Network complexity, 5G rollouts will drive SON (Self-Organizing Network) spending to $5.5 Billion 2018 to 2025 Forecasts

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.

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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.

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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, the SON will account for a market worth $5.5 Billion.

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.

The Global SON (Self-Organizing Networks) Market research 2018 covers the current market size and its growth rates based on 5 year history data. It also covers various types of segmentation such as by geography [North America, Europe, China, Japan, Southeast Asia & India], by product /end user type, by applications in overall market. The in-depth information by segments of SON (Self-Organizing Networks) market helps monitor performance & make critical decisions for growth and profitability. It provides information on trends and developments focuses on markets and materials, capacities, technologies and the changing structure of the Global SON (Self-Organizing Networks) Market.

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, the SON will account for a market worth $5.5 Billion.

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:  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 and many more……..

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