The concept of the autonomous network was launched with an aim to deliver hyper-automated digital services and operations across several businesses. It was also introduced by the telecom industry to define a better-connected future especially when artificial intelligence (AI) capabilities are incorporated at the network element (NE), and cloud layers. So now let us see how autonomous networks will transform from concept to reality with Reliable Mobile Network Monitoring Tools, Mobile Network Drive Test Tools, Mobile Network Testing Tools and Reliable RF drive test tools & equipment, RF tester software app & network LTE 4g tester.
With the ongoing adoption of next-generation technologies such as 5G in several industry verticals, today’s society is quickly approaching an intelligent world with many opportunities such as all things will be connected, almost everything will detect thereby making the world intelligent. For this, customer expectations will be high, and MNOs will try to meet their expectations by delivering increasingly digitized and diversified services. So, in this context, network operators would consider ways to manage the network more easily. Here comes the autonomous network!
An autonomous network is a type of network that can run based on the purpose determined by an operator’s desired business outcomes. The autonomous network is adaptive, agile, and programmable, able to configure, monitor, and maintain itself independently with self-optimization capabilities. These networks can adapt to the operator’s environment and learn from data by leveraging Artificial Intelligence (AI) and machine learning, which enables the businesses’ operation of the network and runs with minimum investment and without human involvement.
Therefore, the assumption says the concept of autonomous networks (self-organizing, self-healing, and self-optimizing) can become a reality by integrating AI capabilities. Let’s discuss the status of this integration.
AI (Artificial Intelligence) in Networks
Generally, AI is used to re-develop the network management system (NMS), but it shows limited progress in this area. For instance, Tier-1 vendors are working actively in this area, but progress is slow due to their complex NMS systems.
The network can be controlled dynamically and managed automatically, and for this, you need to build a digital twin of a network through an intelligent management and control system. And the key benefits of AI in autonomous networks are automatic deployment, prevention and prediction, pre-event simulation, post-event verification, and proactive optimization.
AI in Network Elements (NEs)
The introduction of AI in Network Elements is useful in creating digitally intelligent NEs. Small vendors are introducing AI in specific use cases, but Tier-1s are leading this race when it comes to AI in Network Elements (NEs). Thus, the entire network along with NE is served with attributes such as more processing, extra precise insights, and inference execution.
Artificial Intelligence (AI) in the Cloud
In the context of network AI in the cloud, which means the training and model services are provided on the cloud. Though Cloud plays an excellent role in AI, hence good progress occurring in this area – the software systems and AI models on networks will be continuously upgraded to boost autonomous driving capabilities once progress is made in this layer, resulting smarter network.
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Conclusion
In the coming years, telecom operators are expected to switch to the autonomous networks era, and for creating intelligent connectivity within reach – the concept of autonomous networks initiative is becoming reality not only for network architectures but also for operation and business models. The results you can get from autonomous networks are optimization of the production cost structure and enhances business agility of digital services and these will be possible if your network connectivity is stable.
4G/5G network monitoring and testing play a main role – RantCell is one of the most reliable network measurement tools that provide QoE to end users. Its SaaS-based feature and cost-effective solutions will not only help the operators to check the network connectivity remotely but also save them money as compared to traditional network monitoring tester.
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