery delay: computing q(r); 1.4.1. Model validation; 1.4.2. Model exploitation; 1.4.3. Model solution complexity and accuracy; 2.1.1. The 802.15.4 MAC protocol
2.2.1. Single message transfer2.2.2. Multiple message transfers; 2.3.1. Time discretization; 2.3.2. Transient solution; 2.3.3. Performance metrics computation; 3.2.1. The spatial differentiation approach; 3.2.2. The safety application; 3.6.1. A Gaussian approximation to the transient system behavior; 3.7.1. The impact of power capture; 3.7.2. The case of occupation probability ρ = 1; 3.7.3. The case of homogeneous occupation probability ρ < 1; 3.7.4. The case of inhomogeneous occupation probability; 3.7.5. The impact of the forwarding policy; 4.2.1. Model description; 5.1.1. Scenario
5.1.2. RAT selection strategy5.2.1. Functional rates; 5.3.1. Analytical approach; 5.3.2. Computation of performance metrics; 5.4.1. Setting and results; 1.3.1.1. Computing єm(r, r')|; 1.3.1.2. Computing FkmE(e|r); 1.3.1.3. Computation of the minimum energy path (equation [1.9]); 1.3.1.4. Computing FmE(e|r); 1.3.1.5. Computing ps; r(r'|e); 1.3.1.6. Computing u(r'|r); 1.3.2.1. Computation of the mean number of transmissions freezing the backoff counter; 1.3.3.1. Computing q(r) for always active sensors; 1.3.3.2. Computing q(r) for active and sleeping sensors; 5.1.1.1. Network scenario
5.2.1.1. Rates derivation
Record Nr. UNINA-9910135012303321
Chiasserini Carla-Fabiana  
London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Analytical modeling of wireless communication systems / / Carla-Fabiana Chiasserini, Marco Gribaudo, Daniele Manini
Analytical modeling of wireless communication systems / / Carla-Fabiana Chiasserini, Marco Gribaudo, Daniele Manini
Autore Chiasserini Carla-Fabiana
Edizione [1st edition]
Pubbl/distr/stampa London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016
Descrizione fisica 1 online resource (155 p.)
Disciplina 621.384
Collana Stochastic Models in Computer Science and Telecommunication Networks Set
Soggetto topico Wireless communication systems
Wireless communication systems - Design and construction
ISBN 1-119-30774-0
1-119-30773-2
1-119-30772-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface; Introduction; List of Acronyms; PART 1: Sensor Networks; PART 2: Vehicular Networks; PART 3: Cellular Networks; Bibliography; Index; Other titles from ISTE in Networks and Telecommunications; EULA; 1: Fluid Models and Energy Issues; 2: Hybrid Automata for Transient Delay Analysis; 3: Safety Message Broadcasting; 4: Modeling Information Sharing; 5: Multi-RAT Algorithms; 1.1. The fluid-based approach; 1.2. Network scenario; 1.3. The sensor network model; 1.4. Results; 2.1. Event detection in WSNs; 2.2. Model for single-hop network topologies
2.3. Solution technique2.4. Model for multi-hop network topologies; 2.5. Model validation and exploitation results; 2.6. Discussion; 3.1. System description; 3.2. Dissemination of safety messages; 3.3. Assumptions and notations; 3.4. Model outline; 3.5. Computation of the block probability; 3.6. Computation of the probability of first reception; 3.7. Performance evaluation; 4.1. System scenario; 4.2. Modeling information exchange in IVN; 4.3. Computation of the probability of successful information retrieval; 4.4. Model validation and exploitation; 5.1. RAT network; 5.2. Network model
5.3. Model solution5.4. Performance evaluation; 1.1.1. Sensor density and traffic generation; 1.1.2. Data routing; 1.1.3. Local and relay traffic rates; 1.1.4. Channel contention and data transmission; 1.1.5. Mean packet delivery delay; 1.1.6. Sensor active/sleep behavior; 1.3.1. A minimum energy routing strategy: computing u(r'|r); 1.3.2. Channel contention and data transmission: computing s(r) and PR(r); 1.3.3. Mean packet delivery delay: computing q(r); 1.4.1. Model validation; 1.4.2. Model exploitation; 1.4.3. Model solution complexity and accuracy; 2.1.1. The 802.15.4 MAC protocol
