AI for 5G Network Operations

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How is Artificial Intelligence making better 5G networks?

AI is upgrading 5G technology – in the network and on devices both. AI for 5G network operations is nothing but the application of AI in 5G wireless network and devices to allow seamless and efficient wireless communications and give new amazing experiences. There are several challenges in implementing wireless technology that is difficult to solve with legacy methods and can be solved with the utilization of powerful tool like AI. With 5G and AI everywhere, we expect to see much more reliable and resilient network than ever. However, it is still the talk of the town as how AI will make 5G a better network. AI will have a strong impact on multiple key areas of 5G network management namely simplified deployment, enhanced service quality, higher network efficiency, and upgraded network security. For instance, utilization of artificial intelligence to manage network traffic of 5G wireless networks and detect anomalies, identification of unusual usage of spectrum. Further AI can be deployed to interpret complex RF signals coming out of devices. Increased radio awareness facilitates new improvements such as enhanced performance of system, device experience, with better security. 

Streamlining 5G Network Operations with Artificial Intelligence

  • Planning and designing networks


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    Artificial Intelligence can help CSPs to enhance their network design for enabling better capacity and throughput prediction for short-term and long-term needs of their consumer base. Highly capable in working as a recommendation engine, AI capabilities are just more than enough to see traffic trends and behavioural flow of their consumers through AI-based analytics solutions and then better understand on how to optimize networks to give best Quality of Experience (QoE) to their users. 


  • Embrace AI-driven tools for service operations


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    From reporting of problems to responding to event and incident, AI-driven tools for network operations assist network engineers automate and streamline network activities and incident management. ‘AIOps’ is the next level of automation with intelligent 5G when cellular networks meet artificial intelligence and is being deployed in telecom industry aimed at empowering software tools to take quick actions and respond immediately enabling predictive maintenance with the utilization AI technology for any operational events / incidents, security issues – that also without the intervention of humans.  


  • Place AI at the heart of CAPEX agenda


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    With the deployment of 5G networks, operators’ network expenditure is anticipated to rise significantly over the years as they have to perform multiple iterations of testing with 5G network testing equipment & tools. While pricing pressure prevails, new concepts like private networks may challenge legacy value chain. As a solution to these challenges, operators are taking a smarter approach to plan their Capital Expenditure (CAPEX) and deliver better experience to consumers, satisfy regulators and drive enhancements in return on investments. Standardized AI based technology can deliver critical data with capabilities of deep learning and dynamic modelling in capex planning tools. According to a report from Ericsson, 48% of CSPs are on the stage of testing AI, focusing on how to reduce capex by this new-age technology. 


  • Analysing logs of data with AI


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    With 5G, millions of IoT devices are getting connected and data is generated in huge bulks from internal procedures, server logs, applications, network controllers and other equipment. Conventional method used to accumulate data in logs and not much of accessibility was there. In the wake of AI, the network management systems are now automated, can analyse data, get results and extract insights to enhance network performance on regular intervals thus reducing downtime. Additionally, the speed in which an activity is performed is faster than humans.


  • Automatically prioritising critical network traffic


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    Networks are now guaranteed with timely delivery of critical traffic as they are built with AI-enabled smart switching. The inception of COVID-19 drastically changed the network service demands and operational processes due to movement restrictions and work from home policies. AI will enable network with proactive and dynamic resource allocation to allocate resources in desired locations based on real-time demand unlike static resource allocation method used in existing networks till now. This can resolve the issue of sudden shift in traffic demands from major cities to small towns and rural areas straining RAN and backhaul network.


    Furthermore, Artificial Intelligence to manage network traffic of 5G wireless networks are used to forecast traffic and identify cell outages enabling network to amend new configurations. It can be done by switching off unoperative base stations or turn on self-healing functionalities of self-organizing networks (SON). AI will also optimise proactive handover required to manage critical emergency situations wherein patients are attended via video conferencing/voice communications and avoid network disruption or in case switching connections from one cell tower to another while care professionals are in the ambulance on their way to hospitals.


  • AI increases flexibility of cloud-enabled networks


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    CSPs are under pressure to curb operational and capital costs as they accelerate 5G wireless network rollouts. Technologies like Artificial Intelligence and Machine Learning are gaining traction in the network management field and assisting operators to manage 5G networks. Initially, reluctant to place their data on public clouds, operators have started optimising network through AI algorithms on public cloud due to its multiple key benefits. Due to the increase in complexity of 5G architecture, use of AI is certainly becoming a prerequisite to manage and optimise such network.


    It is not only about the complexity of the architecture but also, addition of 5G on top of the layer stack comprising previous cellular technologies 2G, 3G, 4G. Moreover, modern use cases and abilities such as network slicing adds on to its intricacy. This is something humans cannot perform efficiently and require huge manpower which results in additional costs for CSPs. According to a survey conducted from 50 CSPs, 56% of CSPs come across data quality issues, 77% struggle with data storage and accumulation, and only 35% of them agreed to embrace AI to deploy intelligent ‘data capture’ methods. Analysing this study, it can be said that CSPs need to associate with AI vendors to assist them in reducing risks and up-front investments while providing top-notch data security and user experience. Implementation of AI-as-a-service (AAAS) approach can ensure flexibility and operators can pay based on what they consumed and get customised AI solutions from service providers to detect faults and auto-resolution addressal without human involvement.

 Employing AI to improve 5G mobile networks

Innovative AI solutions are being leveraged to enhance the network performance and provide best connectivity. Here are some examples of operators utilising AI to enhance 5G wireless networks:

  • China Mobile is utilising AI technology to isolate network anomalies and bandwidth demand where the data capture is originated from the RIC (RAN Intelligent Controller).

  • Mobile network operators are using VMware’s Uhana to detect RAN anomalies. Signal strength is determined, and radio sessions are managed in real-time applying eNodeB trace data. In addition, AI can analyse impact on customer due to cell site after detecting RAN anomalies.

  • Ciena, a telecom company is implementing AI to resolve signal impairments in layer zero, one and two i.e., optical and ethernet. AI-engine has the capability to drive decision input and automate manual tasks executed by skilled engineers.

Conclusion - 5G and AI are two of the most disruptive technologies 

In the world of new technologies, 5G and AI everywhere, are two technologies expected to change the entire ecosystem. The deadly combination of 5G and AI on one platform will lead to incredible new opportunities with a totally new point of view. The cutting-edge AI and 5G technologies will help creating an environment where data-driven algorithms control cloud-enabled processes, devices to give an enthralling experience to its consumers. And, AI will play a critical role in enhancing 5G wireless networks to give excellent Quality of Experience 24X7.  

Building and managing network is a constant process for mobile network operators. Multiple components and several new-age technologies added into the networks like 5G increases its complexity and puts several challenges on operators. To address such operators’ concerns, operators are partnering with AI solution providers to solve and reduce their network management costs. The power of combining 5G and AI will interpret complex datasets faster with more accuracy than humans, recommend engines to customize offerings based on user preferences. Clubbing 5G and AI technologies can give new 5G and AI use cases used in different industry verticals to improve efficiency. Data-driven techniques embedded in networks via AI will help operators automate their network operations and ensure flexibility, agility, service assurance, enhance subscriber experience. As AI is being adopted by CSPs around the world, it is expected to scale 5G network deployment in the years to come and enable wider range of services to users and get significant returns on investment.