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Analysis Forecast Coronavirus COVID-19 Industry Impact

Network Complexity, 5G rollouts will drive SON (Self-Organizing Network) Market spending to $5.5 Billion

The latest research report indicates that the growing complexity of mobile networks and 5G NR (New Radio) infrastructure rollouts will drive SON (Self-Organizing Network) spending to $5.5 Billion by 2022.

SON technology minimizes the lifecycle cost of running a mobile network by eliminating manual configuration of network elements at the time of deployment, right through to dynamic optimization and troubleshooting during operation. Besides improving network performance and customer experience, SON can significantly reduce the cost of mobile operator services, improving the OpEx-to-revenue ratio and deferring avoidable CapEx.

To support their LTE and HetNet deployments, early adopters of SON have already witnessed a spate of benefits – in the form of accelerated rollout times, simplified network upgrades, fewer dropped calls, improved call setup success rates, higher end-user throughput, alleviation of congestion during special events, increased subscriber satisfaction and loyalty, and operational efficiencies – such as energy and cost savings, and freeing up radio engineers from repetitive manual tasks.
Although SON was originally developed as an operational approach to streamline cellular RAN (Radio Access Network) deployment and optimization, mobile operators and vendors are increasingly focusing on integrating new capabilities such as self-protection against digital security threats, and self-learning through artificial intelligence techniques, as well as extending the scope of SON beyond the RAN to include both mobile core and transport network segments – which will be critical to address 5G requirements such as end-to-end network slicing. In addition, dedicated SON solutions for Wi-Fi and other access technologies have also emerged, to simplify wireless networking in home and enterprise environments.
Largely driven by the increasing complexity of today’s multi-RAN mobile networks – including network densification and spectrum heterogeneity, as well as 5G NR infrastructure rollouts, global investments in SON technology are expected to grow at a CAGR of approximately 11% between 2019 and 2022. By the end of 2022, SNS Telecom & IT estimates that SON will account for a market worth $5.5 Billion.
The “SON (Self-Organizing Networks) in the 5G Era: 2019 – 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of the SON and associated mobile network optimization ecosystem, including market drivers, challenges, enabling technologies, functional areas, use cases, key trends, standardization, regulatory landscape, mobile operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents revenue forecasts for both SON and conventional mobile network optimization, along with individual projections for 10 SON submarkets, and 6 regions from 2019 till 2030.
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Table of Content
1  Chapter  1:  Introduction
1.1  Executive  Summary
1.2  Topics  Covered
1.3  Forecast  Segmentation
1.4  Key  Questions  Answered
1.5  Key  Findings
1.6  Methodology
1.7  Target  Audience
1.8  Companies  &  Organizations  Mentioned2  Chapter  2:  SON  &  Mobile  Network  Optimization  Ecosystem
2.1  Conventional  Mobile  Network  Optimization
2.1.1  Network  Planning
2.1.2  Measurement  Collection:  Drive  Tests,  Probes  and  End  User  Data
2.1.3  Post-Processing,  Optimization  &  Policy  Enforcement
2.2  The  SON  (Self-Organizing  Network)  Concept
2.2.1  What  is  SON?
2.2.2  The  Need  for  SON
2.3  Functional  Areas  of  SON
2.3.1  Self-Configuration
2.3.2  Self-Optimization
2.3.3  Self-Healing
2.3.4  Self-Protection
2.3.5  Self-Learning
2.4  Market  Drivers  for  SON  Adoption
2.4.1  The  5G  Era:  Continued  Mobile  Network  Infrastructure  Investments
2.4.2  Optimization  in  Multi-RAN  &  HetNet  Environments
2.4.3  OpEx  &  CapEx  Reduction:  The  Cost  Savings  Potential
2.4.4  Improving  Subscriber  Experience  and  Churn  Reduction
2.4.5  Power  Savings:  Towards  Green  Mobile  Networks
2.4.6  Alleviating  Congestion  with  Traffic  Management
2.4.7  Enabling  Large-Scale  Small  Cell  Rollouts
2.4.8  Growing  Adoption  of  Private  LTE  &  5G-Ready  Networks
2.5  Market  Barriers  for  SON  Adoption
2.5.1  Complexity  of  Implementation
2.5.2  Reorganization  &  Changes  to  Standard  Engineering  Procedures
2.5.3  Lack  of  Trust  in  Automation
2.5.4  Proprietary  SON  Algorithms
2.5.5  Coordination  Between  Distributed  and  Centralized  SON
2.5.6  Network  Security  Concerns:  New  Interfaces  and  Lack  of  Monitoring

