The Evolution Of SON With Cloud-Native Architecture

Forbes

10-07-2025

Apeksha Jain is a Global Expert in Architecting Distributed Applications, Engineering Leader in Cloud-Scale Systems.
Wireless networks have long faced the challenges of manually configuring, optimizing and maintaining thousands of base stations. This process is labor-intensive, economically inefficient and prone to errors. The inability to adapt in real time also makes it difficult to respond to issues like network congestion, meaning that base station faults go unresolved until manually identified.
To address these challenges, the self-organizing network (SON) was introduced into 3GPP specifications in Release 8 in 2009.
SON is a tool that provides self-healing and allows the network to detect and recover from failures on its own. This update enhanced operational efficiency through its automated functionalities, which include:
• Self-Configuration: SON automates the setup of key parameters, such as initial neighbors, physical cell identifier (PCI) and tracking area code (TAC) for newly deployed base stations, ensuring compatibility with neighboring stations to prevent network interference.
• Self-Optimization: SON can continuously monitor network performance and automatically adjust base station parameters to optimize resources, improve service quality and reduce interference.
• Self-Healing: With SON, the network can automatically detect and resolve base station faults before they impact the network or users, leading to faster recovery and reducing operational costs.
However, over the years, traditional SON architectures have faced several challenges, some of which can be overcome by using cloud-native SON. Let's explore those challenges, the role that cloud-native SON can play in addressing them and how to successfully implement cloud-native SON.
The Challenges With Traditional SON
Traditional embedded SON applications—also called distributed SON (D-SON)—deploy directly on network controllers. They enhance network management, but they also pose functional limitations in today's dynamic telecom landscape.
When operating in isolation on a network controller, SON only has visibility into the base stations connected to a network controller, lacking a global view of the network. This limits SON's ability to implement network-wide load balancing needed to improve the overall efficiency of the network. D-SON can only load balance the user traffic between the base stations connected to the same network controller, which can also result in conflicting configurations across the base stations.
As explained in an article on Telecoms.com, this type of SON architecture embedded within vendor-specific network controllers relies on proprietary interfaces. In multi-vendor environments, this design can make it difficult for SON functions to interoperate across different vendor equipment, which often leads to misconfiguration of neighboring base stations and inconsistent network behavior.
Additionally, maintaining this solution may be operationally inefficient due to slow feature rollouts and resource constraints.
Together, these limitations can prevent D-SON from leveraging advanced AI technology for predictive network configuration and management.
The Shift Toward Cloud-Native SON
Cloud-native SON is an architecture built on cloud infrastructure, typically delivered as a SaaS solution. It leverages the cloud's compute power and storage to process large volumes of network data in real time, enabling it to maintain a unified view of thousands of base stations across the network.
As Nokia points out, this architecture is intended to enable automation, agility and seamless integration with other cloud-native network functions. The SaaS model can also support rapid deployment, continuous updates and operational efficiency to make network management more flexible and adaptive.
Unlike traditional SON solutions, cloud-native SONs are developed by independent providers and built using standard APIs. A single SON application can, therefore, manage all base stations across the network and address interoperability issues between different vendor systems. With a holistic network view, cloud-native SON can prevent misconfigurations between neighboring base stations and support network-wide capabilities such as load balancing, improving overall performance and user experience.
The cloud infrastructure is intended to provide a foundation for the integration of AI into SON applications. As noted by TeckNexus, AI-enhanced SON capabilities include predictive fault detection, intelligent load balancing and proactive energy optimization.
This shift moves SON toward AI-supported decision-making, as it can offer more flexibility and scalability for emerging network requirements such as 5G.
Adopting Cloud-Native SON
While transitioning to cloud-native SON can offer substantial benefits, wireless operators need to be aware of the key challenges and navigate strategically to ensure a smooth transformation.
Many operators lack in-house expertise in cloud-native tools and frameworks, making it necessary to upskill existing teams or recruit new talent with relevant experience. Beyond technical skills, the adoption of cloud-native SON also requires a cultural shift toward fast-paced Agile- and DevOps-driven practices. This operational mindset is essential for unlocking the full potential of cloud-native systems.
Another major consideration is the integration of existing network controllers with cloud-native SON. Operators using traditional SON embedded in their network equipment often use proprietary interfaces. Moving to a cloud-native SON with a standard API interface requires a middleware layer in their network controllers, which can be a complex and resource-intensive task that requires careful planning and phased execution.
There may also be concerns about data sovereignty, cloud security and compliance when offloading SON operations to the cloud. To address these concerns, organizations can adopt region-specific data hosting, end-to-end encryption and strict access controls. Regulatory compliance can be improved through robust auditing, and hybrid or private cloud models can provide greater control over sensitive data.
By addressing these considerations in a timely and strategic manner, the operators can ensure the successful adoption of cloud-native SON.
Conclusion
As wireless infrastructure expands, there is a continuous push to accelerate SON adoption, streamline deployment and reduce operational costs, which is why cloud-native networks are gaining traction. Adopting cloud-native SON involves addressing key regulatory, technical and process challenges, but it can play a crucial role in the evolution toward AI-native networks.
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