2.2.1. Single message transfer2.2.2. Multiple message transfers; 2.3.1. Time discretization; 2.3.2. Transient solution; 2.3.3. Performance metrics computation; 3.2.1. The spatial differentiation approach; 3.2.2. The safety application; 3.6.1. A Gaussian approximation to the transient system behavior; 3.7.1. The impact of power capture; 3.7.2. The case of occupation probability ρ = 1; 3.7.3. The case of homogeneous occupation probability ρ < 1; 3.7.4. The case of inhomogeneous occupation probability; 3.7.5. The impact of the forwarding policy; 4.2.1. Model description; 5.1.1. Scenario
5.1.2. RAT selection strategy5.2.1. Functional rates; 5.3.1. Analytical approach; 5.3.2. Computation of performance metrics; 5.4.1. Setting and results; 1.3.1.1. Computing єm(r, r')|; 1.3.1.2. Computing FkmE(e|r); 1.3.1.3. Computation of the minimum energy path (equation [1.9]); 1.3.1.4. Computing FmE(e|r); 1.3.1.5. Computing ps; r(r'|e); 1.3.1.6. Computing u(r'|r); 1.3.2.1. Computation of the mean number of transmissions freezing the backoff counter; 1.3.3.1. Computing q(r) for always active sensors; 1.3.3.2. Computing q(r) for active and sleeping sensors; 5.1.1.1. Network scenario
5.2.1.1. Rates derivation
Record Nr. UNINA-9910821465503321
Chiasserini Carla-Fabiana  
London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Artificial intelligence for 6G / / Haesik Kim
Artificial intelligence for 6G / / Haesik Kim
Autore Kim Haesik
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2022]
Descrizione fisica 1 online resource (534 pages)
Disciplina 621.384
Soggetto topico Wireless communication systems - Design and construction
Wireless communication systems - Economic aspects
ISBN 9783030950415
9783030950408
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Abbreviations -- Part I Artificial Intelligence Techniques -- 1 Historical Sketch of Artificial Intelligence -- 1.1 Introduction to Artificial Intelligence -- 1.2 History of Artificial Intelligence -- References -- 2 Artificial Intelligence Ecosystem, Techniques, and Use Cases -- 2.1 Artificial Intelligence Ecosystem -- 2.2 Hardware and Software of Artificial Intelligence -- 2.3 Artificial Intelligence Techniques and Selection -- 2.4 Artificial Intelligence Workflow and Use Cases -- References -- 3 Unsupervised Learning -- 3.1 Types and Performance Metrics of Unsupervised Learning -- 3.2 Clustering Algorithms -- 3.2.1 Hierarchical Clustering -- 3.2.2 Partitional Clustering -- 3.3 Association Rule Mining -- 3.4 Dimensionality Reduction -- 3.5 Problems -- References -- 4 Supervised Learning -- 4.1 Supervised Learning Workflow, Metrics, and Ensemble Methods -- 4.2 Classification of Supervised Learning -- 4.2.1 Decision Tree -- 4.2.2 K-Nearest Neighbours -- 4.2.3 Support Vector Machine -- 4.3 Regression of Supervised Learning -- 4.3.1 Linear Regression -- 4.3.2 Gradient Descent Algorithms -- 4.3.3 Logistic Regression -- 4.4 Problems -- References -- 5 Reinforcement Learning -- 5.1 Introduction to Reinforcement Learning and Markov Decision Process -- 5.2 Model-Based Approaches -- 5.2.1 Policy Iteration -- 5.2.2 Value Iteration -- 5.3 Model-Free Approaches -- 5.3.1 Monte Carlo Methods -- 5.3.2 Temporal difference learning methods -- 5.4 Problems -- References -- 6 Deep Learning -- 6.1 Introduction to Deep Learning -- 6.2 Deep Neural Network -- 6.3 Convolutional Neural Network -- 6.4 Recurrent Neural Network -- 6.5 Problems -- References -- Part II AI-Enabled Communications and Networks Techniques for 6G -- 7 6G Wireless Communications and Networks Systems -- 7.1 6G Wireless Communications and Networks.
