Learning Commons | Cardinal Cushing Library
Library Catalog - Books/Videos

Cooperative and cognitive satellite systems

Table of Contents: “…3.2.4 Payload phase errors3.2.4.1 Sensitivity to phase offsets; 3.2.4.2 Imperfect CSI estimation; 3.2.4.3 Outdated CSI; 3.2.5 Feeder link; 3.3 Frame-based precoding design; 3.3.1 Unicast multibeam precoding; 3.3.2 Block-SVD precoding; 3.3.3 Heuristic multicast aware MMSE precoding; 3.3.4 Optimal multigroup multicast precoding; 3.4 User selection for frame-based precoding; 3.4.1 Maximum channel norm selection; 3.4.2 Scheduling based on geographic user clusters; 3.4.2.1 Geographic user clustering; 3.4.3 Semi-parallel user selection; 3.4.4 Multicast aware user scheduling…”
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Optimization of the communication system for networked control systems by Blind, Rainer

Table of Contents: “…Intro; 1 Introduction; 1.1 Motivation; 1.2 Communication System; 1.3 Contribution of the Thesis; 2 Presentation Layer: Linear Precoding; 2.1 Motivation; 2.2 Problem Setup; 2.2.1 Control System; 2.2.2 Communication System; 2.3 Linear Precoding; 2.4 Kalman Filtering with Linear Precoding; 2.5 Examples; 2.6 Summary; 3 Transport Layer: Retransmitting Measurements; 3.1 Problem Setup; 3.2 Transmission and Retransmission Schemes; 3.2.1 Previous Transmission and Retransmission Schemes; 3.2.2 New Retransmission Scheme; 3.3 Example; 3.4 Summary; 4 Transport Layer: Optimal Sampling Time…”
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Evolution of air interface towards 5G : radio access technology and performance analysis by Das, Suvra Sekhar

Table of Contents: “…2.5.2 Receiver Processing2.6 GFDM; 2.6.1 Transmitter; 2.6.2 Receiver; 2.7 Precoded GFDM; 2.7.1 Block IDFT Precoded GFDM; 2.7.1.1 Joint processing; 2.7.1.2 BIDFT-N precoding; 2.7.1.3 Two-stage processing; 2.7.1.4 BIDFT-N precoding; 2.7.1.5 BIDFT-M precoding; 2.7.2 DFT Precoded GFDM; 2.7.3 SVD Precoded GFDM; 2.8 FBMC; 2.8.1 Cosine Modulated Tone; 2.8.2 Filter Characteristics; 2.8.3 Simplified Filter Characteristics; 2.8.4 MMSE Equalizer for FBMC; 2.9 UFMC; 2.9.1 Structure of UFMC Transceiver; 2.9.2 System Model for UFMC; 2.9.3 Output of the Receiver for the UFMC Transceiver Block Diagram.…”
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LTE and LTE advanced : 4G network radio interface by Perez, Andre

Table of Contents: “…Mapping on the spatial layers -- 7.2.6. Precoding.…”
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Wireless MIMO-OFDM Systems with Coherent and Non-Coherent Detection. by Vanaev, Alexander

Table of Contents: “…Acknowledgements; Contents; 1 Introduction; 2 Mobile communication over multipath radio channel ; 3 Diversity and multiplexing MIMO techniques ; 4 MIMO algorithms with spatial precoding ; 5 Broadband MIMO WSSUS channel model ; 6 MIMO-OFDM transmission with spatial multiplexing and diversity ; 7 Differential transmission techniques for OFDM systems ; 8 Conclusions; Bibliography; Curriculum Vitae.…”
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Communication and Localization in UWB Sensor Networks : a Synergetic Approach. by Lücken, Heinrich