3  Chapter  3:  SON  Technology,  Use  Cases  &  Implementation  Architectures
3.1  Where  Does  SON  Sit  Within  a  Mobile  Network?
3.1.1  RAN
3.1.2  Mobile  Core
3.1.3  Transport  (Backhaul  &  Fronthaul)
3.1.4  Device-Assisted  SON
3.2  SON  Architecture
3.2.1  C-SON  (Centralized  SON)
3.2.2  D-SON  (Distributed  SON)
3.2.3  H-SON  (Hybrid  SON)
3.3  SON  Use-Cases
3.3.1  Self-Configuration  of  Network  Elements
3.3.2  Automatic  Connectivity  Management
3.3.3  Self-Testing  of  Network  Elements
3.3.4  Self-Recovery  of  Network  Elements/Software
3.3.5  Self-Healing  of  Board  Faults
3.3.6  Automatic  Inventory
3.3.7  ANR  (Automatic  Neighbor  Relations)
3.3.8  PCI  (Physical  Cell  ID)  Configuration
3.3.9  CCO  (Coverage  &  Capacity  Optimization)
3.3.10  MRO  (Mobility  Robustness  Optimization)
3.3.11  MLB  (Mobility  Load  Balancing)
3.3.12  RACH  (Random  Access  Channel)  Optimization
3.3.13  ICIC  (Inter-Cell  Interference  Coordination)
3.3.14  eICIC  (Enhanced  ICIC)
3.3.15  Energy  Savings
3.3.16  COD/COC  (Cell  Outage  Detection  &  Compensation)
3.3.17  MDT  (Minimization  of  Drive  Tests)
3.3.18  AAS  (Adaptive  Antenna  Systems)  &  Massive  MIMO
3.3.19  Millimeter  Wave  Links  in  5G  NR  (New  Radio)  Networks
3.3.20  Self-Configuration  &  Optimization  of  Small  Cells
3.3.21  Optimization  of  DAS  (Distributed  Antenna  Systems)
3.3.22  RAN  Aware  Traffic  Shaping
3.3.23  Traffic  Steering  in  HetNets
3.3.24  Optimization  of  NFV-Based  Networking
3.3.25  Auto-Provisioning  of  Transport  Links
3.3.26  Transport  Network  Bandwidth  Optimization
3.3.27  Transport  Network  Interference  Management
3.3.28  Self-Protection
3.3.29  SON  Coordination  Management
3.3.30  Seamless  Vendor  Infrastructure  Swap
3.3.31  Dynamic  Spectrum  Management  &  Allocation
3.3.32  Network  Slice  Optimization
3.3.33  Cognitive  &  Self-Learning  Networks