7.1.1 6G Use Cases and Requirements -- 7.1.2 6G Timeline, Technical Requirements, and Technical Challenges -- 7.1.3 6G Key Enabling Techniques -- 7.2 AI-Enabled 6G Wireless Communications and Networks -- 7.2.1 AI and ML Contributions to Physical Layers -- 7.2.2 AI and ML Contribution to Data Link and Network Layers and Open Research Challenges -- 7.3 Problems -- References -- 8 AI-Enabled Physical Layer -- 8.1 Design Approaches of AI-Enabled Physical Layer -- 8.2 End-To-End Physical Layer Redesign with Autoencoder -- 8.3 Wireless Channel Models -- 8.4 Signal Detection and Modulation -- 8.5 Channel Estimation -- 8.6 Error Control Coding -- 8.7 MIMO -- 8.8 Problems -- References -- 9 AI-Enabled Data Link Layer -- 9.1 Design Approaches of AI-Enabled Data Link Layer -- 9.2 Radio Resource Allocation and Scheduling -- 9.2.1 Resource Allocation Problems in Wireless Networks and Convex Optimization -- 9.2.2 Resource Allocation Models and Performance Measure -- 9.2.3 Utility Functions and Fairness of Resource Allocation -- 9.2.4 Resource Allocation Using AI Techniques -- 9.3 Handover Using AI Techniques -- 9.4 Problems -- References -- 10 AI-Enabled Network Layer -- 10.1 Design Approaches of AI-Enabled Network Layer -- 10.2 Cellular Systems and Networking -- 10.2.1 Evolution of Cellular Networks -- 10.2.2 Concept of Cellular Systems -- 10.2.3 Cell Planning -- 10.3 Network Traffic Prediction -- 10.3.1 Classic Network Traffic Prediction -- 10.3.2 AI-Enabled Network Traffic Prediction -- 10.4 Problems -- References -- Index.
Record Nr. UNINA-9910558492703321
Kim Haesik  
Cham, Switzerland : , : Springer International Publishing, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas [[electronic resource] ] : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas [[electronic resource] ] : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Autore Lau Vincent K. N
Pubbl/distr/stampa Hoboken, N.J., : John Wiley, c2006
Descrizione fisica 1 online resource (544 p.)
Disciplina 621.3845/6
621.38456
Altri autori (Persone) KwokYu-Kwong Ricky
Collana Wiley series in telecommunications and signal processing
Soggetto topico Wireless communication systems - Design and construction
Soggetto genere / forma Electronic books.
ISBN 1-280-34358-3
9786610343584
0-470-36032-1
0-471-77406-5
0-471-77405-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Channel-Adaptive Technologies and Cross-Layer Designs for Wireless Systems with Multiple Antennas; CONTENTS; List of Figures; List of Tables; Preface; Acknowledgments; PART 1 THEORY; Chapter 1 Basic Concepts in Wireless Communications; 1.1 Overview; 1.2 Wireless Channel Models; 1.2.1 AWGN Channel Model; 1.2.2 Linear Time-Varying Deterministic Spatial Channel; 1.2.3 The Random Channels; 1.2.4 Frequency-Flat Fading Channels; 1.2.5 Frequency-Selective Fading Channels; 1.3 Equivalence of Continuous-Time and Discrete-Time Models; 1.3.1 Concepts of Signal Space; 1.3.2 Sufficient Statistics