Table of Contents: “…3.5.2 Measured Channels3.6 Implementation Issues and Complexity Analysis; 3.7 Conclusion; 4 Multiuser Precoding; 4.1 Dense Networks: Low data rate despite Gigahertz bandwidth; 4.2 System Model; 4.3 Signal-to-Interference-and-Noise Ratio for Multiuser Transmission; 4.4 Precoding Optimization; 4.5 Performance Evaluation; 4.6 Conclusions; 5 Maximum Likelihood Timing Estimation; 5.1 Introduction; 5.1.1 Localization in UWB Sensor Networks; 5.1.2 Channel Model for Localization based on Time of Arrival; 5.1.3 Position Estimation; 5.2 System Model; 5.3 Conventional Time-of-Arrival Estimators.…”
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Future Mobile Communication : From Cooperative Cells to the Post-Cellular Relay Carpet. by Rolny, Raphael T. L.

Table of Contents: “…7.4 Power Control7.5 Conclusions; 8 Post-Cellular Networks; 8.1 System Model; 8.2 Cooperative Precoding; 8.3 Constrained Cluster Optimization; 8.4 Simulation Results & Discussion; 8.5 Conclusions; 9 Conclusions; 9.1 Achievements & Insights; 9.2 Outlook & Future Work.…”
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Evaluation of HSDPA and LTE : From Testbed Measurements to System Level Performance. by Rupp, Markus

Table of Contents: “…EVALUATION OF HSDPA AND LTE; Contents; About the Authors; About the Contributors; Preface; Acknowledgments; List of Abbreviations; Part I CELLULAR WIRELESS STANDARDS; Introduction; References; 1 UMTS High-Speed Downlink Packet Access; 1.1 Standardization and Current Deployment of HSDPA; 1.2 HSDPA Principles; 1.2.1 Network Architecture; 1.2.2 Physical Layer; 1.2.3 MAC Layer; 1.2.4 Radio Resource Management; 1.2.5 Quality of Service Management; 1.3 MIMO Enhancements of HSDPA; 1.3.1 Physical Layer Changes for MIMO; 1.3.2 Precoding; 1.3.3 MAC Layer Changes for MIMO.…”
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Recent advances in information, communications and signal processing

Table of Contents: “…2.2 The 5th-Generation Cellular Mobile Communications2.2.1 Design Issues at Base Station for 5G Cellular Mobile Communication System; 2.2.2 Design Issues at User Equipment for 5G Cellular Mobile Communication System; 2.2.3 Applications and Techniques Supported by 5G Technology; 2.3 Proposed Antenna: Design and Analysis; 2.3.1 Proposed MIMO Antenna Model #1; 2.3.2 Proposed MIMO Antenna Model #2; 2.3.3 Proposed MIMO Antenna Model #3; 2.4 Conclusion; Acknowledgments; References; Chapter 3 -- Random Linear Network Coding with Source Precoding for Multi-session Networks; 3.1 Introduction.…”
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Machine Learning Applications in Electromagnetics and Antenna Array Processing by Martínez-Ramón, Manel

