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O-RAN準リアルタイムRIC市場 - 世界の産業規模、動向、機会、予測:コンポーネント別、展開別、地域別、競合別、2019-2029年

O-RAN Near-Real-Time RAN Intelligent Controller Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Deployment, By Region, and By Competition, 2019-2029F


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英文 185 Pages
納期
2~3営業日
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O-RAN準リアルタイムRIC市場 - 世界の産業規模、動向、機会、予測:コンポーネント別、展開別、地域別、競合別、2019-2029年
出版日: 2024年06月14日
発行: TechSci Research
ページ情報: 英文 185 Pages
納期: 2~3営業日
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  • 概要
  • 目次
概要

O-RAN準リアルタイムRICの世界市場規模は2023年に45億3,000万米ドルとなり、2029年までのCAGRは51.62%で予測期間の堅調な成長が予測されています。

世界のO-RAN準リアルタイムRIC市場は、通信と最先端技術の融合に牽引され、変革的な成長を遂げています。O-RANは、RANのダイナミックなオーケストレーションを促進し、準リアルタイムRICはこのパラダイムシフトの要として浮上しています。このインテリジェントコントローラーは、リソースの割り当てを最適化し、ネットワークの効率を高め、多様なサービス要件に適応します。業界の覇権を握るのは北米であり、技術力と急速な5Gの普及を活用しています。xAppフレームワークは、開発者が多様なネットワーク需要に合わせたアプリケーションを作成できるようにする、支配的なコンポーネントとして際立っています。集中型の導入モデルが主流で、全体的なネットワーク管理を提供し、クラウドネイティブの動向と一致しています。セキュリティの課題は依然として残っていますが、協調的な取り組み、標準化イニシアティブ、オープンアーキテクチャへのコミットメントがイノベーションを後押ししています。市場の軌跡は、インテリジェントで柔軟性が高くO-RANへのコミットメントを強調するものであり、準リアルタイムRICは通信ランドスケープの再形成の最前線にあります。

市場概要
予測期間 2025-2029
市場規模:2023年 45億3,000万米ドル
市場規模:2029年 399億6,000万米ドル
CAGR:2024年~2029年 51.62%
急成長セグメント 集中型
最大市場 北米

市場促進要因

5G導入の加速とネットワークの柔軟性への要求

オープンかつ分離されたネットワークアーキテクチャへの移行

インテリジェントなオーケストレーションと最適化の需要

人工知能と機械学習の進歩

コスト削減と運用効率の目標

主な市場課題

相互運用性の複雑さと標準化の課題

O-RAN環境におけるセキュリティの懸念

既存のRANインフラとの統合課題

AI/MLの統合と最適化の複雑さ

多様なサービスのためのネットワークスライシングの管理

主な市場動向

O-RAN準リアルタイムRICによるネットワークアーキテクチャの進化

5G展開の加速とO-RANの導入

相互運用性とコラボレーションへの取り組み

人工知能と機械学習の統合

準リアルタイムRICの展開におけるセキュリティと信頼性

目次

第1章 概要

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 COVID-19が世界のO-RAN準リアルタイムRIC市場に与える影響

第5章 顧客の声

第6章 世界のO-RAN準リアルタイムRIC市場概要

第7章 世界のO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別(A1メディエーター、Demo1、E2マネージャー(E2M)、E2ターミネーター(E2T)、ロギング、RICアラームシステム、RICメッセージルーター(RMR)、RNIB、ルーティングマネージャー、CXX用 xAppフレームワーク、Go用 xAppフレームワーク、Python用 xAppフレームワーク)
    • 展開別(集中型、分散型)
    • 地域別(北米、欧州、南米、中東・アフリカ、アジア太平洋)
  • 企業別(2023)
  • 市場マップ

第8章 北米のO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別
    • 展開別
    • 国別
  • 北米:国別分析
    • 米国
    • カナダ
    • メキシコ