4  Chapter  4:  Key  Trends  in  Next-Generation  LTE  &  5G  SON  Implementations
4.1  Big  Data  &  Advanced  Analytics
4.1.1  Maximizing  the  Benefits  of  SON  with  Big  Data
4.1.2  The  Importance  of  Predictive  &  Behavioral  Analytics
4.2  Artificial  Intelligence  &  Machine  Learning
4.2.1  Towards  Self-Learning  SON  Engines  with  Machine  Learning
4.2.2  Deep  Learning:  Enabling  “Zero-Touch”  Mobile  Networks
4.3  NFV  (Network  Functions  Virtualization)
4.3.1  Enabling  the  SON-Driven  Deployment  of  VNFs  (Virtualized  Network  Functions)
4.4  SDN  (Software  Defined  Networking)  &  Programmability
4.4.1  Using  the  SDN  Controller  as  a  Platform  for  SON  in  Transport  Networks
4.5  Cloud  Computing
4.5.1  Facilitating  C-SON  Scalability  &  Elasticity
4.6  Small  Cells,  HetNets  &  RAN  Densification
4.6.1  Plug  &  Play  Small  Cells
4.6.2  Coordinating  UDNs  (Ultra  Dense  Networks)  with  SON
4.7  C-RAN  (Centralized  RAN)  &  Cloud  RAN
4.7.1  Efficient  Resource  Utilization  in  C-RAN  Deployments  with  SON
4.8  Unlicensed  &  Shared  Spectrum  Usage
4.8.1  Dynamic  Management  of  Spectrum  with  SON
4.9  MEC  (Multi-Access  Edge  Computing)
4.9.1  Potential  Synergies  with  SON
4.10  Network  Slicing
4.10.1  Use  of  SON  Mechanisms  for  Network  Slicing  in  5G  Networks
4.11  Other  Trends  &  Complementary  Technologies
4.11.1  Alternative  Carrier/Private  LTE  &  5G-Ready  Networks
4.11.2  FWA  (Fixed  Wireless  Access)
4.11.3  DPI  (Deep  Packet  Inspection)
4.11.4  Digital  Security  for  Self-Protection
4.11.5  SON  Capabilities  for  IoT  Applications
4.11.6  User-Based  Profiling  &  Optimization  for  Vertical  5G  Applications
4.11.7  Addressing  D2D  (Device-to-Device)  Communications  &  New  Use  Cases to be continued at https://www.supplydemandmarketresearch.com/son-self-organizing-networks-in-the-g-era-opportunities-challenges-strategies-forecasts-45574

SUPPLY DEMAND MARKET RESEARCH
Mr. Charles Lee
302-20 Misssisauga Valley Blvd, Missisauga, L5A 3S1, Toronto
Ph:12764775910
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Private LTE & 5G network infrastructure market an $8 Billion opportunity

The latest research report indicates that annual investments in private LTE and 5G network infrastructure – which includes RAN (Radio Access Network), mobile core and transport network equipment – will reach $8 Billion by the end of 2023.

With the standardization of features such as MCX (Mission-Critical PTT, Video & Data) services and URLCC (Ultra-Reliable Low-Latency Communications) by the 3GPP, LTE and 5G NR (New Radio) networks are rapidly gaining recognition as an all-inclusive critical communications platform for the delivery of both mission and business critical applications.

By providing authority over wireless coverage and capacity, private LTE and 5G networks ensure guaranteed and secure connectivity, while supporting a wide range of applications – ranging from PTT group communications and real-time video delivery to wireless control and automation in industrial environments. Organizations across the critical communications and industrial IoT (Internet of Things) domains – including public safety agencies, militaries, utilities, oil & gas companies, mining groups, railway & port operators, manufacturers and industrial giants – are making sizeable investments in private LTE networks.

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This 1,200-plus page report is the most comprehensive publication on the private LTE and 5G network market. In addition to detailed market size projections, it profiles more than 600 ecosystem players and covers over 40 case studies of private LTE and 5G networks, as well as analysis of hundreds of other private cellular networks.

The very first private 5G networks are also beginning to be deployed to serve a diverse array of usage scenarios spanning from connected factory robotics and massive-scale sensor networking to the control of AVGs (Automated Guided Vehicles) and AR/VR (Augmented & Virtual Reality). For example, Daimler’s Mercedes-Benz Cars division is establishing a local 5G network to support automobile production processes at its “Factory 56” in Sindelfingen, while the KMA (Korea Military Academy) is installing a dedicated 5G network in its northern Seoul campus to facilitate mixed reality-based military training programs – with a primary focus on shooting and tactical simulations.

In addition, with the emergence of neutral-host small cells, multi-operator connectivity and unlicensed/shared spectrum access schemes,  the use of private LTE and 5G networks in enterprise buildings, campuses and public venues is expected to grow significantly over the coming years. The practicality of spectrum sharing schemes such as the three-tiered CBRS (Citizens Broadband Radio Service) framework and Japan’s unlicensed sXGP (Shared Extended Global Platform) has already been proven with initial rollouts in locations such as corporate campuses, golf courses, race tracks, stadiums, airports and warehouses.

