High-Density and De-Densified Smart Campus Communications E-Book

Daniel Minoli

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 838

Veröffentlichungsjahr: 2021

Beschreibung

High-Density and De-Densified Smart Campus Communications Design, deliver, and implement high-density communications solutions High-density campus communications are critical in the operation of densely populated airports, stadiums, convention centers, shopping malls, classrooms, hospitals, dense smart cities, and more. They also drive Smart City and Smart Building use cases as High-Density Communications (HDC) become recognized as an essential fourth utility. However, the unique requirements and designs demanded by HDC make implementation challenging. In High-Density and De-Densified Smart Campus Communications: Technologies, Integration, Implementation and Applications, a team of experienced technology strategists delivers a one-of-a-kind treatment of the requirements, technologies, designs, solutions, and trends associated with HDC. From the functional requirements for HDC and emerging data/Wi-Fi 6/internet access/5G cellular/OTT video, and IoT automation--including pandemic-related de-densification--to the economics of broad deployment of HDC, this book includes coverage of every major issue faced by the professionals responsible for the design, installation, and maintenance of high-density communication networks. It also includes: * A thorough introduction to traditional and emerging voice/cellular design for campus applications, including the Distributed Antenna System (DAS) * Comprehensive explorations of traditional sensor networks and Internet of Things services approaches * Practical discussions of high-density Wi-Fi hotspot connectivity and related technologies, like Wi-Fi 5, Wi-Fi 6, spectrum, IoT, VoWiFi, DASs, microcells issues, and 5G versus Wi-Fi issues * In-depth examinations of de-densification, office social distancing, and Ultra-Wideband (UWB) technologies Perfect for telecommunication researchers and engineers, networking professionals, technology planners, campus administrators, and equipment vendors, High-Density Smart Campus Communications will also earn a place in the libraries of senior undergraduate and graduate students in applied communications technologies.

Leseprobe

Table of Contents

Cover

Title Page

Copyright Page

Dedication Page

Preface

About the Authors

Acknowledgments

1 Background and Functional Requirements for High‐Density Communications

1.1 BACKGROUND

1.2 REQUIREMENTS FOR HIGH‐DENSITY COMMUNICATIONS

1.3 PANDEMIC‐DRIVEN SOCIAL DISTANCING

1.4 THE CONCEPT OF A WIRELESS SuperNetwork

REFERENCES

2 Traditional WLAN Technologies

2.1 OVERVIEW

2.2 WLAN STANDARDS

2.3 WLAN BASIC CONCEPTS

2.4 HARDWARE ELEMENTS

2.5 KEY IEEE 802.11AC MECHANISMS

2.6 BRIEF PREVIEW OF IEEE 802.11AX

REFERENCES

3 Traditional DAS Technologies

3.1 OVERVIEW

3.2 FREQUENCY BANDS OF CELLULAR OPERATION

3.3 DISTRIBUTED ANTENNA SYSTEMS (DASs)

REFERENCES

4 Traditional Sensor Networks/IoT Services

4.1 OVERVIEW AND ENVIRONMENT

4.2 ARCHITECTURAL CONCEPTS

4.3 WIRELESS TECHNOLOGIES FOR THE IoT

4.4 EXAMPLES OF SEVEN‐LAYER IoT PROTOCOL STACKS

4.5 GATEWAY‐BASED IoT OPERATION

4.6 EDGE COMPUTING IN THE IoT ECOSYSTEM

4.7 SESSION ESTABLISHMENT EXAMPLE

4.8 IoT SECURITY

REFERENCES

5 Evolved Campus Connectivity

5.1 ADVANCED SOLUTIONS

5.2 VOICE OVER Wi‐Fi (VoWi‐Fi)

5.3 5G TECHNOLOGIES

5.4 IoT

5.5 5G DAS SOLUTIONS

5.6 INTEGRATED SOLUTIONS

REFERENCES

6 De‐densification of Spaces and Work Environments

6.1 OVERVIEW

6.2 BASIC APPROACHES

6.3 RTLS METHODOLOGIES AND TECHNOLOGIES

6.4 STANDARDS

6.5 APPLICATIONS

REFERENCES

7 UWB‐Based De‐densification of Spaces and Work Environments

7.1 REVIEW OF UWB TECHNOLOGY

7.2 CARRIAGE OF INFORMATION IN UWB

7.3 UWB STANDARDS

7.4 IoT APPLICATIONS FOR UWB

7.5 UWB APPLICATIONS FOR SMART CITIES AND FOR REAL‐TIME LOCATING SYSTEMS

7.6 OSD/ODCMA APPLICATIONS

REFERENCES

8 RTLSs and Distance Tracking Using Wi‐Fi, Bluetooth, and Cellular Technologies

8.1 OVERVIEW

8.2 RF FINGERPRINTING METHODS

8.3 Wi‐Fi RTLS APPROACHES

8.4 BLE

8.5 CELLULAR APPROACHES

8.6 SUMMARY

REFERENCES

9 Case Study of an Implementation and Rollout of a High‐Density High‐Impact Network

9.1 THURGOOD MARSHALL BWI AIRPORT DESIGN REQUIREMENTS

9.2 OVERVIEW OF THE FINAL DESIGN

10 The Age of Wi‐Fi and Rise of the Wireless SuperNetwork (WiSNET)

10.1 WHAT PRECEDED THE WiSNET

10.2 WHAT COMES NEXT

10.3 THE SUPER‐INTEGRATION CONCEPT OF A WIRELESS SUPERNETWORK (WiSNET)

10.4 THE MULTIDIMENSIONALITY OF A SUPERNETWORK (WiSNET)

10.5 THE GENESIS OF THE WiSNET CONCEPT DEFINED IN THIS TEXT

10.6 THE DEFINITION AND CHARACTERIZATION OF A WiSNET

10.7 ECONOMIC ADVANTAGES OF A WiSNET SYSTEM

10.8 5G SLICE CAPABILITIES

10.9 CONCLUSION

REFERENCES

Index

End User License Agreement

List of Tables

Chapter 1

TABLE 1.1 Key Performance Indicators HDC Key Performance Indicators (KPIs)

TABLE 1.2 HDC KPIs for Airports

TABLE 1.3 Top US Airports – Actual and Heuristic Data Shown

TABLE 1.4 Largest US Football Stadiums

TABLE 1.5 Top Convention Centers in the United States

TABLE 1.6 Top Amusement Parks in the United States

TABLE 1.7 Enrolments at Largest US Districts

TABLE 1.8 Example of School Demographics (NYC)

