and wireless energy harvesting; Internet of Things and smart cities; and millimeter 5G Physical Layer: Technology Opportunities and Challenges, video, Reinaldo A. Valenzuela, director of the Wireless Communications Research Department at Bell Labs, Alcatel-Lucent. Each chapter of 5G Physical Layer Technologies contains texts, mathematical analysis, and applications supported by figures, graphs, data tables, appendices, and a list of up to date references, along with an … Where are we today? 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. Working off-campus? Method 497, 11.7.1 Multi-User Linear Zero-Forcing (ZF) Precoding for BC 497, 11.7.2 ZF Precoder Design with Total Transmit Power Constraint 498, 11.7.3 Optimal ZF Precoding with per-Antenna Power Constraint 499, 11.9 Precoding for MIMO Channels with Johan et al. 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. Engineering and Technology (IET, previously called IEE UK) and a Senior Member of Enter your email address below and we will send you your username, If the address matches an existing account you will receive an email with instructions to retrieve your username, In depth coverage of a hot topic the communications and technology industry. 56 research papers published in renowned IEEE/IET journals, refereed 22 international courses on wireless communications and technology. where technologies are not explained in depth or omitted altogether. Ultra-short Pulse … Additional chapters look at millimeter wave propagation losses caused by atmospheric gases, rain, snow, building materials and vegetation; wireless channel modeling and array mutual coupling; massive array configurations and 3D channel modeling; massive MIMO channel estimation schemes and channel reciprocity; 3D beamforming technologies; and linear precoding strategies for multiuser massive MIMO systems. Download Product Flyer is to download PDF in new tab. The physical layer technologies include flexible … Copyright © 2000-document.write(new Date().getFullYear()) by John Wiley & Sons, Inc., or related companies. Furthermore, to … and 3D channel modeling; massive MIMO channel estimation schemes and channel reciprocity; 5G Physical Layer: Principles, Models and Technology Components explains fundamental physical layer design principles, models and components for the 5G new radio access technology – 5G New Radio … In addition, 3GPP has included л/2-BPSK in UL to enable a further reduced peak-to-average power ratio and enhanced power-amplifier efficiency at lower data rates, which is important for mMTC services, for example. The 5G layer-2 include MAC, RLC and PDCP.The 5G layer-3 is RRC layer as shown in 5G protocol stack. 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. summary of the key issues. Refer 5G protocol layer functions >>. of information for design engineers, research and development engineers, the private-public As an example, consider the time it takes to download an 800 MB movie. Every technological The physical layer technologies include flexible multi-carrier waveforms, advanced multi-antenna solutions, and channel coding schemes for a wide range of services, deployments, and frequencies … Principles, Models and Technology Components explains fundamental physical layer design principles, models and components for the 5G new radio access technology – 5G New Radio (NR). The physical layer models include radio wave propagation and hardware impairments for the full range of frequencies considered for the 5G NR (up to 100 GHz). data and measurements are checked. September 2019 It perfectly illustrates how the technology itself will benefit both individual consumers and industry as the world heads towards a more connected state of being. 