A number of independent neutral-host and wholesale operators are also stepping up with pioneering business models to provide LTE and 5G connectivity services to both mobile operators and enterprises, particularly in indoor settings and locations where it is technically or economically not feasible for traditional operators to deliver substantial wireless coverage and capacity.

Expected to reach $4.7 Billion in annual spending by the end of 2020, private LTE and 5G networks are increasingly becoming the preferred approach to deliver wireless connectivity for critical communications, industrial IoT, enterprise & campus environments, and public venues.  The market will further grow at a CAGR of 19% between 2020 and 2023, eventually accounting for nearly $8 Billion by the end of 2023.

According to our estimates that as much as 30% of these investments – approximately $2.5 Billion – will be directed towards the build-out of private 5G networks which will become preferred wireless connectivity medium to support the ongoing Industry 4.0 revolution for the automation and digitization of factories, warehouses, ports and other industrial premises, in addition to serving other verticals.

The “Private LTE & 5G Network Ecosystem: 2020 – 2030 – Opportunities, Challenges, Strategies, Industry Verticals & Forecasts” report presents an in-depth assessment of the private LTE and 5G network ecosystem including market drivers, challenges, enabling technologies, vertical market opportunities, applications, key trends, standardization, spectrum availability/allocation, regulatory landscape, deployment case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents forecasts for private LTE and 5G network infrastructure investments from 2020 till 2030. The forecasts cover three submarkets, two air interface technologies, 10 vertical markets and six regions.

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Table  of  Contents
1 Chapter  1:  Introduction
1.1 Executive  Summary
1.2 Topics  Covered
1.3 Forecast  Segmentation
1.4 Key  Questions  Answered
1.5 Key  Findings
1.6 Methodology
1.7 Target  Audience
1.8 Companies  &  Organizations  Mentioned