TABLE 1.9 Top Subway and Rapid Transit Systems in the United States

TABLE 1.10 HDC KPIs for Airports

Chapter 2

TABLE 2.1 Comparison of key features of WLANs/WPANs [3]

TABLE 2.2 IEEE 802.11 Active Projects at Press Time

TABLE 2.3 Inter‐frame Space Types

TABLE 2.4 Basic Error Coding Schemes

TABLE 2.5 5 GHz Wi‐Fi Frequencies

TABLE 2.6 802.11 Cheat Sheet

TABLE 2.7 Modulation and Coding Schemes for Single Spatial Stream

Chapter 3

TABLE 3.1 Bandwidths for LTE Systems in North America

TABLE 3.2 Satellite Bands, Generalized View per IEEE Standard 521‐1984

TABLE 3.3 Performance Measures, eMBB/5G

TABLE 3.4 Frequency Range 1 (FR1)

TABLE 3.5 Frequency Range 2

TABLE 3.6 CPRI Rates

Chapter 4

TABLE 4.1 IoT Deployment Synthesis

TABLE 4.2 IoT Systems and Methods to Support the Connected Ecosystem

TABLE 4.3 Partial Listing of Key IoT RAs

TABLE 4.4 Wireless Communications Technologies that are Typically Used in IoT Sys...

TABLE 4.5 Comparison of Key Fog/Edge and Core Wireless Technologies Applicable to...

TABLE 4.6 Features of Some Key Protocol Stacks

TABLE 4.7 Comparison of Key Features

TABLE 4.8 CIA Security Goals

TABLE 4.9 User Plane Confidentiality Protection Mechanisms for LTE

TABLE 4.10 User Plane Integrity Protection Mechanisms for LTE

TABLE 4.11 OSiRM‐assisted Transition from “As Is” to a “To Be” Environment...

Chapter 5

TABLE 5.1 Higher Efficiency and Capacity Features Under 802.11ax/Wi‐Fi 6

TABLE 5.2 802.11ax Changes Compared with 802.11ac

TABLE 5.3 Total Number of RUs by Channel Bandwidth

TABLE 5.4 Key EPC Architecture Elements

Chapter 6

TABLE 6.1 Occupancy Aspects that are Important to OSD/ODCMA Policies

TABLE 6.2 Taxonomy of Occupancy Detection Systems, with Focus on RTLSs

TABLE 6.3 RTLS Comparison

TABLE 6.4 Possible RTLS Applications in Smart Cities

TABLE A.1 Basic Terms and Concepts Relative to Positioning Technologies

TABLE A.2 Basic RFID Terms and Concepts Relative to Positioning Technologies

Chapter 8

TABLE 8.1 Basic best practices of overlay Wi‐Fi‐based RTLSs (summarized from [21]...

TABLE 8.2 Bluetooth Protocol Versions

TABLE 8.3 Additional comparison of technologies [57]

TABLE 8.4 Overall comparison of sensor technologies for RTLSs

Chapter 9

TABLE 9.1 MyBWI‐FI technology plan

TABLE 9.2 DAS Requirements for the BWI Airport

Chapter 10

TABLE 10.1 Plethora of Players at BWI – In a WiSNET, All of These Are Managed by ...

TABLE 10.2 Technical Characterization of a WiSNET

List of Illustrations

Chapter 1

FIGURE 1.1 Requirements bouquet.

FIGURE 1.2 A gate area at Fort Lauderdale‐Hollywood International Airport is...

FIGURE 1.3 Inventory of US buildings.

FIGURE 1.4 Heuristic model for office space allocation.

FIGURE 1.5 Infection and casualty data from the COVID‐19 Dashboard by the Ce...

FIGURE 1.6 Pandemic impact on airline travel in the Fall of 2020.

FIGURE 1.7 A pictorial view of an RTLS environment [50].

FIGURE 1.8 Generic RTLS system concept.

FIGURE 1.9 De‐densified (heuristic model).

FIGURE 1.10 INET‐v6: a Wireless SuperNetwork (WiSNET).

Chapter 2

FIGURE 2.1 Example of a WLAN (MIMO case).

FIGURE 2.2 Block diagram of a WLAN device (example).

FIGURE 2.3 A general MIMO system (after [12]).

FIGURE 2.4 Example of PHY transmit procedure [2].

FIGURE 2.5 Inter‐frame Space relationships [2].

FIGURE 2.6 Carrier Sense Multiple Access/Collision Avoidance‐based frame tra...

FIGURE 2.7 Distributed MIMO communication with beamforming [20].

FIGURE 2.8 SU‐MIMO versus MU‐MIMO.

FIGURE 2.9 5GHz spectrum usability for IEEE 802.11ac LANs.

FIGURE 2.10 Space–time block coding [2].

Chapter 3

FIGURE 3.1 Basic cellular and DAS setup.

FIGURE 3.2 Examples of base station architectures. Top: traditional. Bottom:...

FIGURE 3.3 Hoteling concept for RRUs.

FIGURE 3.4 Frequency reuse [11].

FIGURE 3.5 Block diagram depicting architecture of a typical LTE/EPC environ...

FIGURE 3.6 CBRS spectrum.

FIGURE 3.7 Example of a multi‐antenna transmission embodiment having multipl...

FIGURE 3.8 General DAS concept [37].

FIGURE 3.9 A DAS system using digital remote antenna units [38].

FIGURE 3.10 In‐building installation of a DAS [39].

FIGURE 3.11 BS‐to‐HEU‐RAU connectivity (partially based on [40]).

FIGURE 3.12 Illustrative example of carrier‐specific DAS [5].

FIGURE 3.13 Illustrative example of carrier‐specific DAS used to better supp...

FIGURE 3.14 Possible DAS arrangement for outdoor coverage in 5G environments...

FIGURE 3.15 More detailed view of the DAS: two perspectives [2, 39].

FIGURE 3.16 RRH sections.

FIGURE 3.17 Fronthaul and backhaul.

Chapter 4

FIGURE 4.1 A logical view of an IoT ecosystem.

FIGURE 4.2 Applications scope of IoT/CPS (examples).

FIGURE 4.3 Example of IoT ecosystem [50].

FIGURE 4.4 OSiRM: open systems IoT reference model (transaction stack).

FIGURE 4.5 Typical wireless technologies usable in the IoT context.

FIGURE 4.6 The pre‐5G and the 5G IoT connectivity ecosystem.

