
How Can AI Help in Network Planning?

For any CSP (Communication Service Provider), network planning is a hassle. There are several processes under the category of network planning that need to be completed at regular intervals. For example, a CSP has to continuously check whether the telecommunication network is meeting the demands of the client or not. To ensure high service availability, CSPs have to take care of network planning. Enterprises also have to spend some time on network synthesis and network realization to ensure the better performance of their networks. Network planning is an issue as the latest network technologies are more complex. The use of AI in network planning is considered the right solution. Read on to find out how AI helps in network planning.
Network planning is closely related to network design. With network planning and design, the requirements of clients and subscribers are met. Several processes involved in network planning and design are as follows:
Besides the aforementioned tasks, there are many small tasks under the bracket of network planning. To ensure the high service reliability of the network, these processes need to be completed on time. Network planning is a continual process that goes on until the network is in use. Let us know the challenges that led to the need for AI in network planning.
Why is there a need for automation in network planning? Several challenges have appeared in recent years for network planning. Network planning challenges in 2022 are as follows:
As you can see, there are many challenges for CSPs and enterprises in network planning. The recent innovations in 5G technology have offered speed, reliability, and scalability. However, there are bigger challenges when it comes to maintaining the service availability of 5G networks. That is why CSPs and enterprises are looking towards AI solutions for network planning and designing.
You must have heard about the pros of AI data analytics monitoring tools. Similarly, an AI-based solution for network planning collects calibration and network data continuously. Based on available data, network planning is conducted automatically. With AI-based solutions, network planning is conducted to meet the demands of clients and subscribers. AI-based solutions use the real-world measurement data to:
• Predictive analytics models automatically determine the best-fit network topology and design based on user requirements.
• AI-based solutions can help a network adapt to different deployment environments.
• Radio network modelling becomes simpler with AI-based solutions.
• CSPs can improve their coverage and service reliability with AI-based solutions. CSPs will have better control of their networks with AI-based solutions.
• With AI, CSPs can achieve zero-touch network planning and service management. They can create network plans that are based on the needs of the client and not on any hyperbolic data set.
If you decide to manually calibrate and plan your network, you need to be accurate. If you fail to get the right network plan, you have to begin again. In doing so, network planning costs will go up drastically. It is only human to make mistakes, and CSPs cannot afford to design complex network topologies repeatedly. It is where AI-led solutions can find the best possible network design in no time. An AI-based solution will also minimize the chances of future problems in the network. There are many AI-based technologies for improving the performance of a network. Among them, AIOps (Artificial Intelligence for IT Operations) is a beneficial technology for network planning in 2022.
AIOps can aggregate network data from numerous sources. Based on the available network data, network planning activities can be completed. You don’t have to ask the clients for issues within the deployed network. With the best AIOps products and tools, you can identify network issues remotely via smart monitoring. Use AIOps for network planning right away!
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