CATEGORY
Radio Access Networks
Radio Access Networks market size is anticipated to grow from $13.75 billion in 2023 to $19.09 billion by 2027, at a CAGR rate of 8 to 9.5 percent during the forecast period
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Schedule a DemoRadio Access Networks market report transcript
Radio Access Networks Global Market Outlook
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RAN market size is anticipated to grow from $13.75 billion in 2023 to $19.09 billion by 2027, at a CAGR rate of 8 to 9.5 percent during the forecast period
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The 5G RAN market is expected to grow by over 11 percent per annum over the next three years (2023 to 2025)
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RAN market is expected to grow in the coming years, driven by factors, such as the increasing demand for high-speed internet and mobile connectivity, the growing adoption of 5G technology, and the rising trend of virtualization and cloud-based RAN solutions
Radio Access Networks: Drivers & Constraints
Drivers
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Increasing demand for high-speed mobile broadband: With the explosion of mobile data traffic, there is a growing need for faster and more reliable mobile broadband networks. This is driving the development of new RAN technologies, such as 5G, to provide faster data transfer rates, lower latency, and higher capacity.
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Proliferation of connected devices: The increasing use of connected devices, such as smart home appliances and wearables, is driving the need for RANs that can support a large number of connected devices. This is leading to the development of new RAN technologies that can handle massive machine-type communications (MTC) and the Internet of Things (IoT).
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Government initiatives and regulations: Governments and regulators are also driving the growth of RANs through initiatives such as spectrum auctions, which enable operators to acquire the frequencies needed for new services, and regulations that encourage the deployment of new network infrastructure in rural and remote areas.
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Shift towards cloud-based and virtualized RAN: The adoption of cloud-based and virtualized RANs is gaining momentum as operators seek to reduce their capital and operating expenses while improving network performance. This shift is driving the development of new RAN architectures that are software-defined and more flexible.
Constraints
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Limited spectrum availability: Radio frequencies used for wireless communication are a limited resource and are regulated by government bodies. The amount of available spectrum can be a constraint for RAN deployments, as it can limit the amount of data that can be transmitted over a network.
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High cost of deployment: Building and maintaining RANs can be expensive, as it involves installing equipment, laying cables, and setting up network infrastructure. The cost of deployment can be a significant constraint, particularly for smaller network operators.
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Interference: Interference can occur when multiple wireless networks operate in the same frequency band. This can cause problems with signal quality and can impact the reliability of the network.
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Security: RANs are vulnerable to cyber attacks, which can compromise the privacy and security of user data. Ensuring the security of RANs is a critical constraint that must be addressed to ensure the safety and privacy of network users.
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Environmental factors: RANs can be impacted by environmental factors such as weather, topography, and vegetation. This can affect signal quality and coverage, particularly in remote areas.
Sourcing Models: Radio Access Networks
Single vendor
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By engaging with a single vendor regionally, buyers will decrease their operational complexity and cost. However, adoption of single vendor model is low in RAN.
Bi-vendor model
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This model is also prevalent among the buyers for RAN. In a bi-vendor regional model, one service provider will function as a primary and the other as a secondary, who is predominantly used as a fail safe or back up in case a network outage occurs with the primary.
Multi-vendor model
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Engaging with more than two vendors is more prevalent in RAN.
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Multi-vendor model offers buyers with top quality coverage and services. Operational complexity and cost are comparatively increased in this model.
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