1.3.3 Discrete-Time Signal Model-Flat Fading1.3.4 Discrete-Time Channel Model-Frequency-Selective Fading; 1.4 Fundamentals of Information Theory; 1.4.1 Entropy and Mutual Information; 1.4.2 Shannon's Channel Coding Theorem; 1.4.3 Examples of Channel Capacity; 1.5 Summary; Exercises; Chapter 2 MIMO Link with Perfect Channel State Information; 2.1 Overview; 2.2 Mathematical Model of the MIMO Link; 2.2.1 Probabilistic Channels with States; 2.2.2 General Transmission and CSI Feedback Model; 2.2.3 Adaptive-Channel Encoding and Decoding; 2.2.4 Transmit Power Constraint
2.2.5 Causal Feedback Constraint2.3 Ergodic and Outage Channel Capacity; 2.3.1 Ergodic Capacity; 2.3.2 Outage Capacity; 2.4 Channel Capacity with No CSIT and No CSIR; 2.4.1 Fast Flat Fading MIMO Channels; 2.4.2 Block Fading Channels; 2.5 Channel Capacity with Perfect CSIR; 2.5.1 Block Fading Channels; 2.5.2 Fast Flat Fading MIMO Channels; 2.5.3 Effect of Antenna Correlation on Ergodic MIMO Capacity; 2.5.4 Slow Flat Fading MIMO Channels; 2.6 Channel Capacity with Perfect CSIT Only; 2.6.1 Discrete Block Fading Channels; 2.6.2 Discrete Channel with Three States
2.6.3 Fast Flat Fading MIMO Channels2.6.4 Slow Flat Fading MIMO Channels; 2.7 Channel Capacity with Perfect CSIR and Perfect CSIT; 2.7.1 Fast Flat Fading MIMO Channels; 2.7.2 Slow Flat Fading MIMO Channels; 2.8 Summary; Exercises; Chapter 3 MIMO Link with Imperfect Channel State Information; 3.1 Overview; 3.2 Effect of Imperfect CSI Estimation; 3.2.1 CSI Estimation for MIMO Channels; 3.2.2 Capacity Bounds of MIMO Link; 3.3 Effect of Limited Feedback-Optimizing for SNR; 3.3.1 Introduction to Optimizing Effective SNR; 3.3.2 Grassmannian Line Packing
3.3.3 Grassmannian Precoding for MIMO Systems-Spatial Diversity3.3.4 Grassmannian Precoding for MIMO Systems-Spatial Multiplexing; 3.4 Effect of Limited Feedback-Optimizing for Ergodic Capacity; 3.4.1 Channel Capacity with Partial CSIT; 3.4.2 Coding Theorem with Partial CSIT; 3.4.3 Equivalence with Vector Quantization Problem; 3.4.4 Fast Flat Fading MIMO Channels; 3.4.5 Lloyd's Algorithm; 3.4.6 Approximate Closed-Form Solution for Step 1; 3.4.7 Complexity of the Online Adaptation Strategy; 3.4.8 MMSE-SIC Receiver Structure; 3.4.9 Numerical Results and Discussion; 3.5 Summary; Exercises
Chapter 4 Spacetime Coding and Layered Spacetime Coding for MIMO with Perfect Channel State Information
Record Nr. UNINA-9910143564603321
Lau Vincent K. N  
Hoboken, N.J., : John Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas [[electronic resource] ] : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas [[electronic resource] ] : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Autore Lau Vincent K. N
Pubbl/distr/stampa Hoboken, N.J., : John Wiley, c2006
Descrizione fisica 1 online resource (544 p.)
