Emerging technologies like AI and ML are key to optimising networks and managing related costs, says Mikko Lavanti, senior VP of mobile networks for Nokia MEA.
Nokia is a founding member of the AI-RAN alliance, which was launched at the GSMA Mobile World Congress in Barcelona and aims to advance RAN (adio access network) technology by integrating AI into cellular networks, leveraging 5G and 6G.
AI-powered network optimisation refers to the use of AI and ML algorithms to enhance network performance, reliability, and efficiency. AI is used to monitor network performance and predict potential failures, which allows for proactive repairs.
Lavanti explains: “This involves analysing vast amounts of data in real time to predict, identify, and resolve issues before they impact users. It also includes automating tasks such as resource allocation, traffic management, and fault detection to maximise the network's overall capacity and responsiveness.”
AI algorithms can also dynamically allocate bandwidth and resources to ensure consistent quality of service, as well as save energy, adds Lavanti.
“By analysing usage patterns, AI can reduce energy consumption in underutilised areas of the network. AI also supports self-optimising networks enabling them to autonomously adjust configurations for optimal performance based on real-time conditions and can identify and mitigate cyber security threats in real time, reducing vulnerability,” he continues.
Smart spending
Smart capex (capital expenditure) refers to the use of AI and big data analytics to optimise capital expenditures in network infrastructure.
According to Lavanti, it enables service providers to make data-driven decisions about where and when to invest in network upgrades, expansions, or new technologies, ensuring maximum ROI and alignment with user demand trends.
“Smart capex relies on the insights generated by AI-powered network optimisation to allocate resources effectively. For instance, AI can predict areas with increasing traffic demands, guiding targeted investments. Optimised networks reduce operational costs, freeing up budget for strategic capex and by integrating AI, smart capex ensures investments align with both current and future requirements, avoiding over- or under-provisioning.”
5G and 6G support
Nokia adds that AI-powered network optimisation is critical for leveraging 5G and preparing for 6G because it addresses the unique challenges and opportunities of these advanced communication technologies.
“5G networks are far more complex than their predecessors, with features like network slicing, ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). AI enables operators to manage this complexity through dynamic resource allocation and real-time adaptation. AI also assists with power optimisation and sustainability planning therefore enhancing energy efficiency,” says Lavanti.
The company recommends a phased approach to AI-powered network optimisation, starting with pilot projects to demonstrate ROI and scalability.
It must also be integrated holistically, ensuring that AI systems work seamlessly with existing network infrastructure and tools.
“Build a team skilled in AI, machine learning, and telecommunications and partner with technology leaders for cutting-edge solutions and guidance. Finally, continuously evaluate performance to refine AI models based on new data,” Lavanti adds.
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