2 Chapter  2:  An  Overview  of  Private  LTE/5G  Networks
2.1 Private  Wireless  Networks
2.1.1 Addressing  the  Needs  of  the  Critical  Communications  Industry
2.1.2 The  Limitations  of  LMR  (Land  Mobile  Radio)  Networks
2.1.3 Growing  Use  of  Commercial  Mobile  Broadband  Technologies
2.1.4 Connectivity  Requirements  for  the  Industrial  IoT  (Internet  of  Things)
2.1.5 Localized  Mobile  Networks  for  Buildings,  Campuses  &  Public  Venues
2.2 LTE  &  5G  for  Private  Networking
2.2.1 Why  LTE  &  5G?
2.2.2 Performance  Metrics
2.2.3 Coexistence,  Interoperability  and  Spectrum  Flexibility
2.2.4 A  Thriving  Ecosystem  of  Chipsets,  Devices  &  Network  Equipment
2.2.5 Economic  Feasibility  of  Operation
2.2.6 Moving  Towards  LTE-Advanced  &  LTE-Advanced  Pro
2.2.7 Private  LTE  Support  in  LTE-Advanced  Pro
2.2.8 5G  NR  (New  Radio)  Capabilities  &  Usage  Scenarios
2.2.8.1 eMBB  (Enhanced  Mobile  Broadband)
2.2.8.2 URLCC  (Ultra-Reliable  Low-Latency  Communications)
2.2.8.3 mMTC  (Massive  Machine-Type  Communications)
2.3 Private  LTE  &  5G  Network  Operational  Models
2.3.1 Independent  Private  Network
2.3.2 Managed  Private  Network
2.3.3 Shared  Core  Private  Network
2.3.4 Hybrid  Commercial-Private  Network
2.3.5 Private  MVNO:  Commercial  Network  with  a  Private  Mobile  Core
2.3.6 Other  Approaches
2.4 Key  Applications  of  Private  LTE  &  5G  Networks
2.4.1 Secure  &  Seamless  Mobile  Broadband  Access
2.4.2 Bandwidth-Intensive  &  Latency-Sensitive  Field  Applications
2.4.3 Bulk  Multimedia  &  Data  Transfers
2.4.4 In-Building  Coverage  &  Capacity
2.4.5 Seamless  Roaming  &  Mobile  VPN  Access
2.4.6 Mission-Critical  HD  Voice  &  Group  Communications
2.4.7 Video  &  High-Resolution  Imagery
2.4.8 Massive-Scale  Video  Surveillance  &  Analytics
2.4.9 Messaging  &  Presence  Services
2.4.10 Location  Services  &  Mapping
2.4.11 Command  &  Control  Systems
2.4.12 Smart  Grid  Operations
2.4.13 Environmental  Monitoring
2.4.14 Industrial  Automation
2.4.15 Connected  Robotics
2.4.16 Machine  Vision
2.4.17 AR/VR  (Augmented  &  Virtual  Reality)
2.4.18 Telehealth  &  Remote  Surgery
2.4.19 High-Speed  Railway  Connectivity
2.4.20 PIS  (Passenger  Information  Systems)
2.4.21 Delay-Sensitive  Control  of  Railway  Infrastructure
2.4.22 In-Flight  Connectivity  for  Passengers  &  Airline  Operators
2.4.23 Maritime  Connectivity  for  Vessels  &  Offshore  Facilities
2.4.24 Telemetry,  Control  &  Remote  Diagnostics
2.4.25 Unmanned  Ground,  Marine  &  Aerial  Vehicles
2.5 Market  Drivers
2.5.1 Recognition  of  LTE  &  5G  as  the  De-Facto  Platform  for  Wireless  Connectivity
2.5.2 Spectral  Efficiency  &  Bandwidth  Flexibility
2.5.3 Regional  Interoperability  &  Cost  Efficiency
2.5.4 Endorsement  from  the  Critical  Communications  Industry
2.5.5 Emergence  of  Unlicensed  &  Shared  Spectrum  Technologies
2.5.6 Growing  Demand  for  High-Speed  &  Low-Latency  Data  Applications
2.5.7 Limited  Coverage  in  Indoor,  Industrial  &  Remote  Environments
2.5.8 Favorable  Licensing  Schemes  for  Localized  LTE  &  5G  Networks
2.5.9 Control  over  QoS  (Quality-of-Service)
2.5.10 Privacy  &  Security
2.6 Market  Barriers
2.6.1 Lack  of  Licensed  Spectrum  for  Wide-Area  Coverage
2.6.2 Funding  Challenges  for  Large-Scale  Networks
2.6.3 Technical  Complexities  of  Implementation  &  Operation
2.6.4 Smaller  Coverage  Footprint  Than  Legacy  LMR  Systems
2.6.5 Competition  from  IEEE  802.16s,  AeroMACS,  WiGRID  &  Other  Technologies
2.6.6 Delayed  Standardization