FIGURE 4.7 Example of communication systems in IoT with local aggregation [6...

FIGURE 4.8 WAN/LPWAN IoT environment [55].

FIGURE 4.9 Dual‐mode systems.

FIGURE 4.10 Support of LTE‐M and NB‐IoT under 5G.

FIGURE 4.11 Key IoT protocols in a full stack.

FIGURE 4.12 The UPnP process for device control.

FIGURE 4.13 Example of gateway performing a “bridging” function between non‐...

FIGURE 4.14 Typical networking arrangement for smart home services where an ...

FIGURE 4.15 Networking arrangement for smart home services where an IoT edge...

FIGURE 4.16 IoT Session establishment example [121].

Chapter 5

FIGURE 5.1 TCO illustrative example.

FIGURE 5.2 Basic channel access/management in recent 802.11 specifications [...

FIGURE 5.3 Example scenario of an airport with high user density targeted fo...

FIGURE 5.4 HE PPDU (data) frame

FIGURE 5.5 Trigger frame

FIGURE 5.6 Access point supporting beamforming [19].

FIGURE 5.7 Concept comparison of a single user using the channel and OFDMA m...

FIGURE 5.8 Illustrative 20 MHz spectrum allocation based on resource unit si...

FIGURE 5.9 Example of resource unit allocation scheme in 802.11ax

FIGURE 5.10 Theoretical example of 8 × 8 MU‐MIMO AP using differences in the...

FIGURE 5.11 Trigger process implemented by the AP [2].

FIGURE 5.12 Beamforming process [2].

FIGURE 5.13 MU service negotiation and measurement exchange process

FIGURE 5.14 A formal view of VoWi‐Fi (partially based on ETSI 123 402).

FIGURE 5.15 Simplified example Wi‐Fi call through a Wi‐Fi AP and block diagr...

FIGURE 5.16 5G services under development.

FIGURE 5.17 Some technical features of 5G services.

FIGURE 5.18 5G transition options and IoT support.

FIGURE 5.19 Detailed 5G transition options and IoT support.

FIGURE 5.20 Network architecture and interface of a 5G cellular system [32]....

FIGURE 5.21 Path loss as a function of distance and frequency.

FIGURE 5.22 Attenuation as a function of precipitation and frequency.

FIGURE 5.23 Attenuation as a function of fog density and frequency.

FIGURE 5.24 Attenuation as a function of atmospheric gasses and frequency (n...

FIGURE 5.25 OFDM resources and LTE legacy support [33].

FIGURE 5.26 Scenarios of providing 5G services sorted according to usage ban...

FIGURE 5.27 Path loss simulations for 5G by various entities.

FIGURE 5.28 PLE.

FIGURE 5.29 A state‐of‐the‐art integrated system.

FIGURE 5.30 Conceptual view of an advanced high‐density high‐impact network....

Chapter 6

FIGURE 6.1 Social distancing other infection containment and control measure...

FIGURE 6.2 Monitoring of people presence and/or density – general concept.

FIGURE 6.3 Seat/desk‐specific tags.

FIGURE 6.4 Heat maps generated over a time window.

FIGURE 6.5 Pictorial view of the Tag‐Based Approach.

FIGURE 6.6 RTLS approaches (from [70]). Top: Calculation of location with re...

FIGURE 6.7 Illustrative example of an RFID RTLS.

FIGURE 6.8 RFID environment (top) and backscatter (bottom) [68].

FIGURE 6.9 Various systems for generating location estimates from location i...

FIGURE 6.10 PPE article tracking compliance systems [74].

Chapter 7

FIGURE 7.1 FCC mask for UWB.

FIGURE 7.2 Approximate positioning of UWB technology.

FIGURE 7.3 Pulse train (Gaussian second derivative pulse).

FIGURE 7.4 Various pulse shapes.

FIGURE 7.5 Resolvable and unresolvable MPCs.

FIGURE 7.6 Examples of modulation.

FIGURE 7.7 Transmission systems. Part a: Traditional system. Part b: UWB sys...

FIGURE 7.8 IEEE Std 802.15.4 HRP UWB PHY signal flow (top: TX; bottom: RX)....

FIGURE 7.9 Protocol layers covered by various UWB standards.

FIGURE 7.10 IEEE Std 802.15.4 HRP UWB PPDU.

FIGURE 7.11 IEEE Std 802.15.4 HRP UWB PHY symbol structure.

FIGURE 7.12 UWB‐based RTLS.

FIGURE 7.13 UWB transceiver that is powered by an RF input through an antenn...

FIGURE 7.14 UWB positioning techniques.

FIGURE 7.15 Comparison of methods.

FIGURE 7.16 Example of a tag transmission pulsing sequence for a UWB‐based R...

FIGURE 7.17 Example timing diagram for a receiver [50].

FIGURE 7.18 UWB OSD model

FIGURE 7.19 UWB apparatus and analytics

FIGURE 7.20 Example of UWB RTLS System, Zebra Technology

FIGURE 7.21 Airtls product features

FIGURE 7.22 Pozxy system

Chapter 8

FIGURE 8.1 Symbology for various technologies.

FIGURE 8.2 WLAN/cellular RTLS environment

FIGURE 8.3 Basic WLAN/Wi‐Fi RTLS architecture.

FIGURE 8.4 Example of Wi‐Fi‐based RTLS [16].

FIGURE 8.5 Mode of operation of a Wi‐Fi‐based RTLS [17].

FIGURE 8.6 Forecast of the deployment of Bluetooth technology.

FIGURE 8.7 Simple BLE RTLS setup.

FIGURE 8.8 More complex BLE RTLS setup (loosely based on [43]).

FIGURE 8.9 Another conceptual view of a BLE RTLS [3].

FIGURE 8.10 Typical beacon elements.

FIGURE 8.11 Examples of BLE beacons.

FIGURE 8.12 Example of RTLS tags for OSD/ODCMA

FIGURE 8.13 Mist (Juniper Networks) vBLE concept (courtesy).

FIGURE 8.14 OTDOA approach for LTE [54].

FIGURE 8.15 Example of DAS‐based system [54].

Chapter 9

FIGURE 9.1 Aerial view showing the terminal and concourses of the airport.

FIGURE 9.2 BWI services obtainable over the new network.

FIGURE 9.3 New network infrastructure.

FIGURE 9.4 Exemplary plot for LTE.

FIGURE 9.5 Access/aggregation design using Cluster Network Controller over p...