第9章 欧州のO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別
    • 展開別
    • 国別
  • 欧州:国別分析
    • ドイツ
    • フランス
    • 英国
    • イタリア
    • スペイン

第10章 南米のO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別
    • 展開別
    • 国別
  • 南米:国別分析
    • ブラジル
    • コロンビア
    • アルゼンチン

第11章 中東・アフリカのO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別
    • 展開別
    • 国別
  • 中東・アフリカ:国別分析
    • サウジアラビア
    • アラブ首長国連邦
    • 南アフリカ

第12章 アジア太平洋地域のO-RAN準リアルタイムRIC市場展望

  • 市場規模・予測
    • 金額別
  • 市場シェア・予測
    • コンポーネント別
    • 展開別
    • 国別
  • アジア太平洋地域:国別分析
    • 中国
    • インド
    • 日本
    • 韓国
    • オーストラリア

第13章 市場力学

  • 促進要因
  • 課題

第14章 市場動向と発展

第15章 企業プロファイル

  • Nokia Corporation
  • Rakuten Mobile, Inc.
  • Samsung Electronics Co., Ltd.
  • Sterlite Technologies Limited
  • Telefonaktiebolaget LM Ericsson
  • IS-Wireless
  • Parallel Wireless, Inc.
  • VIAVI Solutions Inc.
  • HCL Technologies Limited
  • Casa Systems, Inc.

第16章 戦略的提言

第17章 調査会社について・免責事項

目次
Product Code: 21480

Global O-RAN Near-Real-Time RAN Intelligent Controller Market was valued at USD 4.53 Billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 51.62% through 2029. The Global O-RAN Near-Real-Time RAN Intelligent Controller (Near-RT RIC) Market is witnessing transformative growth, driven by the convergence of telecommunications and cutting-edge technologies. O-RAN, an open and disaggregated architecture, facilitates the dynamic orchestration of radio access networks, and Near-RT RIC emerges as a linchpin in this paradigm shift. This intelligent controller optimizes resource allocation, enhances network efficiency, and adapts to diverse service requirements, essential for the evolving landscape of 5G and beyond. Industry dominance is marked by North America, leveraging technological prowess and rapid 5G adoption. The xApp Framework stands out as a dominant component, empowering developers to create applications tailored to varied network demands. Centralized deployment models prevail, providing holistic network management and aligning with cloud-native trends. While security challenges persist, collaborative efforts, standardization initiatives, and a commitment to open architectures fuel innovation. The market's trajectory underscores a commitment to intelligent, flexible, and open radio access networks, with Near-RT RIC at the forefront of reshaping the telecommunications landscape.

Market Overview
Forecast Period2025-2029
Market Size 2023USD 4.53 Billion
Market Size 2029USD 39.96 Billion
CAGR 2024-202951.62%
Fastest Growing SegmentCentralized
Largest MarketNorth America

Key Market Drivers

Acceleration of 5G Deployments and Demand for Network Flexibility:

A primary driver propelling the global O-RAN Near-Real-Time RAN Intelligent Controller market is the accelerating deployment of 5G networks worldwide. The demand for higher data rates, lower latency, and increased network capacity has led to a rapid rollout of 5G infrastructure. Near-RT RIC plays a pivotal role in 5G networks by providing intelligent and dynamic orchestration of radio access network (RAN) functions. As operators seek to harness the full potential of 5G, the flexibility offered by O-RAN principles becomes essential. Near-RT RIC enables operators to optimize RAN resources, allocate bandwidth efficiently, and adapt to varying network conditions, fostering a more agile and responsive communication infrastructure.

Shift Towards Open and Disaggregated Network Architectures:

The global O-RAN Near-Real-Time RAN Intelligent Controller market is driven by a fundamental shift in network architectures towards openness and disaggregation. Traditional monolithic RAN architectures are being replaced by open and interoperable solutions that leverage virtualization and software-defined principles. The O-RAN Alliance's initiatives, promoting open interfaces and standardized protocols, have accelerated this transformation. Near-RT RIC serves as a linchpin in this paradigm shift, offering intelligent control and orchestration capabilities within the disaggregated RAN environment. The driver behind this trend is the industry's recognition of the need for flexibility, vendor diversity, and innovation in RAN deployments, ultimately leading to a more competitive and adaptable landscape.