Disciplina 621.3845/6
621.38456
Altri autori (Persone) KwokYu-Kwong Ricky
Collana Wiley series in telecommunications and signal processing
Soggetto topico Wireless communication systems - Design and construction
ISBN 1-280-34358-3
9786610343584
0-470-36032-1
0-471-77406-5
0-471-77405-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Channel-Adaptive Technologies and Cross-Layer Designs for Wireless Systems with Multiple Antennas; CONTENTS; List of Figures; List of Tables; Preface; Acknowledgments; PART 1 THEORY; Chapter 1 Basic Concepts in Wireless Communications; 1.1 Overview; 1.2 Wireless Channel Models; 1.2.1 AWGN Channel Model; 1.2.2 Linear Time-Varying Deterministic Spatial Channel; 1.2.3 The Random Channels; 1.2.4 Frequency-Flat Fading Channels; 1.2.5 Frequency-Selective Fading Channels; 1.3 Equivalence of Continuous-Time and Discrete-Time Models; 1.3.1 Concepts of Signal Space; 1.3.2 Sufficient Statistics
1.3.3 Discrete-Time Signal Model-Flat Fading1.3.4 Discrete-Time Channel Model-Frequency-Selective Fading; 1.4 Fundamentals of Information Theory; 1.4.1 Entropy and Mutual Information; 1.4.2 Shannon's Channel Coding Theorem; 1.4.3 Examples of Channel Capacity; 1.5 Summary; Exercises; Chapter 2 MIMO Link with Perfect Channel State Information; 2.1 Overview; 2.2 Mathematical Model of the MIMO Link; 2.2.1 Probabilistic Channels with States; 2.2.2 General Transmission and CSI Feedback Model; 2.2.3 Adaptive-Channel Encoding and Decoding; 2.2.4 Transmit Power Constraint
2.2.5 Causal Feedback Constraint2.3 Ergodic and Outage Channel Capacity; 2.3.1 Ergodic Capacity; 2.3.2 Outage Capacity; 2.4 Channel Capacity with No CSIT and No CSIR; 2.4.1 Fast Flat Fading MIMO Channels; 2.4.2 Block Fading Channels; 2.5 Channel Capacity with Perfect CSIR; 2.5.1 Block Fading Channels; 2.5.2 Fast Flat Fading MIMO Channels; 2.5.3 Effect of Antenna Correlation on Ergodic MIMO Capacity; 2.5.4 Slow Flat Fading MIMO Channels; 2.6 Channel Capacity with Perfect CSIT Only; 2.6.1 Discrete Block Fading Channels; 2.6.2 Discrete Channel with Three States
2.6.3 Fast Flat Fading MIMO Channels2.6.4 Slow Flat Fading MIMO Channels; 2.7 Channel Capacity with Perfect CSIR and Perfect CSIT; 2.7.1 Fast Flat Fading MIMO Channels; 2.7.2 Slow Flat Fading MIMO Channels; 2.8 Summary; Exercises; Chapter 3 MIMO Link with Imperfect Channel State Information; 3.1 Overview; 3.2 Effect of Imperfect CSI Estimation; 3.2.1 CSI Estimation for MIMO Channels; 3.2.2 Capacity Bounds of MIMO Link; 3.3 Effect of Limited Feedback-Optimizing for SNR; 3.3.1 Introduction to Optimizing Effective SNR; 3.3.2 Grassmannian Line Packing
3.3.3 Grassmannian Precoding for MIMO Systems-Spatial Diversity3.3.4 Grassmannian Precoding for MIMO Systems-Spatial Multiplexing; 3.4 Effect of Limited Feedback-Optimizing for Ergodic Capacity; 3.4.1 Channel Capacity with Partial CSIT; 3.4.2 Coding Theorem with Partial CSIT; 3.4.3 Equivalence with Vector Quantization Problem; 3.4.4 Fast Flat Fading MIMO Channels; 3.4.5 Lloyd's Algorithm; 3.4.6 Approximate Closed-Form Solution for Step 1; 3.4.7 Complexity of the Online Adaptation Strategy; 3.4.8 MMSE-SIC Receiver Structure; 3.4.9 Numerical Results and Discussion; 3.5 Summary; Exercises
Chapter 4 Spacetime Coding and Layered Spacetime Coding for MIMO with Perfect Channel State Information
Record Nr. UNINA-9910830046903321
Lau Vincent K. N  
Hoboken, N.J., : John Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Channel-adaptive technologies and cross-layer designs for wireless systems with multiple antennas : theory and applications / / Vincent K.N. Lau, Yu Kwong Ricky Kwok
Autore Lau Vincent K. N
Pubbl/distr/stampa Hoboken, N.J., : John Wiley, c2006
Descrizione fisica 1 online resource (544 p.)
