With 5G driven applications coming into play, networks will experience improved speed, consistency, reliability and capacity
With an increase in smartphone penetration, democratisation of internet, HD video consumption and use of sophisticated technologies like AR and VR, massive amounts of data constantly hit a mobile network today. According to the Ericsson Mobility Report, June 2019 edition, data traffic per smartphone per month in South East Asia and Oceania will grow from 3.6GB to 17GB at a compounded annual growth rate of 29%. The report also predicts that the total mobile data traffic per month in the region is expected to grow 7 times from 2.3EB in 2018 to 16EB by 2024. With 5G and rapid expansion of IoT devices, data traffic will only grow further, prompting legacy networks to evolve into dynamic ones that are able to react in real-time to increased demands, problems and shifts in traffic.
Data deluge with 5G
The Ericsson Mobility report highlights that the total mobile traffic is expected to reach 136EB/month by the end of 2024. In the same time period, the number of cellular IoT connections is forecasted to reach 4.1 billion. As a result, network congestion will increase as service providers will handle multiple technologies such as 4G, 5G and IoT in tandem. Therefore, it is no wonder that service providers are gearing up to deploy artificial intelligence and machine learning to manage the complexity and optimise system performance. With 5G driven applications coming into play, networks will experience improved speed, consistency, reliability and capacity. To manage these factors, there will be a demand for faster, more responsive, available-on-demand networks that will be possible only through AI and machine learning deployment. Critical areas where service providers are already seeing value and return from AI are in building new revenue opportunities and enjoying operational cost savings. As they scale up their transformation, the benefits of automation and AI solutions deployment in networks become more evident.
Transforming to networks of tomorrow
According to an Ericsson, whitepaper on employing AI techniques, 91 per cent of service providers in Southeast Asia, India and Oceania want more AI in their network as they believe it will serve as an essential component for handling the increased traffic and other complexities. One of the foremost advantages of using machine learning in networks is that it will analyse raw data and will be able to yield further insights. By building cognitive and predictive AI algorithms, operators will be able to effectively manage network traffic and ensure network performance has minimal to zero impact with additional devices. AI enabled networks will employ advanced data analytics that will make systems smart, adaptive, self-aware, proactive and prescriptive. Ultimately, increasing use of AI in managing networks will play a key role in reducing associated operating costs and in addressing many of the barriers that service providers have indicated are preventing insights from data being acted upon.
The end consumers immensely stand to gain from improved network capabilities as well. For instance, 4K video has seen unprecedented rise in popularity among viewers who now want to experience the same level of detail and quality on the go. On 5G networks, AI and automation will help predict lags in service experiences and automate fixes, allowing consumers to enjoy a seamless 4K consumption. Leveraging on its developments in Artificial Intelligence (AI) and automation, Ericsson recently announced that it will support Airtel in India to proactively address network complexity and boost user experience. Combining deep domain expertise with advanced technologies like AI and automation, Ericsson managed services provides the performance, reliability, and flexibility to meet the dynamic needs of consumers and enterprises as well as intelligently monitoring and managing networks to drive operational efficiencies.
Given the increasing complexity and scale of data volumes that 5G will bring in, manual operations by human workers will need to be augmented .The good news is that operators have already started taking steps towards AI application and enhancing network performance to maximise end customer satisfaction. In order to provide a rich and seamless experience for both industrial partners and end consumers, it is important to speed up adoption of AI, automation and machine learning. It will help service providers to operate in a resilient and secure manner and take the mobile network to a new level of innovation for the benefit of industry and society.[…]