Demand for Intelligent Orchestration and Optimization:

The increasing complexity of modern communication networks, coupled with the dynamic nature of user demands, is driving the demand for intelligent orchestration and optimization provided by Near-RT RIC. As networks evolve to support a diverse range of services, including enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC), the need for adaptive and real-time RAN control becomes paramount. Near-RT RIC addresses this demand by dynamically orchestrating RAN functions, optimizing resource allocation, and adapting to varying network conditions. The driver here is the industry's quest for more efficient and responsive networks capable of meeting the diverse requirements of emerging applications and services.

Advancements in Artificial Intelligence and Machine Learning:

The integration of artificial intelligence (AI) and machine learning (ML) capabilities represents a significant driver in the global O-RAN Near-Real-Time RAN Intelligent Controller market. AI and ML enable Near-RT RIC to learn from network behavior, predict future conditions, and make informed decisions in near-real-time. This driver is fueled by advancements in AI algorithms, increased computational power, and the availability of large datasets for training models. Leveraging AI and ML, Near-RT RIC can optimize RAN parameters, predict network congestion, and proactively address issues, contributing to enhanced network performance and user experiences. The industry's pursuit of self-optimizing and autonomous networks is a driving force behind the integration of AI and ML in Near-RT RIC.

Cost Reduction and Operational Efficiency Goals:

Cost reduction and operational efficiency emerge as critical drivers in the adoption of O-RAN Near-Real-Time RAN Intelligent Controllers. Traditional RAN architectures often involve proprietary hardware and tightly integrated solutions, resulting in high capital and operational expenditures. O-RAN's open and disaggregated approach allows operators to introduce vendor diversity, choose best-of-breed components, and leverage commercial off-the-shelf (COTS) hardware. Near-RT RIC, by providing intelligent control and optimization capabilities, contributes to operational efficiency by dynamically adapting to network conditions and automating resource management. The drive to minimize costs and enhance operational efficiency motivates operators to embrace O-RAN principles, with Near-RT RIC playing a pivotal role in realizing these objectives.

Key Market Challenges

Interoperability Complexities and Standardization Challenges:

One of the significant challenges facing the global O-RAN Near-Real-Time RAN Intelligent Controller market is the complexities associated with interoperability and the ongoing standardization efforts. The industry's move towards open and disaggregated network architectures necessitates seamless interoperability among components from different vendors. However, achieving this interoperability is challenging due to variations in implementations, interfaces, and protocols across different Near-RT RIC solutions. The lack of standardized interfaces poses hurdles in integrating diverse components, potentially leading to integration issues, performance discrepancies, and limiting the flexibility that O-RAN aims to provide. Industry alliances, such as the O-RAN Alliance, are actively working towards defining common interfaces, but the process of standardization is intricate and requires consensus among various stakeholders.

Security Concerns in Open RAN Environments:

Security concerns pose a significant challenge to the adoption of O-RAN Near-Real-Time RAN Intelligent Controllers, particularly in the context of open RAN environments. The disaggregated and open nature of O-RAN introduces new attack vectors and vulnerabilities that need to be addressed comprehensively. Ensuring the security and integrity of communication networks becomes paramount as Near-RT RIC plays a crucial role in orchestrating and optimizing RAN functions. Challenges include securing interfaces, preventing unauthorized access, and safeguarding against potential cyber threats. Industry stakeholders must collaborate to establish robust security frameworks, implement encryption protocols, and develop best practices to fortify the security posture of Near-RT RIC deployments.