Table of Contents: “…3.4 Kernel Framework for Estimating Signal Models -- 3.4.1 Primal Signal Models -- 3.4.2 RKHS Signal Models -- 3.4.3 Dual Signal Models -- References -- 4 The Basic Concepts of Deep Learning -- 4.1 Introduction -- 4.2 Feedforward Neural Networks -- 4.2.1 Structure of a Feedforward Neural Network -- 4.2.2 Training Criteria and Activation Functions -- 4.2.3 ReLU for Hidden Units -- 4.2.4 Training with the BP Algorithm -- 4.3 Manifold Learning and Embedding Spaces -- 4.3.1 Manifolds, Embeddings, and Algorithms -- 4.3.2 Autoencoders -- 4.3.3 Deep Belief Networks -- References -- 5 Deep Learning Structures -- 5.1 Introduction -- 5.2 Stacked Autoencoders -- 5.3 Convolutional Neural Networks -- 5.4 Recurrent Neural Networks -- 5.4.1 Basic Recurrent Neural Network -- 5.4.2 Training a Recurrent Neural Network -- 5.4.3 Long Short-Term Memory Network -- 5.5 Variational Autoencoders -- References -- 6 Direction of Arrival Estimation -- 6.1 Introduction -- 6.2 Fundamentals of DOA Estimation -- 6.3 Conventional DOA Estimation -- 6.3.1 Subspace Methods -- 6.3.2 Rotational Invariance Technique -- 6.4 Statistical Learning Methods -- 6.4.1 Steering Field Sampling -- 6.4.2 Support Vector Machine MuSiC -- 6.5 Neural Networks for Direction of Arrival -- 6.5.1 Feature Extraction -- 6.5.2 Backpropagation Neural Network -- 6.5.3 Forward-Propagation Neural Network -- 6.5.4 Autoencoder Framework for DOA Estimation with Array Imperfections -- 6.5.5 Deep Learning for DOA Estimation with Random Arrays -- References -- 7 Beamforming -- 7.1 Introduction -- 7.2 Fundamentals of Beamforming -- 7.2.1 Analog Beamforming -- 7.2.2 Digital Beamforming/Precoding -- 7.2.3 Hybrid Beamforming -- 7.3 Conventional Beamforming -- 7.3.1 Beamforming with Spatial Reference -- 7.3.2 Beamforming with Temporal Reference -- 7.4 Support Vector Machine Beamformer -- 7.5 Beamforming with Kernels.…”
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Advanced wireless communications & Internet : future evolving technologies / Advanced wireless communications and Internet by Glisic, Savo G.

Table of Contents: “…8 UltraWide Band Radio 459 -- 8.1 UWB Multiple Access in a Gaussian Channel 459 -- 8.2 The UWB Channel 462 -- 8.3 UWB System with M-ary Modulation 468 -- 8.4 M-ary PPM UWB Multiple Access 476 -- 8.5 Coded UWB Schemes 483 -- 8.6 Multiuser Detection in UWB Radio 486 -- 8.7 UWB with Space / Time Processing 487 -- 8.8 Beamforming for UWB Radio 492 -- References 519 -- 9 Linear Precoding for MIMO Channels 523 -- 9.1 Space / Time Precoders and Equalizers for MIMO Channels 523 -- 9.2 Linear Precoding Based on Convex Optimization Theory 530 -- 9.3 Convex Optimization-Theory-Based Beamforming 540 -- References 561 -- 10 Cognitive Networks 565 -- 10.1 Optimal Channel Sensing in Cognitive Wireless Networks 565 -- 10.2 Optimal Sequential Channel Sensing 568 -- 10.3 Optimal Parallel Multiband Channel Sensing 569 -- 10.4 Collaborative Spectrum Sensing 573 -- 10.5 Multichannel Cognitive MAC 578 -- References 583 -- 11 Relay-AssistedWireless Networks 585 /A. …”
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Signal processing for 5G : algorithms and implementations

Table of Contents: “…Cloud Radio Access Networks: Uplink Channel Estimation and Downlink Precoding / Osvaldo Simeone, Jinkyu Kang, Joonkhyuk Kang, Shlomo Shamai (Shitz) -- Energy-efficient Resource Allocation in 5G with Application to D2D / Alessio Zappone, Francesco Di Stasio, Stefano Buzzi, Eduard Jorswieck -- Ultra Dense Networks: General Introduction and Design Overview / Jianchi Zhu, Xiaoming She, Peng Chen -- Radio-resource Management and Optimization in 5G Networks / Antonis Gotsis, Athanasios Panagopoulos, Stelios Stefanatos, Angeliki Alexiou -- REFERENCE DESIGN AND 5G STANDARD DEVELOPMENT. …”
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SMART ANTENNAS, ELECTROMAGNETIC INTERFERENCE AND MICROWAVE ANTENNAS FOR WIRELESS COMMUNICATIONS

