Why India needs smart grids for a 5G future



Reducing complexity enables more transparent digital experiences at the edge

As new use cases continue to evolve that allow CSPs to better monetize their 5G investments, networks must become increasingly dynamic and agile to better serve an increasingly on-demand market. Training the workforce on every aspect of the network and finding enough network engineers to manage and maintain it will be a huge challenge. In addition, this approach significantly increases the inflated operational budgets that CSPs have constantly tried to reduce. A move towards network autonomy, driven by data-driven artificial intelligence (AI) and machine learning, will help alleviate these new challenges.

Data-driven automation can accurately predict network faults, detect them in real time, diagnose and recover quickly. These networks can also self-configure, self-optimize and self-repair.

CSPs can take advantage of the massive data sets that their existing systems generate and use it to train machine learning algorithms, potentially enabling them to build a fully automated and self-sustaining network. It will then operate with little or no human intervention and will configure, monitor and maintain itself independently.

CSPs need to advance AI and cloud technologies to simplify network operations and improve efficiency.

With software-driven networks, all that CSPs will need is to create 5G network slices for each use case of a customer segment, then let the automated network do its job: design, plan, provision. , monitor and even maintain the network. And if you think we are talking about the future, remember that future is now!


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