Integration Challenges with Existing RAN Infrastructure:

Integrating O-RAN Near-Real-Time RAN Intelligent Controllers with existing RAN infrastructure poses a substantial challenge for network operators. Many operators have established RAN deployments that may not be inherently designed to accommodate the open and disaggregated principles of O-RAN. Retrofitting existing infrastructure to support Near-RT RIC functionalities involves navigating compatibility issues, addressing legacy protocols, and managing the coexistence of traditional and modern RAN components. The challenge lies in ensuring a smooth transition that leverages the benefits of Near-RT RIC without causing disruptions to existing services or compromising the performance of the overall network.

Complexity of AI/ML Integration and Optimization:

The integration of artificial intelligence (AI) and machine learning (ML) capabilities into O-RAN Near-Real-Time RAN Intelligent Controllers introduces a unique set of challenges. While AI and ML promise to enhance the adaptability and efficiency of RAN operations, integrating these technologies seamlessly requires addressing complexity in algorithm development, training models, and ensuring real-time responsiveness. Challenges include optimizing AI/ML models for near-real-time decision-making, managing the computational resources required for on-device processing, and handling the dynamic and unpredictable nature of wireless networks. The industry must overcome these challenges to fully harness the potential of intelligent RAN controllers and deliver on the promise of self-optimizing and autonomous networks.

Management of Network Slicing for Diverse Services:

As the O-RAN Near-Real-Time RAN Intelligent Controller market evolves, the management of network slicing emerges as a notable challenge. Network slicing is a key feature enabling the creation of isolated virtual networks tailored to specific service requirements. However, efficiently managing multiple network slices for diverse services, each with distinct performance and latency requirements, presents challenges. Coordinating resources, ensuring isolation, and dynamically adapting to changing service demands require sophisticated orchestration and coordination mechanisms within the Near-RT RIC. Addressing these challenges is crucial to delivering on the promise of flexible and scalable networks that can accommodate a wide range of services and applications across industries.

Key Market Trends

Evolving Network Architectures with O-RAN Near-RT RIC:

The global O-RAN Near-Real-Time RAN Intelligent Controller market is witnessing a trend marked by the evolution of network architectures. Near-RT RIC plays a pivotal role in this evolution by introducing intelligence and programmability to radio access networks (RANs). This trend is characterized by the shift toward more flexible and dynamic RAN architectures, allowing operators to optimize network performance, enhance resource allocation, and support diverse services. The introduction of intelligence at the RAN level enables near-real-time decision-making, contributing to the overall efficiency and adaptability of communication networks.

Acceleration of 5G Deployments and O-RAN Adoption:

A significant trend in the O-RAN Near-RT RIC market is the acceleration of 5G deployments and the widespread adoption of O-RAN principles. As 5G networks continue to roll out globally, there is a growing recognition of the importance of intelligent RAN controllers in optimizing the performance of 5G infrastructure. Near-RT RIC, by facilitating real-time orchestration and control of RAN functions, aligns with the requirements of 5G networks, enabling operators to deliver enhanced user experiences, low-latency communication, and efficient resource utilization.

Interoperability and Collaboration Initiatives:

Interoperability and collaborative initiatives are emerging as prominent trends in the O-RAN Near-RT RIC market. As the industry embraces the principles of openness and disaggregation, there is a concerted effort to ensure interoperability among different vendors' Near-RT RIC solutions. Industry alliances, such as the O-RAN Alliance, are playing a crucial role in fostering collaboration, defining common interfaces, and establishing standards that promote seamless integration of Near-RT RIC components. This trend aims to create a more diverse and competitive ecosystem while avoiding vendor lock-in and accelerating the pace of innovation.

Integration of Artificial Intelligence and Machine Learning:

The integration of artificial intelligence (AI) and machine learning (ML) capabilities is a notable trend in the O-RAN Near-RT RIC market. Near-RT RIC, empowered by AI and ML algorithms, enhances its ability to dynamically optimize RAN functions based on real-time data and network conditions. This trend reflects a strategic shift toward autonomous and self-optimizing networks, where intelligent controllers can adapt to changing environments, predict network behavior, and proactively address issues. The incorporation of AI and ML in Near-RT RIC is poised to play a key role in optimizing network performance, reducing operational costs, and ensuring a more resilient and responsive communication infrastructure.