FIGURE 9.6 Machine learning analyzes data and provides insight, such as root...

FIGURE 9.7 Sample reports.

Chapter 10

FIGURE 10.1 (Also shown as Figure 1.9): INET‐v6: A Wireless SuperNetwork (Wi...

FIGURE 10.2 Present mode of operation (left hand side) and evolving future m...

FIGURE 10.3 The three key dimensions of a WiSNET.

FIGURE 10.4 MyBWI‐FI SuperNetwork at the Baltimore, MD airport.

FIGURE 10.5 The digital transformation of a high‐density network – The BWI W...

FIGURE 10.6 Simple, unified hierarchical WiSNET architecture.

FIGURE 10.7 Slice environment (modified from [12] and [13]). NF: network fun...

Guide

Cover Page

Title Page

Copyright Page

Dedication Page

Preface

About the Authors

Acknowledgments

Table of Contents

Begin Reading

Index

Wiley End User License Agreement

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HIGH‐DENSITY AND DE‐DENSIFIED SMART CAMPUS COMMUNICATIONS

Technologies, Integration, Implementation, and Applications

Daniel Minoli

DVI Communications

New York, NY, USA

Red Bank, NJ, USA

Jo‐Anne Dressendofer

Slice Wireless Solutions

New York, NY, USA

This edition first published 2022© 2022 John Wiley & Sons, Inc.

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The right of Daniel Minoli and Jo‐Anne Dressendofer to be identified as the authors of this work has been asserted in accordance with law.

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Library of Congress Cataloging‐in‐Publication Data:

Names: Minoli, Daniel, 1952– author. | Dressendofer, Jo‐Anne, author.Title: High‐density and de‐densified smart campus communications : technologies, integration, implementation and applications / Daniel Minoli, Jo‐Anne Dressendofer.Description: Hoboken, NJ : Wiley, 2022. | Includes bibliographical references and index.Identifiers: LCCN 2021050372 (print) | LCCN 2021050373 (ebook) | ISBN 9781119716051 (hardback) | ISBN 9781119716068 (adobe pdf) | ISBN 9781119716082 (epub)Subjects: LCSH: Wireless communication systems. | Smart materials.Classification: LCC TK5103.2 .M5665 2021 (print) | LCC TK5103.2 (ebook) | DDC 621.384–dc23/eng/20211110LC record available at https://lccn.loc.gov/2021050372LC ebook record available at https://lccn.loc.gov/2021050373

Cover design by WileyCover image: © enjoynz/Getty Images

In loving memory of my wife Anna (Dan)

Era una santa e completò la sua missione con passione, pur giovane

.

“E se dal caro oggetto, Lungi convien che sia, convien che sia, Sospirerò penando, Ogni momento”

(from a stanza in Vivaldi's “Vedrò con mio diletto”)

In loving memory of my mother Helene (Jo‐Anne)

Who was there for every tear along my not‐so‐easy career and pushed me to dream even bigger

PREFACE

High‐density campus communications have traditionally been important in many environments, including airports, stadiums, convention centers, shopping malls, classrooms, hospitals, cruise ships, train and subway stations, evangelical megachurches, large multiple dwelling units, boardwalks, (special events in) parks, dense smart cities, and other venues. These communications span several domains: people‐to‐people, people‐to‐websites, people‐to‐applications, sensors‐to‐cloud analytics, and machines‐to‐machines/device‐to‐device. While the later Internet of Things (IoT) applications are generally (but not always) low speed, the former applications are typically high speed. In many settings, people access videos (a la Over The Top [OTT] mode) or websites and applications that often include short videos or other high data‐rate content. Deploying optimally performing high‐density campus communication systems is desired and required in many cases, but it can, at the same time, be a complex task to undertake successfully.

High‐density campus communications play a role in the evolution of Smart Campuses but also drive the Smart City and Smart Building use cases. Connectivity is now considered a fourth utility (in addition to gas, water, and electricity). In fact, massive‐type communication is a recognized requirement of 5G, even if just in the machine‐type communication environment. In the campus applications just cited, people‐to‐people, people‐to‐websites, and people‐to‐applications connectivity is increasingly important, given that nearly everyone now carries a smartphone and many apps entail high‐throughput transmissions.

There are unique requirements and unique designs required for high‐density communications, particularly because of the relative scarcity of available spectrum. In addition, there has been and continues to be a set of transitions, even transformations, of the underlying technologies. The world has moved to IP for all data, voice, and video communications. Additionally, there is a trend toward the use of Wi‐Fi‐based hotspot communication in all practical situations, due to near ubiquity of service, lower end‐user costs, higher bandwidth, technical simplicity, lower infrastructure costs, decentralized administration, regulation relief, and non‐bureaucratic delivery of service (without the reliance of large institutional providers). While 5G promises to deliver a set of new capabilities, neither 3G nor 4G displaced Wi‐Fi as a common access technology in the office, in the campus, on the street, and in travel. The technologies per se used for high‐density communications are not new (perhaps with the exception of 5G), but the requirements, as well as the design and system synthesis, are relatively unique.

As the second decade of the twenty‐first century rolled along, however, a new requirement presented itself due to the worldwide pandemic: physical/desk distancing in support of Office Social Distancing (OSD) and Office Dynamic Cluster Monitoring and Analysis (ODCMA). Wireless technologies have been harvested to address and manage these pressing issues. Real‐Time Locating Systems (RTLS) have been employed for a number of years to automatically identify and then track the location of objects or people in real‐time, within a building, or in other constrained locations are seeing renewed interest and applications. Even if effective vaccines are found and distributed globally, the common opinion is that many (but not all) societal and workplace changes driven by the pandemic may become permanent.

This book assesses the requirements, technologies, designs, solutions, and trends associated with High‐Density Communications (HDC). We believe this to be the first book that specifically synthesizes the topic of applied high‐density communications. Chapter 1 looks at the functional requirements for high‐density communications. Chapter 2 discusses the traditional data/Wi‐Fi Internet access, including OTT video. Chapter 3 addresses the traditional voice/cellular design for campus applications, especially the Distributed Antenna System (DAS). Chapter 4 peruses the traditional sensor networks/IoT services approaches. Chapter 5 is the core of this text and examines evolved Wi‐Fi hotspot connectivity and related technologies (Wi‐Fi 5, Wi‐Fi 6, spectrum, IoT, VoWiFi, DASs, microcells issues, 5G versus Wi‐Fi issues), as well as intelligent integration of the discrete set of campus/venue networks into a cohesive platform usable in airports, stadiums, convention centers, classrooms, hospitals, and the like.

