Report Description
The global self-organizing network and optimization software market is anticipated to expand at a substantial CAGR during the forecast period, 2021 – 2028. The growth of the market is attributed to the rapidly increasing cellular traffic and growing number of mobile phone users.
Self-organizing networks (SONs) are advanced systems that offer effective network activities by operating, optimizing, and configuring congested traffic to make them easier to manage and automate. The key functions of the system include changes in propagation characteristics, traffic patterns, and network deployments that can help to optimize communication networks. Under congested traffic conditions, SONs provide effective transmission by providing capacity-based optimization or a load balancing. This optimization software, in turn, offers an efficient distribution of network traffic across multiple resources to enhance network efficiency and network self-healing.
Market Trends, Drivers, Restraints, and Opportunities:
- Some SONs benefit such as improved user experience and lower operating costs of network service are key factors that can drive market growth.
- Wide expansion of 2G and 3G networks by service providers and increasing number of mobile phone users are expected to boost market growth during the forecast period.
- The inability of conventional systems to handle network complexities combined with the increasing complexities of 3G and LTE networks present key driving factors for the market.
- High cost of the installation and lack of expert operators of the network system are key challenging factors that can hamper the market growth.
- R&D activities and technological advancement that help to produce innovative self-organizing network systems are key opportunities for the market expansion in the coming years.
Scope of the Report
The report on the global self-organizing network and optimization software market includes an assessment of the market, trends, segments, and regional markets. Overview and dynamics have also been included in the report.
Attributes
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Details
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Report Title
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Self-organizing Network and Optimization Software Market - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast
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Base Year
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2020
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Historic Data
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2018–2019
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Forecast Period
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2021–2028
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Segmentation
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Network Types (Centralized SONs [Manual Open Loop and Automated Closed-loop] and Distributed SONs) and Network Technology (2G, 3G, and 4G or LTE)
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Regional Scope
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Asia Pacific, North America, Latin America, Europe, and Middle East & Africa
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Report Coverage
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Company Share, Market Analysis and Size, Competitive Landscape, Growth Factors, and Trends, and Revenue Forecast
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Key Players Covered in the Report
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Cisco Systems Inc., Amdocs Ltd., Ericsson, Nokia Solutions and Networks, Reverb Networks, Huawei Technologies Co. Ltd., Cellwize Wireless Technologies Pte. Ltd., and Eden Rock Communications.
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Global Self-organizing Network and Optimization Software Market Segment Insights
LTE segment is expected to grow at a rapid pace
Based on network technology, the global self-organizing network and optimization software market is divided into 2G, 3G, and 4G or LTE. The LTE segment accounted for a key share of the market in 2020 and is anticipated to expand at a rapid pace during the forecast period. The LTE of cellular communications provides significantly more bandwidth, easy operation, and implementation of a wide range of new applications. With the rise in network capacity, network management helps to facilitate the need for better operations and operational support systems. As SON a newer technology, it is acting as a key catalyst for developing operational support structures for LTE networks.
C-SONs segment is expected to register at a substantial CAGR
On the basis of network types, the global self-organizing network and optimization software market is bifurcated into centralized SONs (C-SONs) and Distributed SONs (D-SONs). The C-SONs segment is further segmented into manual open loop and automatic closed-loop. The C-SONs segment is anticipated to expand at a substantial CAGR during the forecast period owing to increased adoption of C-SONs by various network operators due to its easy handling of several different networks under a central system.
North America is expected to constitute a major share
In terms of regions, the global self-organizing network and optimization software market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America is expected to constitute a major share of the market due to increasing use of SONs apps and early developed of innovative network infrastructure especially in the US. However, the market in Asia Pacific is anticipated to register a significant CAGR during the forecast period due to increased adoption of LTE in cellular networks, especially in countries such as China and India.
Segments
The global self-organizing network and optimization software market has been segmented on the basis of
Network Types
- Centralized SONs (C-SONs)
- Manual Open Loop
- Automated Closed-loop
- Distributed SONs (D-SONs)
Network Technology
Regions
- Asia Pacific
- North America
- Latin America
- Europe
- Middle East & Africa
Key Players
- Cisco Systems Inc.
- Amdocs Ltd.
- Ericsson (Sweden)
- Nokia Solutions and Networks
- Reverb Networks
- Huawei Technologies Co. Ltd.