Security and Trustworthiness in Near-RT RIC Deployments:

Security and trustworthiness have emerged as critical trends in the deployment of Near-RT RIC solutions. As these intelligent controllers become integral components of RANs, ensuring the security of communication networks becomes paramount. This trend involves the implementation of robust security measures, including encryption, authentication, and secure interfaces, to protect Near-RT RIC deployments from potential cyber threats and unauthorized access. Industry stakeholders are actively addressing security concerns to build trust in the reliability and resilience of Near-RT RIC solutions, fostering a secure foundation for the evolving landscape of intelligent and open RAN architectures.

Segmental Insights

Component Insights

xApp Framework for CXX segment dominated in the global O-RAN Near-Real-Time RAN Intelligent Controller market in 2023. The xApp Framework serves as a foundation for creating RAN applications, enabling developers to design, implement, and seamlessly integrate their functionalities into the O-RAN architecture. This dominance is attributed to the critical role of xApps in enhancing the intelligence and agility of RAN operations. By leveraging the xApp Framework, developers can build applications that contribute to dynamic resource allocation, intelligent network orchestration, and real-time optimization of RAN functions.

The xApp Framework's dominance is evident in its ability to facilitate innovation and the rapid introduction of new services within the O-RAN ecosystem. Developers across the globe prefer the xApp Framework for its support of multiple programming languages, allowing them to use the language best suited to their expertise and application requirements. The adaptability of the xApp Framework ensures that it remains at the forefront of the O-RAN Near-Real-Time RIC market, accommodating the evolving needs of operators, service providers, and the broader telecommunications industry.

xApp Framework promotes a collaborative and open ecosystem by fostering interoperability between different applications and components within the O-RAN architecture. This collaborative aspect aligns with the core principles of O-RAN, emphasizing vendor diversity and enabling a seamless integration of innovative solutions from various contributors. As a result, the xApp Framework not only dominates but also serves as a unifying force within the O-RAN Near-Real-Time RAN Intelligent Controller market, contributing to the realization of open, intelligent, and efficient RAN deployments globally.

Regional Insights

North America dominated the Global O-RAN Near-Real-Time RAN Intelligent Controller Market in 2023. The region is home to some of the world's leading telecommunications and technology companies that are at the forefront of O-RAN innovation. Major players based in North America have heavily invested in research and development, driving the advancement of intelligent RAN controllers. The United States, in particular, is a hub for technological innovation, with Silicon Valley serving as a global epicenter for cutting-edge developments in telecommunications, networking, and artificial intelligence.

The region has witnessed rapid and widespread adoption of 5G technology, creating a fertile ground for the deployment and utilization of O-RAN Near-Real-Time RAN Intelligent Controllers. As North American telecom operators aggressively roll out 5G networks to meet the escalating demand for high-speed, low-latency connectivity, the need for intelligent RAN controllers becomes paramount. Near-RT RIC is instrumental in optimizing the performance of 5G networks, aligning with the region's commitment to staying at the forefront of next-generation communication technologies. North America's regulatory environment fosters innovation and competition in the telecommunications sector. Policies that encourage open architectures and standards, such as those advocated by the Federal Communications Commission (FCC), align well with the principles of O-RAN. This regulatory support has provided a conducive landscape for the testing and deployment of O-RAN solutions, including Near-RT RIC, encouraging widespread adoption by network operators.

The region's leadership in the global O-RAN Near-Real-Time RAN Intelligent Controller market is further propelled by collaborative initiatives and industry alliances. North American companies actively participate in global standardization efforts, contributing to the development of open interfaces and interoperable solutions. This collaborative spirit fosters a vibrant ecosystem that accelerates the adoption of O-RAN principles.

Key Market Players

Nokia Corporation

Rakuten Mobile, Inc.