3D beamforming technologies; and linear precoding strategies for multiuser massive This is a dummy description. soon to become the backbone of IoT connecting devices, machines, and vehicles, Addresses the need for green communications for the 21, Provides a comprehensive support for the advanced mathematics exploited in the COVID-19 Discipline-Specific Online Teaching Resources, Peer Review & Editorial Office Management, The Editor's Role: Development & Innovation, People In Research: Interviews & Inspiration, General & Introductory Electrical & Electronics Engineering, In depth coverage of a hot topic soon to become the backbone of IoT connecting devices, machines, and vehicles, Addresses the need for green communications for the 21, Provides a comprehensive support for the advanced mathematics exploited in the book by including appendices and worked examples, Contributions from the EU research programmes, the International telecommunications companies, and the International standards institutions (ITU; 3GPP; ETSI) are covered in depth, Includes numerous tables and illustrations to aid the reader, Fills the gap in the current literature where technologies are not explained in depth or omitted altogether. tables and illustrations to aid the reader, Fills the gap in the current literature He is also a member of the UK engineering council, a member of the Institute of Download Product Flyer is to download PDF in new tab. 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. Written in a clear and concise manner, this book presents readers with an in-depth Each chapter of 5G Physical Layer Technologies contains texts, mathematical analysis, and applications supported by figures, graphs, data tables, appendices, and a list of up to date references, along with an … ISBN: 978-1-119-52549-3 2 A PHYSICAL LAYER “INFRASTRUCTURE” PERSPECTIVE Are You Ready for 5G? data tables, appendices, and a list of up to date references, along with an executive application presented is modeled in a schematic diagram and is considered in depth It is also an excellent source of information for design … active-passive measurements to characterize 5G from the physical layer to application layer, with particular emphasis on its compar-ison against 4G LTE. 234, 6 mmWave Propagation Modelling: Atmospheric Gaseous and Rain Losses 241, 6.2 Contemporary Radio Wave Propagation Models 242, 6.2.2 Stanford University Interim (SUI) Propagation Model 244, 6.2.3 Modified SUI Model for mmWave Propagation 245, 6.3.2 Attenuation by Atmospheric Gases 250, 6.3.3 ITU Recommendations for Modelling Atmospheric Gaseous Attenuation 252, 6.4 Dry Atmosphere for Attenuation Calculations 256, 6.5 Calculation of Atmospheric Gaseous Attenuation Using ITU-R, 6.6 Rain Attenuation at mmWave Frequency Bands 257, 6.7 The Physical Rain (EXCELL) Capsoni Model 259, 6.7.2 Monoaxial Cell and Biaxial Cell Models 261, 6.7.3 Fitting the Model to the Local Meteorological Data 261, 6.7.4 Development of the Capsoni EXCELL Model 263, 6.8 ITU Recommendations on Rainfall Rate Conversion 265, 6.8.2 Recommendations ITU–R P.530-17 and ITU-R P.838-3 266, 6.8.2.1 Linear and Circular Polarization 266, 6.8.3 Recommendations ITU-R P.1144-6 and ITU-R P.837-7 269, 6.9.1 EM Propagation Properties Through Snow 272, 6.9.2 Transmission Model for Ice Slab 277, 6.9.3 Empirical Model for Snow Attenuation 278, 6.10 Snow Dielectric Constant Formulation Using Strong Fluctuation Theory 281, 7 mmWave Propagation Modelling –Weather, Vegetation, and Building Material Losses 289, 7.2 Attenuation Due to Clouds and Fog 290, 7.4 Modified Gamma Droplets Size Distribution 292, 7.4.1 Analysis of the Size Distribution 292, 7.4.2 Skewness and Kurtosis of Modified Gamma Distribution 294, 7.5 Rayleigh and Mie Scattering Distributions 297, 7.6 ITU Empirical Model for Clouds and Fog Attenuation Calculation 298, 7.7.1 Penetration Losses for Various Building Materials 300, 7.7.2 Penetration Losses for Indoor Obstructions in an Office Environment at 28 GHz 301, 7.7.3 The Penetration Loss for the Exterior of the House 301, 7.8 Modelling the Penetration Loss for Building Materials 302, 7.9 Modelling the Penetration Loss for Indoor Environments 302, 7.10 Attenuation of Propagated Radio Waves