Chapter 6 starts the discussion on de‐densification, using the same kind of technologies discussed in part one of the book; it considers the topic of office social distancing and discusses one of the available technologies. Chapter 7 covers the use of Ultra‐Wideband (UWB) technologies. Chapter 8 addresses the office social distancing challenge using Wi‐Fi, Bluetooth, and cellular/smartphone methodologies. Chapter 9 provides a use case for HDC systems, and Chapter 10 offers a pragmatic view for some of the economics of broad deployment of HDC.

The book is targeted to networking professionals, technology planners, campus administrators, service providers, equipment vendors, and educators. It is not a research monograph, but rather it aims at integrating the real‐world deployment of technologies, strategies, and implementation issues related to delivering an actual working HDC environment in any of the key venues listed above. It is important to note that the composition of this book started in February 2020. While social distancing in the office and public venues was a crucial short‐term goal at press time, the business‐ and public‐venue density requirements will likely resurge over time, likely with some yet to be foreseen modifications.

Many books delve extensively on general technologies of all types; however, they fall short in terms of the economics of such technologies, deployment challenges, associated security issues, and most lack tangible case studies. This book addresses these key aspects, based on actual deployment by the team associated with this writing, at a top US airport.

Some portions of this text make use of patent material filed with the United States Patent Office. All inventors cited are implicitly acknowledged for their contribution to this synthesis.

Daniel Minoli

DVI Communications

Jo‐Anne Dressendofer

Slice Wireless Solutions

30 December 2020

ABOUT THE AUTHORS

DANIEL MINOLI

Mr. Minoli is the principal consultant at DVI Communications. He has published 60 technical telecom and IT books, many are the first in their field (e.g., the first‐ever book on VoIP, the first‐ever on outsourcing of telecom services, the first‐ever book on metro Ethernet, the first‐ever book on green networks, the first‐ever book on IPv6 security, the first book on public hotspots, and the first book on IPv6 support of IoT, among others); he has also published 340 other papers (the majority of which are peer‐reviewed). Many books focus on raw technologies and fail to address Return on Investment (ROI), deployment, security considerations, and to provide case studies; Mr. Minoli's books aim to address these key issues when documenting the applicability of the underlying technologies.

Mr. Minoli started to work on wireless LANs in the late 1970s as part of ARPANet‐sponsored R&D and continued wireless work in the form of Geo/Meo satellite transmission, microwave, free space optics, mmWaves/“wireless fiber,” cellular, Wi‐Fi WLANs, sensor networks, wireless IoT, crowdsensing, 900 MHz SCADA, BMSs, UltraWideband, and 5G. He has written two books on LANs and several long book chapters on WLANs in other books; and, as noted, he has written a book on public hotspots and a book on metroEthernet/VPLS. At press time, over 225 published US patents, as well as 38 US patent applications, cite his work. Additionally, 5917 academic researchers cite his work in their own publications, according to Google Scholar, including 1887 citations of his books on Wireless Sensor Networks, 569 of his books/papers on IoT, 344 of his books on enterprise architectures, 262 of his books on video, and 259 of his books on VoIP. Mr. Minoli is a reviewer for several publishers, including Elsevier, Springer, IEEE, and Wiley. He has taught (adjunct) over 75 college graduate/undergraduate courses at New York University, Stevens Institute of Technology, and Rutgers University. He has been affiliated with Nokia, Ericsson, AT&T, SES, Prudential Securities, Capital One Financial, and AIG, and has been an expert witness/testifying expert in about 20 patent lawsuits. He has undertaken Intellectual Property (IP) work related to patent invalidity, infringement/non‐infringement analysis, breach‐of‐contract, dispute of equipment functionality, and IP portfolio valuation in the area of packet video/IPTV, packet voice/VoIP, networking, imaging (scanned checks), IoT, and wireless. He has provided Court testimony, sustained numerous depositions, and produced numerous Expert Reports, Rebuttal Reports, and Post Grant Review Declarations.

JO‐ANNE DRESSENDOFER

Jo‐Anne (Josie) Dressendofer is the founder of SliceWiFi. The firm was launched in 2016 to address the rapidly expanding need for fast, reliable Wi‐Fi service in permanent and temporary locations. What started as a goal to become the first “Managed Wi‐Fi Brand” ended up becoming the first company to compete with the goliath cellular companies, with Wi‐Fi and an all‐inclusive technology, turning SliceWiFi into a telecommunications company overnight. SliceWiFi initially achieved market recognition in New York City, as one of the leading Wi‐Fi providers in the NY metro area, after successfully supporting difficult, densely populated networking environments such as the Javits Center and downtown Brooklyn rebuilding after Hurricane Sandy; NY Fashion Week's many simultaneous event locations; many hackathons with over a thousand users; the Staten Island Ferry during peak travel over the Hudson River; and the parks at Hudson Yards where no fiber was to be had. In 2017, SliceWiFi won CIO magazine's category award for “Top Wireless Solution Providers.”

Ms. Dressendofer has led a 25‐year career in the tech industry, competing aggressively and winning repeatedly against larger, better‐financed multi‐billion‐dollar competitors. Her firms have a record of being more creative with leading‐edge technology deployment and networking engineering than all the legacy providers in play. The recent win at BWI Thurgood Marshall Airport (BWI) against major players in the telecommunications industry was transcendent and proof that the SuperNetwork concept (Chapters 9 and 10) is not only a trendsetter but a victory for all women in technology.

ACKNOWLEDGMENTS

In addition to the inventors cited in this work, Mr. Minoli wishes to warmly thank Mr. Benedict Occhiogrosso, President, DVI Communications, for the continued support and input in all the bleeding‐edge technologies discussed in this text. DVI Communications, Inc. is a leading and highly respected Information Technology, ICT consultancy, and systems engineering firm with core competencies in IT, ICT, IoT, M2M, wireless, telecom, security, and audiovisual systems. Throughout its 40+ year history, the firm has supported many organizations deploying traditional and emerging technologies, serving both large enterprises and smaller organizations in numerous vertical markets with complex, state‐of‐the‐art systems often working alongside legacy systems, supporting several generations of technology simultaneously.

