The story of artificial intelligence, or AI, is one that spans decades and multiple industries. AI enables a myriad of potential applications that will transform the way we live and work. In the telecommunications industry, we are already seeing AI’s impact and a future where AI enables the automation, orchestration and optimization of networks and services.
The ultimate goal of technological progress is to make life easier and safer. In the communications sector, AI’s predictive and generative powers enable users throughout a network ecosystem to streamline operations, reduce costs, minimize service issues and improve the delivery of services to end customers. AI ensures that as the network grows, it can adapt and expand to new consumer needs and business requirements. This will give rise to complex, demanding and ultra-low-latency applications ranging from smart cities and autonomous driving to Industrial IoT and remote surgery.
Digital Twin’s Predictive Power
AI-powered “Digital Twin” technology enables new predictive capabilities that help fortify networks. By creating a virtual model of a network in the lab, service providers can more quickly and effectively manage network behaviours and disruptions. Because they have seen it before, they can take their learning’s from the lab to the field. These digital twins play a pivotal role in advancing network design, reliability and performance. They are an invaluable tool for identifying network issues before they arise, and enable timely troubleshooting of operational challenges, once the network is deployed and operational.
Digital Twin technology ensures reliable connectivity during mass gatherings. Sporting events, celebrations and other large-scale occasions can easily overwhelm a network – potentially cutting off the communications needed to reunite families in a large crowd, provide medical services or simply share experiences of the day online. AI models help operators understand potential outcomes and equip them to optimize the network and respond to different scenarios.
AI technology, can also predict how natural disasters might disrupt communication and emergency services. Network operators can leverage these models to design more resilient networks, respond to issues and keep lines connected during a disaster, as well as accelerate restoration of critical services afterwards. This ultimately helps mitigate the repercussions of natural disasters on businesses and helps save human lives.
AI-based solutions can also help the transition to Open RAN technology which is critical to securing the telecommunications supply chain. Rather than a controlled network stack from a single vendor, Open RAN networks consists of highly diverse, disaggregated hardware and software components from multiple vendors.
The inherent openness and flexibility introduced by Open RAN also bring complexities – from interoperability and integration challenges to the imperative to match the performance and resiliency of traditional single-vendor-based radio access networks. Digital Twin technology emulates in the lab the intricate network traffic patterns and behaviors characters of complex 5G, O-RAN and anticipated 6G networks. Network operators can virtually build an O-RAN network alongside a digital representation of their existing network to see how they will work together – all before the first component is added. VIAVI has taken on certifying, benchmarking, optimizing and verifying all interoperability use cases and interfaces associated with Open RAN technology. In addition, we develop and verify the RAN Intelligent Controller (RIC), a crucial element responsible for automatically and intelligently allocating resources within the network. The security testing, network automation, orchestration and optimization we perform often leverage advanced AI/ML techniques to enhance the efficiency, automation and security of Open RAN systems.
A Future Shaped by Telco AI
In the ever-evolving landscape of telecommunications, AI will play a pivotal role in shaping a more secure, efficient and resilient network. Like many significant technological advancements that have come before it, AI necessitates a discussion of regulations and guidelines to safeguard its operation and address its direct and indirect consequences. But no two AI technologies are equivalent, and each carry different risks, impacts and implications. Low-risk, high-value AI systems represent a new frontier in enhancing network security, resiliency and efficiency. The regulatory landscape surrounding AI must find the balance between innovation, security and public interests.
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