in Vegetation 303, 7.10.1 Foliage Propagation Path Models 303, 7.10.2 Review of Horizontal Empirical Models 304, 7.10.3 Weissberger MED Vegetation Loss Model 304, 7.10.4 Recommendation ITU Vegetation Loss Model 305, 7.10.5 The Maximum Attenuation (MA) Vegetation Loss Model 305, 7.10.6 The Modified and Fitted ITU-R (MITU-R) and (FITU-R) Vegetation Loss Models 307, 7.10.8 The Nonzero Gradient (NZG) Vegetation Loss Model 308, 7.10.9 The Dual-Gradient (DG) Vegetation Loss Model 310, 7.10.10 Indoor Vegetation Attenuation Measurement 312, 7.11 Review of Vegetation Loss Using Empirical Models for Slant Propagation Path 312, 7.12 Microphysical Modelling of Vegetation Attenuation 315, 7.13 Attenuation in Vegetation Due to Diffraction 321, 7.15 Propagation Modes Connected with the Vegetation Foliage 322, 7.15.1 Calculation of the Attenuation of the Top Diffracted Component 323, 7.15.2 Attenuation Components Due to Side Diffraction 324, 7.15.3 Attenuation of the Ground Reflection Component 325, 7.15.4 Attenuation of the ‘Through’ or Scattered Component 326, 7.15.5 Combination of the Individual Attenuation Components 326, 7.16 Radiative Energy Transfer (RET)Theory 327, 7.16.2 RET Attenuation Prediction Model 329, 7.16.2.1 Scattering Loss for Slant Radiation 331, 7.16.2.2 Scattering Loss for Normal Radiation 332, 7.16.3 Determination of the Medium-Dependent Parameters from Measurement Data 333, 7.A Lognormal Distributed Random Numbers 336, 7.B Derivation of Cloud Water Droplets Mode Radius 338, 7.C The Complex Relative Permittivity and the Complex Relative Refractive Index Relationship 339, 7.D Step-by-Step Tutorial to Calculate the Excess Through (Scatter) Loss in Vegetation 340, 8 Wireless Channel Modelling and Array Mutual Coupling 347, 8.1 Key Parameters in Wireless Channel Modelling 347, 8.3.1 MIMO Channel Model Based on Perfect CSIT or CSIR 353, 8.3.2 MIMO Channel Model Based on Perfect CSIR and CDIT 353, 8.3.3 MIMO Channel Model Based on Perfect CDIT and CDIR 354, 8.5 Correlation Inspired Channel Models 356, 8.5.2 Formation of Kronecker Channel Model 359, 8.6.2 Formulation of Weichselberger Channel Model 362, 8.8 Mutual Coupling in Wireless Antenna Systems 367, 8.8.2 Mutual Coupling of Antenna Arrays Operating in Transmit and Receive Modes 368, 8.8.3 BS Antennas Mutual Coupling in MIMO Systems 369, 8.8.4 Total Power Collected by the Receiving Array 370, 8.9 Mutual Coupling Constrained on Transmit Radiated Power 372, 8.10 Analysis Voltage Induced at the Receive Antenna Port 372, 8.11 MIMO Channel Capacity of Mutually Coupled Wireless Systems 374, 8.11.2 Users Receiver Noise Consideration 375, 8.11.3 Formulation of MIMO Channel Capacity 376, 8.B Power Collected by the Receive Array is Maximum When S11 = SHRR 382, 9 Massive Array Configurations and 3D Channel Modelling 387, 9.1 Massive Antenna Array Configurations at BS 387, 9.9 Spatial MIMO Channel Model in 3GPP Release 6 399, 9.9.2 Per-Path BS and MS Angle Spread (AS) 400, 9.9.3 Per-Path BS and MS Power Azimuth Spectrum 400, 9.9.4 Definitions of BS and MS Angle Parameters for a Scattering Environment 402, 9.11.1 Correlation Between Channel Parameters in 3GPP Release 6 405, 9.11.2 Generation of Values of DS, AS, SF 405, 9.12 2D Spatial Channel Models (SCMs) 407, 9.12.1 Spatial Channel Models with No Antennas Polarization 407, 9.12.4 Generating Channel Parameters for Urban, Suburban Macrocell, and Urban Microcell Environments 408, 9.13 2D Spatial Channel Models (SCMs) with Antenna Polarization 411, 9.13.1 2D Spatial Channel Model (SCMs) with Polarized Antennas 412, 9.14 3D Channel Models in 3GPP Release 14 413, 9.14.2 Local and Global Coordinate Systems 413, 9.14.6 Estimate of the LOS Probability Using Ray Tracing 419, 9.14.7 LOS Probability in 3GPP Release 14 420, 9.14.9 Fast-Fading Model for 3D Channels 422, 9.14.11.1 Channel Coefficients for NLOS Channel Environment 431, 9.14.11.2 Channel Coefficients for LOS Channel Environment 432, 9.15.1 Blockages Modelling Using Random Shape