- Cellwize Wireless Technologies Pte. Ltd.
- (Singapore) and Eden Rock Communications
Competitive Landscape
Some of the key players competing in the self-organizing network and optimization software market include Cisco Systems Inc., Ericsson, Reverb Networks, Amdocs Ltd., Cellwize Wireless Technologies Pte. Ltd., Eden Rock Communications, Huawei Technologies Co. Ltd., and Nokia Solutions and Networks. To expand their market share, these companies are constantly engaged in various market tactics such as product launches, acquisitions, alliances, collaborations, and contracts.
Table Of Content
1. Executive Summary
2. Assumptions and Acronyms Used
3. Research Methodology
4. Self-organizing Network and Optimization Software Market Overview
4.1. Introduction
4.1.1. Market Taxonomy
4.1.2. Market Definition
4.2. Macro-Economic Factors
4.2.1. Industry Outlook
4.3. Self-organizing Network and Optimization Software Market Dynamics
4.3.1. Market Drivers
4.3.2. Market Restraints
4.3.3. Opportunity
4.3.4. Market Trends
4.4. Self-organizing Network and Optimization Software Market - Supply Chain
4.5. Global Self-organizing Network and Optimization Software Market Forecast
4.5.1. Self-organizing Network and Optimization Software Market Size (US$ Mn) and Y-o-Y Growth
4.5.2. Self-organizing Network and Optimization Software Market Size (000’ Units) and Y-o-Y Growth
4.5.3. Self-organizing Network and Optimization Software Market Absolute $ Opportunity
5. Global Self-organizing Network and Optimization Software Market Analysis and Forecast by Types
5.1. Market Trends
5.2. Introduction
5.2.1. Basis Point Share (BPS) Analysis by Types
5.2.2. Y-o-Y Growth Projections by Types
5.3. Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
5.3.1. Centralized SONs (C-SONs)
5.3.2.
Distributed SONs (D-SONs)
5.4. Absolute $ Opportunity Assessment by Types
5.5. Market Attractiveness/Growth Potential Analysis by Types
6. Global Self-organizing Network and Optimization Software Market Analysis and Forecast by Region
6.1. Market Trends
6.2. Introduction
6.2.1. Basis Point Share (BPS) Analysis by Region
6.2.2. Y-o-Y Growth Projections by Region
6.3. Self-organizing Network and Optimization Software Market Size and Volume Forecast by Region
6.3.1. North America
6.3.2. Latin America
6.3.3. Europe
6.3.4. Asia Pacific
6.3.5. Middle East and Africa (MEA)
6.4. Absolute $ Opportunity Assessment by Region
6.5. Market Attractiveness/Growth Potential Analysis by Region
6.6. Global Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
7. North America Self-organizing Network and Optimization Software Market Analysis and Forecast
7.1. Introduction
7.1.1. Basis Point Share (BPS) Analysis by Country
7.1.2. Y-o-Y Growth Projections by Country
7.2. North America Self-organizing Network and Optimization Software Market Size and Volume Forecast by Country
7.2.1. U.S.
7.2.2. Canada
7.3. Absolute $ Opportunity Assessment by Country
7.4. North America Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
7.4.1. Centralized SONs (C-SONs)
7.4.2.
Distributed SONs (D-SONs)
7.5. Basis Point Share (BPS) Analysis by Types
7.6. Y-o-Y Growth Projections by Types
7.7. Market Attractiveness/Growth Potential Analysis
7.7.1. By Country
7.7.2. By Product Type
7.7.3. By Application
7.8. North America Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
8. Latin America Self-organizing Network and Optimization Software Market Analysis and Forecast
8.1. Introduction
8.1.1. Basis Point Share (BPS) Analysis by Country
8.1.2. Y-o-Y Growth Projections by Country
8.1.3. Latin America Average Pricing Analysis
8.2. Latin America Self-organizing Network and Optimization Software Market Size and Volume Forecast by Country
8.2.1. Brazil
8.2.2. Mexico
8.2.3. Rest of Latin America
8.3. Absolute $ Opportunity Assessment by Country
8.4. Latin America Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
8.4.1. Centralized SONs (C-SONs)
8.4.2.