Ms. Dressendofer wishes to credit and thank the staff of Slice Wireless Solutions, Inc. (SliceWiFi) for the support of this initiative, as described in Chapter 9 and further synthesized in Chapter 10, in the context of designing and deploying a reimagined Thurgood Marshall Airport (BWI) SuperNetwork and the development of WiSNET. The complete redesign and the initial redeployment of the entire BWI Airport terminal‐side and some portions of the operations wireless communication infrastructure, amid the COVID‐19 pandemic and the span of 12 months, all while maintaining reliable, uninterrupted airport service, was an enormously complex task. Much has been learned at the practical level and is documented in the last two chapters of this book. John Hutzler, COO, and Ed Wright, CTO, have been instrumental in the successful design and completion of this SuperNetwork redeployment mission, even more so as evinced by the relatively small size and the recent debut of SliceWiFi, and this win against the competition backed by billions faced during the RFP process. Without their labor, there would be no SuperNetwork and no chapters to document herewith. Thanks to Cheryl Beck, CMO and Jeffrey Forester, our legal council.

Lastly, to those who were there before SliceWiFi and who without their contribution would never had led down the path of this incredible development. I especially owe that to Morris Williams, Jiamini Erskine, and Ricky Smith of BWI for having the courage to choose a better way not the old way and stay by our side during the tough times, our Nashville investors and investment team, Eddy Wong, my former partner and mentor, Irwin Cohen whose inspiration and endless contacts led me to the incredible support of Jason Zuckerbrod and Jody Westby, and my six nieces who inspired me every day to do more to open doors and make the world a better place for them. Thank you will never be enough for your help in creating a dream this big, against such odds and see it actualized. Dan Minoli you stand alone in genius and my admiration.

1Background and Functional Requirements for High‐Density Communications

This introductory chapter covers two topics: (i) a basic introduction to the underlying technologies and principles that apply to High‐Density Communications (HDC), but not high‐density specifics, which are covered in the chapters that follow, and (ii) a discussion of the main requirements for HDC in the context of key use cases. Use cases include airports, stadiums, convention centers, classrooms, amusement parks, train and subway stations, large multiple dwelling units, open air special events, and other venues.1

As the second decade of the twenty‐first century rolled along, however, a new requirement presented itself due to the worldwide pandemic: physical/desk distancing in support of Office Social2 Distancing (OSD) and Office Dynamic Cluster Monitoring and Analysis (ODCMA). A “de‐densification” effort was established at the time. The de‐densification effort in the workplace impacts a large number of factors, including network connectivity services and architectures. Propitiously, wireless technologies have been harvested to address and manage these pressing distancing issues. Even if effective vaccines are found and distributed globally, many agree that some of the societal and workplace changes driven by the pandemic may become permanent. One change likely to remain is the increased reliance on Work From Home (WFH) and along with it, are the implications of greater utilization of a global workforce in what might be called Outsourcing 2.0 (with the 1.0 version having taken place in the 1990s and 2000s). However, “the sun will rise again,” and in a few years, people‐based HDC may yet again become the norm; in the meantime, a large population of Internet of Things (IoT) devices may indeed require HDC support, and during the pandemic, the e‐commerce warehouse use case continues to need HDC support. Thus, while “social distancing” was a short‐term goal at press time, the business‐ and public‐venue high‐density requirements are expected to resurge and/or continue over time. Further discussion of these issues is provided in the latter part of the chapter.

1.1 BACKGROUND

The principal ways people currently communicate (especially when away from home) are via 4G/Long‐Term Evolution (LTE) cellular access, for both voice and data, and/or via a public, institutional, or corporate Wi‐Fi™ hotspot. In less populated areas and while in motion, cellular access is typically the norm, rather than Wi‐Fi access. In large business and commercial buildings (e.g. skyscrapers, hospitals, hotels), internal systems known as Distributed Antenna Systems (DASs) may be used to provide better signal quality to cellular users; these systems interoperate with the public cellular network in a number of ways. When stationary, both choices may be available.

Cellular services are offered by carriers using specific carrier‐allocated Radio Frequency (RF) spectrum. Relatively high monthly fees are incurred; additionally, there may be both physical and administrative limits to the amount of bandwidth and interval‐accumulated throughput. Wi‐Fi makes use of bands that are freely allocated; services could be free or could be nearly free based on some account subscription arrangement.

There are plusses and minuses with both technologies: a signal associated with a cellular service such as 4G/LTE reaches longer distances and is often the best choice in sparsely populated areas (assuming the service is available); high‐speed mobility is supported and roaming between towers (cellular access points) is seamless; the service is typically provided by well‐established carriers that have experience with availability and Quality of Service (QoS) metrics; large portions of the United States are covered, and; the session bandwidth is often guaranteed for the session's duration once the session is established. Conversely, the service costs for 4G/LTE are relatively high and there are limits to the user throughput; there is relatively limited practical competition among carriers; large base‐station antennas are needed to cover large geographic areas; the technology is complex; indoor reception of voice and data can be problematic, creating the need for more indoor antennas; and 5G will require smaller (therefore, a larger number of) cells. Wi‐Fi is often perceived to be free; the technology is simpler; the hardware and infrastructure are cheaper; it is a consistent technology between the office and the home; there is more competition in the sense that various establishments (e.g. stores, coffee shops, malls, libraries, institutions) make Wi‐Fi service available. However, the technology is subject to interference; the distance is limited; roaming does not work across different providers and may not even work for a given provider, even within limited geography; congestion can occur, and; QoS is not guaranteed. Nonetheless, both technologies fill a role, and both technologies are clearly needed.

There are several Wireless Local Area (WLAN) standards that have evolved over time, including Institute of Electrical and Electronics Engineers (IEEE) standards 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, 802.11ax. The new standards have been developed to accommodate the evolving requirements for higher speeds. Some protocols and wireless routers provide backward compatibility with older Wi‐Fi systems. The Wi‐Fi Alliance (an industry group) has announced a banding “generation” designation, as follows:

Wi‐Fi 4 is 802.11n, released in 2009

Wi‐Fi 5 is 802.11ac, released in 2014

Wi‐Fi 6 is the new version, also known as 802.11ax (scheduled for release in 2019)

Earlier versions of Wi‐Fi have not been officially branded, but one could label the previous generations as follows:

Wi‐Fi 1: 802.11b, released in 1999

Wi‐Fi 2: 802.11a, released in 1999

Wi‐Fi 3: 802.11g, released in 2003

Radio technologies in cellular communications have grown rapidly. They have evolved since the launch of analog cellular systems in the 1980s, starting from the First Generation (1G) in the 1980s, Second Generation (2G) in the 1990s, Third Generation (3G) in the 2000s, and Fourth Generation (4G) in the 2010s (including LTE and variants of LTE). Fifth Generation (5G) access networks, which can also be referred to as New Radio (NR) access networks, are currently being deployed and are expected to address the demand for exponentially increasing data traffic and are expected to handle an extensive range of use cases and requirements. Basic use cases include, among others, Mobile Broadband (MBB) and Machine‐Type Communications (MTC), for example, involving IoT devices – Machine‐to‐Machine (M2M) communication is a specific IoT niche. The IoT refers to the network of physical objects with Internet connectivity (connected devices) and the communication between them; these connected devices and systems collect and exchange data. The IoT has been defined as “the infrastructure of the information society”; it extends Internet connectivity beyond traditional devices such as desktop and laptop computers and smartphones to a range of devices and everyday entities that use embedded technology to communicate and interact with the external environment [1]. Massive Multiple Inputs and Multiple Outputs (MIMO) designs, new multiple access methods, and novel channel coding approaches are being assessed for use in 5G and HDC environments [2–7].

The upcoming 5G access networks may utilize higher frequencies (i.e. > 6 GHz) to support increasing capacity by allocating larger operating channels and bands, although some lower frequencies can also be used. Millimeter wave (mmWave), the band of spectrum between 30 and 300 GHz, have shorter wavelengths that range from 10 to 1 mm. Currently, much of the mmWave spectrum is underutilized; thus, it can be used to facilitate the deployment of new high‐speed services. While it is known that mmWave signals experience severe path loss, penetration loss, and fading, the shorter wavelength at mmWave frequencies also allows more antennas to be packed in the same physical dimension, which allows for large‐scale spatial multiplexing and highly directional beamforming [8].

Some observers have predicted the “death of Wi‐Fi” at various points in the recent past. To quote Mark Twain (as told by his biographer Albert Bigelow Paine), “the report of my death has been grossly exaggerated.” Ignoring the ALOHAnet of the late 1960s/early 1970s, wireless LANs started to appear in the late 1980s/early 1990s (e.g. with the WaveLAN system originally designed by NCR Systems Engineering/Wireless Communication and Networking Division, available commercially in 1990 and for several years, some concepts eventually making their way into the 1997 IEEE 802.11 standard3). The generic technology has thus been around for 30 years. When (some form of) 3G/4G/LTE was starting to be deployed, some predicted that it would be the death knell of (public hotspot) Wi‐Fi, but it did not happen. In fact, many devices developed the capability of transferring connectivity and roaming seamlessly between the local Wi‐Fi (corporate, public, residential) and cellular service – some users even use their cellular‐based smartphone to create a small local hotspot to support traditional Wi‐Fi elements in their environment. Now with 5G on the horizon, some are offering the same (questionable) prediction about the future of Wi‐Fi [9]. As is the case with many pairs of technologies, one technology moves ahead, the other lagging; then at some point, the second technology makes a quantum leap forward, and the original one lags; then again, the original technology makes a new advancement and leapfrogs the other technology, and so on. One can apply this idea to cellular and Wi‐Fi in terms of speed/throughput as well as cost and end‐device capabilities. In broad terms, Wi‐Fi generally offers higher data rates and service can be cheaper; however, large‐geography coverage and large‐geography roaming are more “natural” in the cellular context. Another observation is that 5G will often require small cells, implying both a similarity with a Wi‐Fi hotspot and increased infrastructure and deployment cost. 5G is advocated from the perch of higher speeds, higher density, and reliable connectivity; however, it remains to be seen if these features can be achieved on a large scale (i.e. over a large geographic, national, or international geography) and in a cost‐effective manner. The global standard could in theory benefit dispersed IoT sensor support, in a smart city setting, for example, but until recently, the cost of the cellular interface for the sensor tended to be fairly expensive (e.g. in the $20–40 range); thus, the use of other Low Power Wide Area Network (LPWAN) technologies such as LoRa or Sigfox have taken hold. This interface cost must decrease substantially if the use of 5G cellular in IoT applications is to become ubiquitous.

1.2 REQUIREMENTS FOR HIGH‐DENSITY COMMUNICATIONS

HDC can be characterized by several (requirement) metrics. Basic metrics include, but are not limited to, user connection density, traffic volume density, experienced data rate, and peak data rate. Many venues require ultra‐high connection density and ultra‐high traffic volume density; applications that entail M2M and may typically (but not always) require very low end‐to‐end latency. For example, 5G systems aim at the following key performance indicators: (i) connection density: one million connections per square kilometer; (ii) traffic volume density: tens of Gbps per square kilometer; (iii) user experienced data rate: 0.1–1 Gbps; (iv) peak data rate: tens of Gbps, and; (iv) end‐to‐end latency: 1–10 ms. See Figure 1.1. In addition, there is a need for scalability: it is one thing to have high density in a small area (say, a classroom), and it is another matter to be able to sustain that over a large venue (for example, a stadium or airport). For this discussion, it is assumed that the mobility speed is not a factor: pedestrian rates (≤10 km/h) are assumed.

One million connections per square kilometer (also definable as 1 connection per m2) equates to one connection every 10 ft2 (1 km2 = 10 763 910 ft2); this is considerably higher than the connectivity goals in an office environment, where typically one has an allocated space of 130–150 ft2 per worker, with one or two connections per worker; this is also higher than the connectivity in a classroom (say a 40 × 40 ft locale and 32 students, or one connection every 50 ft2). Another example could be train cars with 200 users (perhaps not all simultaneously active) in 1000 ft2, or one connection every 10 ft2 if only 50% of the passengers are active at any one point in time.

FIGURE 1.1 Requirements bouquet.