Theory 434, 9.15.2 Analysis Using Random Shape Theory to Model Buildings 436, 9.15.3 Distance to Closest BS with Building Blockage 436, 9.A Laplace Random Variables Distribution 438, 10 Massive MIMO Channel Estimation Schemes 443, 10.2 Massive MIMO Channels Definition 445, 10.3 Time-Division Duplexing (TDD) Transmission Protocol 447, 10.4 Massive MIMO Channel Estimation in Noncooperative TDD Networks 447, 10.4.1 Uplink Pilots’ Transmission Using the Aligned Pilot Scheme 448, 10.4.2 SINR for Uplink Data Transmission 449, 10.4.3 SINR for Downlink Data Transmission 450, 10.4.4 Massive MIMO Channels Estimation Using Time-Shifted Pilot Scheme (TSPS) 451, 10.5 Channel Estimation Using Coordinated Cells in MIMO System 454, 10.5.1 Bayesian Estimation of Uplink for All Users 455, 10.5.2 Bayesian Desired Channel Estimation with Full Pilot Reuse 458, 10.6 Bayesian Estimation of UL in a Massive MIMO System 460, 10.6.1 Rule of Coordinated Pilot Allocation 461, 10.6.2 Evaluation of the Coordinated Pilot Assignment Protocol 461, 10.7 Arbitrary Correlated Rician Fading Channel 465, 10.7.1 Estimation of Correlated Rician Channels Using MMSE Approach 465, 10.7.2 Pilot Sequence Optimization for Channel Matrix Estimation 467, 10.7.3 Optimal Length of Pilot Sequences 468, 10.8 Massive MIMO Antennas Calibration 469, 10.8.2 Mutual Coupling Calibration Antennas Method 473, 10.9 Pre-precoding/Post-precoding Channel Calibration 479, 10.A Noncooperative TDD Networks: Derivation of the Asymptotic Normalization Factor Equation 482, 10.B Beamforming Vectors for Time-Shifted Pilot Scheme 483, 10.C Derivation of equations (10.48b) and (10.49b) 484, 11 Linear Precoding Strategies for Multi-User Massive MIMO Systems 489, 11.2 Group-Level and Symbol-Level Precoding 490, 11.5 Multi-User MIMO Precoding System Model 493, 11.5.1 Broadcast Channel (BC) System Model 493, 11.5.2 Multiple Access Channels (MAC) System Model with Non-Equal Antennas at Each User 494, 11.5.3 Linear Precoding for Massive MIMO MAC with Equal Antennas at Each User 495, 11.6 Linear Multi-User Transmit Channel Inversion Precoding for BC 496, 11.7 Zero-Forcing Precoding using the Wiesel et al. a book entitled Introduction to CDMA Wireless Communications, written over This article describes 5G NR physical layer. Topics covered include: the evolution of wireless communications; full duplex communications and full dimension MIMO technologies; network virtualization and wireless energy harvesting; Internet of Things and smart cities; and millimeter wave massive MIMO technology. Furthermore, published simulation data and measurements are checked. Download Product Flyer is to download PDF in new tab. The amount of data transported by wireless mobile networks is expected to increase rapidly with 5G. This is a dummy description. In light of the current interest in … LTE supports the QPSK, 16QAM, 64QAM and 256QAM modulation formats, and all of these will also be supported by NR. At the heart of the new 5G mobile communications is a brand new wireless access technology, the 5G New Radio (NR), that will connect 5G radio base stations with various types of 5G devices. Furthermore, published simulation If you do not receive an email within 10 minutes, your email address may not be registered, 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. students, technical managers, service providers, and all professionals involved in at the Centre for Security, Communications and Network Research, University of Plymouth, MOSA ALI ABU-RGHEFF, PHD, is a chartered engineer working Since NR will cover a wide range of use cases, it is likely that the set of supported modulation schemes may expand. The physical layer … It is also an excellent source of … Every technological application presented is modeled in a schematic diagram and is considered in depth through mathematical analysis and performance assessment. Additional chapters look at millimeter wave propagation It perfectly illustrates how the technology itself will