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.
Understanding 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:
- Determining the perfect network topology based on the client’s requirements. While designing the topology, it is decided where to place different network components. The costs of the transmission and setting up a network topology are also decided during network planning.
- Network planning includes the placement of concentrators and switches. Under network planning, the optimum connection matrix and GOS (Grade of Service) are also decided.
- Based on the size of network components and GOS, a routing plan is created under network planning.
- To ensure service reliability, capacity requirements are analysed and met under network planning. Forecasts are also made during network planning and designing. The expected traffic and load capacity of a network are predicted by the network managers.
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.
Challenges in network planning in 2022
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 the number of network vendors and consumers is increasing, different planning scenarios are being developed. As a result, it can be a challenge to choose the right planning scenario.
- Due to the rise of digital transformation services and solutions, many subscribers have shifted to a 5G network. Network planning is harder for any radio access network, and there is a need for automation.
- CSPs are now using MIMO (Multiple-Input and Multiple-Output) technique to meet the demands of the clients. With MIMO, CSPs can achieve the maximum range for distributed networks. MIMO management needs some help from automation technologies.
- Gone are the days when networks were only deployed via a physical infrastructure. Nowadays, networks can be deployed easily via a cloud platform. The demand for virtual desktop infrastructure solutions has also rocketed due to the recent COVID scenario. As a result, there is a need for automation for conducting network planning activities remotely.
- Network slicing is now more common than ever with the introduction of 5G. With network slices, many virtual networks can be created over a single physical infrastructure. However, as more and more slices are created in the network, network planning becomes harder. AI is needed to manage the network slices centrally and effectively.
- As the number of subscribers is increasing, CSPs have to rethink their network deployment and configuration practices. They cannot visit each touchpoint for manual configuration or deployment. There is a need for zero-touch network planning and service management at present. Only AI-based solutions have the power to implement zero-touch service management for CSPs.
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.
Pros of AI in network planning
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.
Role of AIOps in network planning
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!