Distributed SONs (D-SONs)
8.5. Basis Point Share (BPS) Analysis by Types
8.6. Y-o-Y Growth Projections by Types
8.7. Market Attractiveness/Growth Potential Analysis
8.7.1. By Country
8.7.2. By Product Type
8.7.3. By Application
8.8. Latin America Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
9. Europe Self-organizing Network and Optimization Software Market Analysis and Forecast
9.1. Introduction
9.1.1. Basis Point Share (BPS) Analysis by Country
9.1.2. Y-o-Y Growth Projections by Country
9.1.3. Europe Average Pricing Analysis
9.2. Europe Self-organizing Network and Optimization Software Market Size and Volume Forecast by Country
9.2.1. Germany
9.2.2. France
9.2.3. Italy
9.2.4. U.K.
9.2.5. Spain
9.2.6. Russia
9.2.7. Rest of Europe
9.3. Absolute $ Opportunity Assessment by Country
9.4. Europe Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
9.4.1. Centralized SONs (C-SONs)
9.4.2.
Distributed SONs (D-SONs)
9.5. Basis Point Share (BPS) Analysis by Types
9.6. Y-o-Y Growth Projections by Types
9.7. Market Attractiveness/Growth Potential Analysis
9.7.1. By Country
9.7.2. By Product Type
9.7.3. By Application
9.8. Europe Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
10. Asia Pacific Self-organizing Network and Optimization Software Market Analysis and Forecast
10.1. Introduction
10.1.1. Basis Point Share (BPS) Analysis by Country
10.1.2. Y-o-Y Growth Projections by Country
10.1.3. Asia Pacific Average Pricing Analysis
10.2. Asia Pacific Self-organizing Network and Optimization Software Market Size and Volume Forecast by Country
10.2.1. China
10.2.2. Japan
10.2.3. South Korea
10.2.4. India
10.2.5. Australia
10.2.6. Rest of Asia Pacific (APAC)
10.3. Absolute $ Opportunity Assessment by Country
10.4. Asia Pacific Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
10.4.1. Centralized SONs (C-SONs)
10.4.2.
Distributed SONs (D-SONs)
10.5. Basis Point Share (BPS) Analysis by Types
10.6. Y-o-Y Growth Projections by Types
10.7. Market Attractiveness/Growth Potential Analysis
10.7.1. By Country
10.7.2. By Product Type
10.7.3. By Application
10.8. Asia Pacific Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
11. Middle East & Africa Self-organizing Network and Optimization Software Market Analysis and Forecast
11.1. Introduction
11.1.1. Basis Point Share (BPS) Analysis by Country
11.1.2. Y-o-Y Growth Projections by Country
11.1.3. Middle East & Africa Average Pricing Analysis
11.2. Middle East & Africa Self-organizing Network and Optimization Software Market Size and Volume Forecast by Country
11.2.1. Saudi Arabia
11.2.2. South Africa
11.2.3. UAE
11.2.4. Rest of Middle East & Africa (MEA)
11.3. Absolute $ Opportunity Assessment by Country
11.4. Middle East & Africa Self-organizing Network and Optimization Software Market Size and Volume Forecast by Types
11.4.1. Centralized SONs (C-SONs)
11.4.2.
Distributed SONs (D-SONs)
11.5. Basis Point Share (BPS) Analysis by Types
11.6. Y-o-Y Growth Projections by Types
11.7. Market Attractiveness/Growth Potential Analysis
11.7.1. By Country
11.7.2. By Product Type
11.7.3. By Application
11.8. Middle East & Africa Self-organizing Network and Optimization Software Demand Share Forecast, 2019-2026
12. Competition Landscape
12.1. Global Self-organizing Network and Optimization Software Market: Market Share Analysis
12.2. Self-organizing Network and Optimization Software Distributors and Customers
12.3. Self-organizing Network and Optimization Software Market: Competitive Dashboard
12.4. Company Profiles (Details: Overview, Financials, Developments, Strategy)
12.4.1. Cisco Systems Inc.
12.4.2.
Amdocs Ltd.
12.4.3.
Ericsson (Sweden)
12.4.4.
Nokia Solutions and Networks
12.4.5.
Reverb Networks
12.4.6.
Huawei Technologies Co. Ltd.
12.4.7.
Cellwize Wireless Technologies Pte. Ltd.