benefit both individual consumers Other features include: 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate courses on wireless communications and technology. Ultra-low latency is one of the important aspects of the 5G networks and beyond, and requires modifications and exploitations of promising technologies at the physical-layer (PHY). and industry as the world heads towards a more connected state of being. explains fundamental physical layer design principles, models and components for the 5G new radio access technology – 5G New Radio (NR).. losses caused by atmospheric gases, rain, snow, building materials and vegetation; The physical layer models include radio wave propagation and hardware impairments for the full range of frequencies considered for the 5G NR (up to 100 GHz). To this end, physical layer technologies such as millimeter wave (mmWave), massive multiple-input multiple-output (MIMO), unmanned aerial vehicles (UAVs), physical layer security (PLS), backscatter … The physical layer … For example, 1024QAM may become part of the NR specif… Provides a comprehensive covering of key 3GPP 5G NR physical layer technologies, presented in a clear, tractable fashion, with sufficient mathematics to make it technically coherent; Addresses all key 5G NR technologies, including digital modulation, LDPC and Polar coding, multicarrier based multiple access techniques, … 5G Physical Layer: Principles, Models and Technology Components. He has authored Other features include: 5G Physical Layer Technologies is an essential resource for undergraduate and postgraduate It is also an excellent source of information for design engineers, research and development engineers, the private-public research community, university research academics, undergraduate and postgraduate students, technical managers, service providers, and all professionals involved in the communications and technology industry. Would you like to change to the site? Request permission to reuse content from this site, 1.2 Overview of Contemporary Cellular Wireless Networks 4, 1.3 Evolution of Wireless Communications in 3GPP Releases 7, 1.4 Multiuser Wireless Network Capacity Regions 10, 1.4.1 The Capacity Region for Multiuser Channel 12, 1.4.2 Analysis of Degraded BC with Superposition Coding 12, 1.4.3 The Capacity Region for Multiuser MIMO Channel 14, 1.7 Green Wireless Communications for the Twenty-First Century 20, 1.8.4 BS Power Consumption at Variable Load 26, 1.A Tutorials on Theory and Techniques of Optimization Mathematics: Basics 33, 1.A.1 Optimization of Unconstrained Function with a Single Variable 33, 1.A.2 Optimization of Unconstrained Function with Multiple Variables 34, 1.B Theory of Optimization Mathematics 36, 1.C Karush–Kuhn–Tucker (KKT) Conditions 39, 2 5G Enabling Technologies: Small Cells, Full-Duplex Communications, and Full-Dimension MIMO Technologies 43, 2.2 The Rationale for 5G Enabling Technologies 45, 2.4 Cloud-Based Radio Access Network (C-RAN) 49, 2.4.1 Resource Management Between Macrocells and Small Cells 51, 2.4.4 Automatic Self-Organising Network (SON) 56, 2.5 Cache-Enabled Small-Cell Networks (CE-SCNs) 57, 2.5.1 File Delivery Performance Analysis of CE-SCN 58, 2.5.2 Outage Probability and Average File Delivery Rate in CE-SC System 59, 2.6.2 FD Transmission Between Two Nodes 64, 2.6.4 Theoretical Example Analysis of Antenna Cancellation 67, 2.6.5 Infrastructure for FD Transmission 68, 2.6.6 Full-Duplex MAC (FD-MAC) Protocol 71, 2.7 Review of Reference Signals, Antenna Ports, and Channels 74, 2.7.2 DL Reference Signals and Antenna Ports 75, 2.7.3.1 UL Reference Signal Sequence Generation 76, 2.7.3.2 Demodulation Reference Signal for PUSCH 77, 2.7.3.3 Demodulation Reference Signal for PUCCH 78, 2.7.3.5 Random-Access Channel Preambles 78, 2.8.1 Full-Dimension MIMO (FD-MIMO) Analysis 81, 2.8.3 3GPP Development of 3D Model for FD-MIMO System 82, 2.8.3.1 Antenna Array Elements Radiation Patterns 82, 2.8.5 CSI Feedback for FD-MIMO Systems 