Samsung Electronics Co., Ltd.

Sterlite Technologies Limited

Telefonaktiebolaget LM Ericsson

IS-Wireless

Parallel Wireless, Inc.

VIAVI Solutions Inc.

HCL Technologies Limited

Casa Systems, Inc.

Report Scope:

In this report, the Global O-RAN Near-Real-Time RAN Intelligent Controller Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

O-RAN Near-Real-Time RAN Intelligent Controller Market, By Component:

    A1 Mediator Demo1 E2 Manager (E2M) E2 Terminator (E2T) Logging RIC Alarm System RIC Message Router (RMR) RNIB Routing Manager xApp Framework for CXX xApp Framework for Go xApp Framework for Python

O-RAN Near-Real-Time RAN Intelligent Controller Market, By Deployment:

    Centralized Distributed

O-RAN Near-Real-Time RAN Intelligent Controller Market, By Region:

    North America

United States

Canada

Mexico

    Europe

Germany

France

United Kingdom

Italy

Spain

    South America

Brazil

Argentina

Colombia

    Asia-Pacific

China

India

Japan

South Korea

Australia

    Middle East & Africa

Saudi Arabia

UAE

South Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global O-RAN Near-Real-Time RAN Intelligent Controller Market.

Available Customizations:

Global O-RAN Near-Real-Time RAN Intelligent Controller Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Baseline Methodology
  • 2.2. Key Industry Partners
  • 2.3. Major Association and Secondary Sources
  • 2.4. Forecasting Methodology
  • 2.5. Data Triangulation & Validation
  • 2.6. Assumptions and Limitations

3. Executive Summary

4. Impact of COVID-19 on Global O-RAN Near-Real-Time RAN Intelligent Controller Market

5. Voice of Customer

6. Global O-RAN Near-Real-Time RAN Intelligent Controller Market Overview

7. Global O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component (A1 Mediator, Demo1, E2 Manager (E2M), E2 Terminator (E2T), Logging, RIC Alarm System, RIC Message Router (RMR), RNIB, Routing Manager, xApp Framework for CXX, xApp Framework for Go, xApp Framework for Python)
    • 7.2.2. By Deployment (Centralized, Distributed)
    • 7.2.3. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 7.3. By Company (2023)
  • 7.4. Market Map

8. North America O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Deployment
    • 8.2.3. By Country
  • 8.3. North America: Country Analysis
    • 8.3.1. United States O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Deployment
    • 8.3.2. Canada O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Deployment
    • 8.3.3. Mexico O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Deployment

9. Europe O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Deployment
    • 9.2.3. By Country
  • 9.3. Europe: Country Analysis
    • 9.3.1. Germany O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Deployment
    • 9.3.2. France O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Deployment
    • 9.3.3. United Kingdom O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Deployment
    • 9.3.4. Italy O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Component
        • 9.3.4.2.2. By Deployment
    • 9.3.5. Spain O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Component
        • 9.3.5.2.2. By Deployment

10. South America O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Deployment
    • 10.2.3. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Deployment
    • 10.3.2. Colombia O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Deployment
    • 10.3.3. Argentina O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Deployment

11. Middle East & Africa O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Component
    • 11.2.2. By Deployment
    • 11.2.3. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Component
        • 11.3.1.2.2. By Deployment
    • 11.3.2. UAE O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Component
        • 11.3.2.2.2. By Deployment
    • 11.3.3. South Africa O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Component
        • 11.3.3.2.2. By Deployment