Table of Contents: “…Chapter 4 Joint Relay-source Escalation for SINR Maximization in Multi Relay Networks and Multi Antenna -- 4.1 Main Text -- 4.2 Proposed System -- 4.2.1 System model -- 4.2.2 SINR maximization under relay transmit power and source constraints -- 4.2.3 Source-relay transmit power minimization under QoS constraints -- 4.2.4 Computation of relay precoder -- 4.2.5 Feasibility of the problem -- 4.3 Advantage -- 4.4 Application -- 4.5 Result and Discussion -- 4.5.1 Tools used -- 4.5.2 Simulated results -- 4.6 Conclusion -- References…”
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OTFS : orthogonal time frequency space modulation : a waveform for 6G by Das, Suvra Sekhar, Prasad, Ramjee

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Cognitive radio communication and networking : principles and practice by Qiu, Robert C., 1966-

Table of Contents: “…5.3.5 Generalized Densities 138 -- 5.4 Stieltjes Transform 139 -- 5.4.1 Basic Theorems 143 -- 5.4.2 Large Random Hankel, Markov and Toepltiz Matrices 149 -- 5.4.3 Information Plus Noise Model of Random Matrices 152 -- 5.4.4 Generalized Likelihood Ratio Test Using Large Random Matrices 157 -- 5.4.5 Detection of High-Dimensional Signals in White Noise 164 -- 5.4.6 Eigenvalues of (A + B)-1B and Applications 169 -- 5.4.7 Canonical Correlation Analysis 171 -- 5.4.8 Angles and Distances between Subspaces 173 -- 5.4.9 Multivariate Linear Model 173 -- 5.4.10 Equality of Covariance Matrices 174 -- 5.4.11 Multiple Discriminant Analysis 174 -- 5.5 Case Studies and Applications 175 -- 5.5.1 Fundamental Example of Using Large Random Matrix 175 -- 5.5.2 Stieltjes Transform 177 -- 5.5.3 Free Deconvolution 178 -- 5.5.4 Optimal Precoding of MIMO Systems 178 -- 5.5.5 Marchenko and Pastur's Probability Distribution 179 -- 5.5.6 Convergence and Fluctuations Extreme Eigenvalues 180 -- 5.5.7 Information plus Noise Model and Spiked Models 180 -- 5.5.8 Hypothesis Testing and Spectrum Sensing 183 -- 5.5.9 Energy Estimation in a Wireless Network 185 -- 5.5.10 Multisource Power Inference 187 -- 5.5.11 Target Detection, Localization, and Reconstruction 187 -- 5.5.12 State Estimation and Malignant Attacker in the Smart Grid 191 -- 5.5.13 Covariance Matrix Estimation 193 -- 5.5.14 Deterministic Equivalents 197 -- 5.5.15 Local Failure Detection and Diagnosis 200 -- 5.6 Regularized Estimation of Large Covariance Matrices 200 -- 5.6.1 Regularized Covariance Estimates 201 -- 5.6.2 Banding the Inverse 203 -- 5.6.3 Covariance Regularization by Thresholding 204 -- 5.6.4 Regularized Sample Covariance Matrices 206 -- 5.6.5 Optimal Rates of Convergence for Covariance Matrix Estimation 208 -- 5.6.6 Banding Sample Autocovariance Matrices of Stationary Processes 211 -- 5.7 Free Probability 213 -- 5.7.1 Large Random Matrices and Free Convolution 218 -- 5.7.2 Vandermonde Matrices 221 -- 5.7.3 Convolution and Deconvolution with Vandermonde Matrices 229.…”
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Wireless connectivity : an intuitive and fundamental guide by Popovski, Petar, 1973-