Disciplina 621.3845/6
Altri autori (Persone) KwokYu-Kwong Ricky
Collana Wiley series in telecommunications and signal processing
Soggetto topico Wireless communication systems - Design and construction
ISBN 1-280-34358-3
9786610343584
0-470-36032-1
0-471-77406-5
0-471-77405-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Channel-Adaptive Technologies and Cross-Layer Designs for Wireless Systems with Multiple Antennas; CONTENTS; List of Figures; List of Tables; Preface; Acknowledgments; PART 1 THEORY; Chapter 1 Basic Concepts in Wireless Communications; 1.1 Overview; 1.2 Wireless Channel Models; 1.2.1 AWGN Channel Model; 1.2.2 Linear Time-Varying Deterministic Spatial Channel; 1.2.3 The Random Channels; 1.2.4 Frequency-Flat Fading Channels; 1.2.5 Frequency-Selective Fading Channels; 1.3 Equivalence of Continuous-Time and Discrete-Time Models; 1.3.1 Concepts of Signal Space; 1.3.2 Sufficient Statistics
1.3.3 Discrete-Time Signal Model-Flat Fading1.3.4 Discrete-Time Channel Model-Frequency-Selective Fading; 1.4 Fundamentals of Information Theory; 1.4.1 Entropy and Mutual Information; 1.4.2 Shannon's Channel Coding Theorem; 1.4.3 Examples of Channel Capacity; 1.5 Summary; Exercises; Chapter 2 MIMO Link with Perfect Channel State Information; 2.1 Overview; 2.2 Mathematical Model of the MIMO Link; 2.2.1 Probabilistic Channels with States; 2.2.2 General Transmission and CSI Feedback Model; 2.2.3 Adaptive-Channel Encoding and Decoding; 2.2.4 Transmit Power Constraint
2.2.5 Causal Feedback Constraint2.3 Ergodic and Outage Channel Capacity; 2.3.1 Ergodic Capacity; 2.3.2 Outage Capacity; 2.4 Channel Capacity with No CSIT and No CSIR; 2.4.1 Fast Flat Fading MIMO Channels; 2.4.2 Block Fading Channels; 2.5 Channel Capacity with Perfect CSIR; 2.5.1 Block Fading Channels; 2.5.2 Fast Flat Fading MIMO Channels; 2.5.3 Effect of Antenna Correlation on Ergodic MIMO Capacity; 2.5.4 Slow Flat Fading MIMO Channels; 2.6 Channel Capacity with Perfect CSIT Only; 2.6.1 Discrete Block Fading Channels; 2.6.2 Discrete Channel with Three States
2.6.3 Fast Flat Fading MIMO Channels2.6.4 Slow Flat Fading MIMO Channels; 2.7 Channel Capacity with Perfect CSIR and Perfect CSIT; 2.7.1 Fast Flat Fading MIMO Channels; 2.7.2 Slow Flat Fading MIMO Channels; 2.8 Summary; Exercises; Chapter 3 MIMO Link with Imperfect Channel State Information; 3.1 Overview; 3.2 Effect of Imperfect CSI Estimation; 3.2.1 CSI Estimation for MIMO Channels; 3.2.2 Capacity Bounds of MIMO Link; 3.3 Effect of Limited Feedback-Optimizing for SNR; 3.3.1 Introduction to Optimizing Effective SNR; 3.3.2 Grassmannian Line Packing
3.3.3 Grassmannian Precoding for MIMO Systems-Spatial Diversity3.3.4 Grassmannian Precoding for MIMO Systems-Spatial Multiplexing; 3.4 Effect of Limited Feedback-Optimizing for Ergodic Capacity; 3.4.1 Channel Capacity with Partial CSIT; 3.4.2 Coding Theorem with Partial CSIT; 3.4.3 Equivalence with Vector Quantization Problem; 3.4.4 Fast Flat Fading MIMO Channels; 3.4.5 Lloyd's Algorithm; 3.4.6 Approximate Closed-Form Solution for Step 1; 3.4.7 Complexity of the Online Adaptation Strategy; 3.4.8 MMSE-SIC Receiver Structure; 3.4.9 Numerical Results and Discussion; 3.5 Summary; Exercises
Chapter 4 Spacetime Coding and Layered Spacetime Coding for MIMO with Perfect Channel State Information
Record Nr. UNINA-9910876511103321
Lau Vincent K. N  
Hoboken, N.J., : John Wiley, c2006
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