86, 2.A Notes on Machine Learning Algorithms 89, 2.B Outage Probability in CE-SC Networks 91, 2.C Signal Power at the Receive Antenna after Antenna Cancellation of Self-Interference 94, 3 5G Enabling Technologies: Network Virtualization and Wireless Energy Harvesting 99, 3.2 Network Sharing and Virtualization of Wireless Resources 100, 3.2.2 Functional Description of Network Sharing Nodes 102, 3.2.2.1 User Equipment (UE) Functions 102, 3.2.2.2 Radio Network Controller (RNC) Functions 103, 3.2.2.3 Evolved Node B (eNB) Functions 103, 3.2.2.4 Base Station Controller (BSC) Functions 103, 3.2.2.5 Mobile Switching Centre (MSC) Functions 103, 3.2.2.6 Mobility Management Entity (MME) Functions 104, 3.2.3 Single BS Shared by a Set of Operators 104, 3.3.1 Principle of Cellular Network Evolved Resource Sharing 109, 3.3.2 Single-Level Resource Allocation Among Operators 109, 3.3.3 Opportunistic Sharing-Based Resource Allocation 112, 3.4 Network Functions Virtualization (NFV) 113, 3.4.2 Principles of the Network Functions Virtualization Infrastructure (NFVI) 116, 3.6 Virtual Evolved Packet Core (vEPC) 119, 3.9 Hierarchical Combinatorial Auction Models 122, 3.10.1 Fundamentals of Wireless Energy Harvesting 126, 3.10.2 Wireless Powered Communications 129, 3.10.3 Full-Duplex Wireless-Powered Communication Network 131, 3.10.4 Wireless Power Transfer in Cellular Networks 133, 3.10.4.1 The Outage Constraint at BSs 134, 3.10.4.2 The Power Outage Constraint at PBs 135, 3.10.4.3 Hybrid Network Mobiles with Large Energy Storage 135, 3.10.4.4 Hybrid Network Mobiles with Small Energy Storage 135, 3.10.5.1 Energy Harvested from a FD BS (configuration 1) 136, 3.10.5.2 Energy Harvested from PBs (configuration 2) 137, 3.11 Integrated Energy and Spectrum Harvesting for 5G Communications 138, 3.12 Energy and Spectrum Harvesting Cooperative Sensing Multiple Access Control (MAC) Protocol 140, 3.13 Millimetre Wave (mmWave) Energy Harvesting 141, 3.14 Analysis of mmWave Energy-Harvesting Technique 144, 4 5G Enabling Technologies: Narrowband Internet of Things and Smart Cities 151, 4.1 Introduction to the Internet of Things (IoT) 151, 4.2.1 Provisioning and Authentication 153, 4.2.4 Software Updates and Maintenance 154, 4.6 DL Narrowband Physical Channels and Reference Signals 156, 4.6.1 DL Physical Broadcast Channel (DPBCH) 156, 4.6.2 Repetition Code SNR Gain Analysis 158, 4.6.3 Narrowband Physical DL Shared Channel (NPDSCH) and Control Channel (NPDCCH) 159, 4.6.4 Narrowband Reference Signal (NRS) 160, 4.6.5 NB-IoT Primary Synchronization Signal (NPSS) 160, 4.6.6 NB-IoT Secondary Synchronization Signal (NSSS) 163, 4.6.7 Narrowband Positioning Reference Signal (NPRS) 165, 4.7 UL Narrowband Physical Channels and Reference Signals 169, 4.7.1 Narrowband Physical UL Shared Channel (NPUSCH) 169, 4.7.2 Narrowband Physical Random-Access Channel (NPRACH) 170, 4.7.3.1 DMRS Sequence for NPUSCH Format1 172, 4.7.3.2 DMRS Sequence for NPUSCH Format2 173, 4.8.2 Bandwidth Perspective-Effective BW 175, 4.8.2.1 Capacity Extension Consideration 175, 4.8.2.2 Coverage Extension Consideration 176, 4.A Minimum Time Required to Transmit Message M When B→∞ 185, 5 Millimetre Wave Massive MIMO Technology 189, 5.2 Capacity of Point-to-Point MIMO Systems 190, 5.3 Outage of Point-to-Point MIMO Links 193, 5.5 Multi-User-MIMO (MU-MIMO) Single-Cell Systems 195, 5.6 Multi-User MIMO Multi-Cell System Representation 197, 5.7 Sum Capacity of Broadcast Channels 198, 5.7.4 DPC Scheme Research Development for Application in the MIMO BC 205, 5.7.5 Review of the DPC Scheme for Massive MIMO Systems 206, 5.8.2 Reciprocity Model for Point-to-Point Links 208, 5.8.4 Reciprocity Analysis Extension to Multiple Users 209, 5.8.5 Reciprocity and Pilot Contamination 210, 5.10.3 Beamformer Using a Reference Signal 214, 5.11.2 Hybrid Digital and Analogue BF for mmWave Antenna Arrays 216, 5.13 mmWave Market and Choice of Technologies 226, 5.A Derivation of Eq. 800 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