Table of Contents: “…10.8 Statistical Modeling of Wireless Channels 300 -- 10.8.1 Fading Models: Rayleigh and Some Others 301 -- 10.8.2 Randomness in the Path Loss 303 -- 10.9 Reciprocity and How to Use It 303 -- 10.10 Chapter Summary 305 -- 10.11 Further Reading 305 -- 10.12 Problems and Reflections 305 -- 11 Using Two, More, or a Massive Number of Antennas 309 -- 11.1 Assumptions about the Channel Model and the Antennas 310 -- 11.2 Receiving or Transmitting with a Two-Antenna Device 311 -- 11.2.1 Receiver with Two Antennas 311 -- 11.2.2 Using Two Antennas at a Knowledgeable Transmitter 313 -- 11.2.3 Transmit Diversity 314 -- 11.3 Introducing MIMO 315 -- 11.3.1 Spatial Multiplexing 317 -- 11.4 Multiple Antennas for Spatial Division of Multiple Users 319 -- 11.4.1 Digital Interference-Free Beams: Zero Forcing 320 -- 11.4.2 Other Schemes for Precoding and Digital Beamforming 322 -- 11.5 Beamforming and Spectrum Sharing 325 -- 11.6 What If the Number of Antennas is Scaled Massively? …”
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Advanced wireless networks : technology and business models by Glisic, Savo G.

Table of Contents: “…7.2 Wireless Network Microeconomics: Data Sponsoring 286 -- 7.3 Spectrum Pricing for Market Equilibrium 291 -- 7.4 Sequential Spectrum Sharing 300 -- 7.5 Data Plan Trading 308 -- References 315 -- 8 Multi-Hop Cellular Networks 318 -- 8.1 Modeling Multi-Hop Multi-Operator Multi-Technology Wireless Networks 318 -- 8.2 Technology Background 319 -- 8.3 System Model and Notation 321 -- 8.4 m3 Route Discovery Protocols 323 -- 8.5 Performance of m3 Route Discovery Protocols 327 -- 8.6 Protocol Complexity 329 -- 8.7 Traffic Offloading Incentives 330 -- 8.8 Performance Illustrations 335 -- References 344 -- 9 Cognitive Networks 346 -- 9.1 Technology Background 346 -- 9.2 Spectrum Auctions for Multi-hop Cognitive Networks 350 -- 9.3 Compound Auctioning in Multi-hop Cognitive Cellular Networks 363 -- References 388 -- 10 Stochastic Geometry 391 -- 10.1 Background Theory 391 -- References 398 -- 11 Heterogeneous Networks 402 -- 11.1 Preliminaries 402 -- 11.2 Self-Organized Small Cell Networks 404 -- 11.3 Dynamic Network Architecture 411 -- 11.4 Economics of Heterogeneous Networks 434 -- References 443 -- 12 Access Point Selection 446 -- 12.1 Background Technology 446 -- 12.2 Network Selection Game 449 -- 12.3 Joint Access Point Selection and Power Allocation 453 -- 12.4 Joint AP Selection and Beamforming Optimization 463 -- References 474 -- 13 Self-Organizing Networks 478 -- 13.1 Self-Organizing Network Optimization 478 -- 13.2 System Model 478 -- 13.3 Joint Optimization of Tilts and AP Association 481 -- References 484 -- 14 Complex Networks 486 -- 14.1 Evolution Towards Large-Scale Networks 486 -- 14.2 Network Characteristics 491 -- 14.3 Random Graphs 494 -- References 496 -- 15 Massive MIMO 499 -- 15.1 Linearly Precoded Multicellular Downlink System 499 -- 15.2 System Model 503 -- 15.3 Optimization for Perfect Channel State Information 505 -- 15.4 Robust Designs for WSRM Problem 509 -- Appendix A.15 519 -- Appendix B.15 519 -- References 521 -- 16 Network Optimization Theory 523.…”
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An introduction to LTE LTE, LTE-advanced, SAE, VoLTE and 4G mobile communications by Cox, Christopher (Christopher Ian), 1965-

Table of Contents: “…Rank Indication -- 8.5.4. Precoding Matrix Indicator -- 8.5.5. Channel State Reporting Mechanisms -- 8.5.6. …”
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