3 Chapter  3:  System  Architecture  &  Technologies  for  Private  LTE/5G  Networks
3.1 Architectural  Components  of  Private  LTE  &  5G  Networks
3.1.1 UE  (User  Equipment)
3.1.2 E-UTRAN  –  LTE  RAN  (Radio  Access  Network)
3.1.2.1 eNBs  –  LTE  Base  Stations
3.1.3 NG-RAN  –  5G  NR  (New  Radio)  Access  Network
3.1.3.1 gNBs  –  5G  NR  Base  Stations
3.1.3.2 en-gNBs  –  Secondary  Node  5G  NR  Base  Stations
3.1.3.3 ng-eNBs  –  Next  Generation  LTE  Base  Stations
3.1.4 Transport  Network
3.1.4.1 Backhaul
3.1.4.2 Fronthaul  &  Midhaul
3.1.5 EPC  (Evolved  Packet  Core)  –  The  LTE  Mobile  Core
3.1.5.1 SGW  (Serving  Gateway)
3.1.5.2 PGW  (Packet  Data  Network  Gateway)
3.1.5.3 MME  (Mobility  Management  Entity)
3.1.5.4 HSS  (Home  Subscriber  Server)
3.1.5.5 PCRF  (Policy  Charging  and  Rules  Function)
3.1.6 5GC  (5G  Core)/NGC  (Next-Generation  Core)
3.1.6.1 AMF  (Access  &  Mobility  Management  Function)
3.1.6.2 UPF  (User  Plane  Function)
3.1.6.3 SMF  (Session  Management  Function)
3.1.6.4 PCF  (Policy  Control  Function)
3.1.6.5 NEF  (Network  Exposure  Function)
3.1.6.6 NRF  (Network  Repository  Function)
3.1.6.7 UDM  (Unified  Data  Management)
3.1.6.8 UDR  (Unified  Data  Repository)
3.1.6.9 AUSF  (Authentication  Server  Function)
3.1.6.10 AF  (Application  Function)
3.1.6.11 NSSF  (Network  Slice  Selection  Function)
3.1.6.12 NWDAF  (Network  Data  Analytics  Function)
3.1.6.13 Other  Elements
3.1.7 IMS  (IP-Multimedia  Subsystem),  Application  &  Service  Elements
3.1.7.1 IMS  Core  &  VoLTE/VoNR
3.1.7.2 eMBMS/FeMBMS  –  Broadcasting/Multicasting  over  LTE/5G  Networks
3.1.7.3 ProSe  (Proximity  Services)
3.1.7.4 Group  Communication  &  Mission-Critical  Services
3.1.8 Gateways  for  LTE/5G-External  Network  Interworking
3.2 Key  Enabling  Technologies  &  Concepts
3.2.1 Critical  Communications
3.2.1.1 MCPTT  (Mission-Critical  PTT)  Voice  &  Group  Communications
3.2.1.2 Mission-Critical  Video  &  Data
3.2.1.3 ProSe  (Proximity  Services)  for  D2D  Connectivity  &  Communications
3.2.1.4 IOPS  (Isolated  E-UTRAN  Operation  for  Public  Safety)
3.2.1.5 Deployable  LTE  &  5G  Systems
3.2.1.6 UE  Enhancements
3.2.2 Industrial  IoT
3.2.2.1 eMTC,  NB-IoT  &  mMTC:  Wide  Area  &  High  Density  IoT  Applications
3.2.2.2 Techniques  for  URLLC
3.2.2.3 TSN  (Time  Sensitive  Networking)
3.2.3 QPP  (QoS,  Priority  &  Preemption)
3.2.4 High-Precision  Positioning
3.2.5 End-to-End  Security
3.2.6 Quantum  Cryptography  Technologies

3.2.7 Licensed  Spectrum  Sharing  &  Aggregation
3.2.8 Unlicensed  &  Shared  Spectrum  Usage
3.2.8.1 CBRS  (Citizens  Broadband  Radio  Service):  Three-Tiered  Sharing
3.2.8.2 LSA  (Licensed  Shared  Access):  Two-Tiered  Sharing
3.2.8.3 sXGP  (Shared  Extended  Global  Platform):  Non-Tiered  Unlicensed  Access
3.2.8.4 LTE-U/LAA  (License  Assisted  Access)  &  eLAA  (Enhanced  LAA):  Licensed  &  Unlicensed  Spectrum  Aggregation
3.2.8.5 MulteFire
3.2.8.6 5G  NR-U
3.2.9 SDR  (Software-Defined  Radio)
3.2.10 Cognitive  Radio  &  Spectrum  Sensing
3.2.11 Wireless  Connection  Bonding
3.2.12 Network  Sharing  &  Slicing
3.2.12.1 MOCN  (Multi-Operator  Core  Network)
3.2.12.2 DECOR  (Dedicated  Core)
3.2.12.3 Network  Slicing
3.2.13 Software-Centric  Networking
3.2.13.1 NFV  (Network  Functions  Virtualization)
3.2.13.2 SDN  (Software  Defined  Networking)
3.2.14 Small  Cells
3.2.15 C-RAN  (Centralized  RAN)
3.2.16 SON  (Self-Organizing  Networks)
3.2.17 MEC  (Multi-Access  Edge  Computing)
3.2.18 Artificial  Intelligence  &  Machine  Learning
3.2.19 Big  Data  &  Advanced  Analytics

to be continued @https://www.supplydemandmarketresearch.com/home/toc_publisher/1350876?code=SDMREL1350876

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