12. Asia Pacific O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook

  • 12.1. Market Size & Forecast
    • 12.1.1. By Value
  • 12.2. Market Share & Forecast
    • 12.2.1. By Component
    • 12.2.2. By Deployment
    • 12.2.3. By Country
  • 12.3. Asia Pacific: Country Analysis
    • 12.3.1. China O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 12.3.1.1. Market Size & Forecast
        • 12.3.1.1.1. By Value
      • 12.3.1.2. Market Share & Forecast
        • 12.3.1.2.1. By Component
        • 12.3.1.2.2. By Deployment
    • 12.3.2. India O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 12.3.2.1. Market Size & Forecast
        • 12.3.2.1.1. By Value
      • 12.3.2.2. Market Share & Forecast
        • 12.3.2.2.1. By Component
        • 12.3.2.2.2. By Deployment
    • 12.3.3. Japan O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 12.3.3.1. Market Size & Forecast
        • 12.3.3.1.1. By Value
      • 12.3.3.2. Market Share & Forecast
        • 12.3.3.2.1. By Component
        • 12.3.3.2.2. By Deployment
    • 12.3.4. South Korea O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 12.3.4.1. Market Size & Forecast
        • 12.3.4.1.1. By Value
      • 12.3.4.2. Market Share & Forecast
        • 12.3.4.2.1. By Component
        • 12.3.4.2.2. By Deployment
    • 12.3.5. Australia O-RAN Near-Real-Time RAN Intelligent Controller Market Outlook
      • 12.3.5.1. Market Size & Forecast
        • 12.3.5.1.1. By Value
      • 12.3.5.2. Market Share & Forecast
        • 12.3.5.2.1. By Component
        • 12.3.5.2.2. By Deployment

13. Market Dynamics

  • 13.1. Drivers
  • 13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

  • 15.1. Nokia Corporation
    • 15.1.1. Business Overview
    • 15.1.2. Key Revenue and Financials
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. Key Product/Services Offered
  • 15.2. Rakuten Mobile, Inc.
    • 15.2.1. Business Overview
    • 15.2.2. Key Revenue and Financials
    • 15.2.3. Recent Developments
    • 15.2.4. Key Personnel
    • 15.2.5. Key Product/Services Offered
  • 15.3. Samsung Electronics Co., Ltd.
    • 15.3.1. Business Overview
    • 15.3.2. Key Revenue and Financials
    • 15.3.3. Recent Developments
    • 15.3.4. Key Personnel
    • 15.3.5. Key Product/Services Offered
  • 15.4. Sterlite Technologies Limited
    • 15.4.1. Business Overview
    • 15.4.2. Key Revenue and Financials
    • 15.4.3. Recent Developments
    • 15.4.4. Key Personnel
    • 15.4.5. Key Product/Services Offered
  • 15.5. Telefonaktiebolaget LM Ericsson
    • 15.5.1. Business Overview
    • 15.5.2. Key Revenue and Financials
    • 15.5.3. Recent Developments
    • 15.5.4. Key Personnel
    • 15.5.5. Key Product/Services Offered
  • 15.6. IS-Wireless
    • 15.6.1. Business Overview
    • 15.6.2. Key Revenue and Financials
    • 15.6.3. Recent Developments
    • 15.6.4. Key Personnel
    • 15.6.5. Key Product/Services Offered
  • 15.7. Parallel Wireless, Inc.
    • 15.7.1. Business Overview
    • 15.7.2. Key Revenue and Financials
    • 15.7.3. Recent Developments
    • 15.7.4. Key Personnel
    • 15.7.5. Key Product/Services Offered
  • 15.8. VIAVI Solutions Inc.
    • 15.8.1. Business Overview
    • 15.8.2. Key Revenue and Financials
    • 15.8.3. Recent Developments
    • 15.8.4. Key Personnel
    • 15.8.5. Key Product/Services Offered
  • 15.9. HCL Technologies Limited
    • 15.9.1. Business Overview
    • 15.9.2. Key Revenue and Financials
    • 15.9.3. Recent Developments
    • 15.9.4. Key Personnel
    • 15.9.5. Key Product/Services Offered
  • 15.10.Casa Systems, Inc.
    • 15.10.1. Business Overview
    • 15.10.2. Key Revenue and Financials
    • 15.10.3. Recent Developments
    • 15.10.4. Key Personnel
    • 15.10.5. Key Product/Services Offered

16. Strategic Recommendations

17. About Us & Disclaimer