TABLE 1.1Key Performance Indicators HDC Key Performance Indicators (KPIs)

Key Performance Indicators

Description

Connection density

Total number of connected devices per unit area (n/km

2

)

User experienced data rate

Minimum data rate for a user in the actual network environment (bps)

Peak data rate

Maximum achievable data rate per user (bps)

Traffic volume density

Total data rate of all users per unit area (bps/km

2

)

End‐to‐end latency

Time lag between the transmission of a data packet from the source and the successful reception at the destination (ms)

Scalability

The ability to retain the above‐defined KPIs over large venues and/or geographic areas

In addition to traditional communications, evolving requirements for high‐density environments include wearables (for example, in augmented reality applications), M2M, and vehicular traffic in Intelligent Transportation Systems (ITSs) environments. For example, densities of 1 node per m2 have been identified for augmented reality applications, as with Personal Area Network (PAN) mechanisms [10]. For ITSs, vehicle density has been one of the main metrics used for assessing road traffic conditions: a high vehicle density usually indicates that the road or street is congested [11]; the communication traffic is comprised of beacon signals and user‐generated signals. A congested road with stopped vehicular traffic might have, say, 12 cars in an area of 2500 ft2, or a density of 1 car in about 200 ft2 – each car could have multiple user sessions. Beyond user counts, the requirements span data rates, as highlighted in Table 1.1; some M2M and process control applications have stringent reliability and latency requirements. Applications such as Ultra HD video Streaming Over The Top (OTT), augmented reality, and online gaming impose challenging requirements on bandwidth and latency; however, these applications are not expected, in the short term at least, to have major deployment in mobile environments, but more so in stationary domiciled environments.

Additional key factors to take into consideration when deploying a state‐of‐the‐art HDC system include spectrum utilization, energy consumption, and infrastructure and endpoint system cost [2]. Spectrum efficiency is measured as the data throughput per unit of spectrum resource per cell or per unit area (bps/Hz/cell or bps/Hz/km2); energy efficiency is quantified in terms of the number of bits that can be transmitted per unit of energy (bits/J); infrastructure cost efficiency can be defined by the number of bits that can be transmitted per unit cost as computed from network infrastructure amortization/allocation (bits/$); endpoint system costs are clearly the endsystem costs, especially for the air interface and the protocol stack resources, to support a given maximum throughput; applicable to human devices (e.g. smartphones) and M2M systems. Improvements in these metrics of one‐to‐two orders of magnitude are being sought compared with legacy environments.

A number of use cases follow.

1.2.1 Pre‐pandemic/Long‐term Requirements for Airports

Table 1.2 identifies some target design parameters for airport applications, including voice, video, data, IoT, IoT‐based security (video surveillance), IoT‐based automation, and wayfinding. Two characteristics of airports are as follow: (i) people at the airport are in a “slave” situation typically with nothing to do but to use their electronic devices – this is unlike a stadium or a school where other events and occurrences take up some of the person's time, thus likely diminishing the connection time of the individuals; (ii) multiple automation M2M‐like tasks may be at play in the airport including baggage handling, wayfinding/mobility/movement, and security. HDC requirements continue to be active, even, or especially, in emergency cases (these requirements were instituted in early 2020 and continued to be active as of press time [12]) – one example of a challenging airport environment even as the pandemic was already raging, is illustrated in Figure 1.2. Typically, the visitor's public airport communication support is completely separate and walled‐off from the high‐security airport operations networks – the discussion and network design considered in this book focus on the former and not the latter, although similar technologies may be at play. Another characteristic is that, unlike stadiums, there is a nearly continuous requirement for connectivity, especially in large hub airports; stadiums are only used for relatively short periods a few times a week (once, less than once, or a few times a week). In addition to visitors, there are stationary concession businesses in the airport that would often make use of the same network infrastructure as the public network, although some administratively secure slice (for example, separate Virtual LANs [VLANs] would be used).

TABLE 1.2HDC KPIs for Airports

Key Performance Indicators

Key Performance Indicators

Pre‐pandemic Requirements

Data/VoIP connection density, for people on smartphones, laptops, tablets

Data/VoIP connection density, for people on smartphones, laptops, tablets

1 per 20 ft

2

in terminals

User experienced data rate

10–50 Mbps

Peak data rate

100 Mbps

Traffic volume density

5 Gbps per gate area (200 people per gate)

End‐to‐end latency

100 ms

Wayfinding

Throughout airport and in adjacent spaces, garages, car rental locations

Area of coverage

Entire airport and in adjacent spaces, garages, car rental locations

Traditional telephony on DAS systems

Dialtone

50 Erlangs per gate area (200 people per gate)

Call length

10 minutes per call

Connection density, IoT devices

Connection density, IoT devices

1 per 10 ft

2

throughout airport

User experienced data rate

0.384 Mbps

Peak data rate

0.768 Mbps

Traffic volume density

100 Mbps per 1000 ft

2

throughout airport and in adjacent spaces, garages, car rental locations

End‐to‐end latency

1–10 ms

Area of coverage

Entire airport and in adjacent spaces, garages, car rental locations

According to the National Plan of Integrated Airport Systems (NPIAS), there are approximately 19 700 airports in the United States. 5170 of these airports are open to the general public and 503 of them serve commercial flights. A typical gate area is 30 000 ft2 (which would equate to an area of 40 × 75 ft); however, not all of that space is usable for sojourn (implying that some areas within the 30 000 ft2 area may have a higher concentration of semi‐stationary users). If the busy hour concentration of people is 150 people, then there will be 1 person per 200 ft2 (a 10 × 20 feet area); however, there may be overcrowding situations where the concentration is comparable to the design goals depicted in Table 1.2. See Table 1.3 for the top 30 airports in the United States. Internationally, the Beijing Capital International Airport (Chaoyang‐Shunyi, Beijing, China) is the second largest in the world, following the Hartsfield–Jackson Atlanta International Airport, with about 50 million passengers per year as of 2018; Tokyo Haneda Airport (Ōta, Tokyo, Japan) had 41 million passengers; Dubai International Airport (Garhoud, Dubai, United Arab Emirates) had 42 million passengers; and London Heathrow Airport (Hillingdon, London, United Kingdom) had 39 million passengers.

FIGURE 1.2 A gate area at Fort Lauderdale‐Hollywood International Airport is crowded with travelers awaiting Delta flight 1420 to Atlanta Saturday, 14 March 2020.

(Courtesy: John Scalzi, Photographer).

1.2.2 Pre‐pandemic/Long‐term Requirements for Stadiums

For stadiums, a target of one million connections per square kilometer (also definable as 1 connection per m2 or one connection every 10 ft2) has been suggested by some researchers [2]. In the bleachers, the density could be high, even multiple individuals (say 2–3) every 10 ft2. Requirements include high‐capacity data and video access, IoT automation support, which also includes surveillance. The requirements are generally consistent with Table 1.2, with the coverage extending to parking lots. The services span more tightly defined time intervals (as contrasted to airports), possibly giving rise to a challenge in achieving certain goals for the Return on Investment on the infrastructure and the core‐network connectivity. The communication session may span the entire sporting event and a specified interval before and after the event.

A football field encompasses 57 600 ft2