Aira Technologies showcases a new GenAI-based capability for securely querying, controlling and automating the Radio Access Network ushering in new possibilities for RAN automation
Aira Technologies a pioneer in the application of Machine Learning (ML) to radically improve wireless telecommunications, announced that it has developed a new capability, RANGPT, that enables observability, analysis, control and automation of the RAN using conversational language. These capabilities make RANGPT an indispensable tool to Mobile Network Operators (MNOs) who seek to develop deep insights on how to improve the performance of the RAN while optimizing network operations. Aira is demonstrating RANGPT at MWC 2024 in partnership with Tech Mahindra and VIAVI Solutions.
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With 5G, the increased complexity of mobile networks poses many operational challenges for MNOs as they try to balance performance, sustainability and economic efficiency. Mobile networks generate enormous amounts of data that operators know can be valuable in improving the design of networks, managing customer experience, lowering the cost of running the network, and even deploying new revenue-generating services. However, doing useful experiments with this data has been tedious and time consuming since it requires expertise and coordination between multiple teams such as wireless and data science groups.
“Quick experimentation is impossible and ideas get killed in the process. Aira addressed these challenges by creating RANGPT to provide a natural language interface to network data,” said Ravikiran Gopalan, co-founder and CTO of Aira Technologies. “With RANGPT, a wireless expert can analyze data, gain insights, iteratively experiment, and ultimately deploy code in a matter of hours – a process which previously would have taken months.”
“Aira is built on the fundamental premise that the application of ML to all layers of the RAN infrastructure stack can deliver breakthrough performance benefits to the operator community,” said Anand Chandrasekher, co-founder and CEO of Aira Technologies. “What we have achieved here showcases the extraordinary potential for ML in cutting-edge wireless applications, offering accessibility without compromising control or security. We look forward to ushering in the era of AI defined networking to make cellular networks significantly more efficient.”
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RANGPT is hosted in the cloud as part of Tech Mahindra NetOp utilizing its multi-vendor multi-domain features to access the emulated network provided by VIAVI.
“We look forward to partnering with Aira Technologies to bring the world’s first GenAI-based solution for automating and operating the Radio Access Network. As a strategic partner for telecom service providers, we are committed to helping our customers build and execute an AI-led Telco playbook. This solution represents a significant stride in harnessing the power of AI to revolutionize network planning, design, deployment, and operations. Our partnership with Aira technologies is an excellent testament of how Tech Mahindra is racing ahead with innovation to deliver groundbreaking solutions to our customers.”, said Manish Mangal, Global Business Head of 5G and Network Services, Tech Mahindra.
“The application of AI techniques to mobile networks opens the possibility for significant gains in network performance, efficiency and simplification for network operators,” added Stephen Hire, Vice President of Marketing and Partnerships, VIAVI. “Large-scale, accurate and realistic training data is fundamental to achieving these improved outcomes. VIAVI has worked closely with Aira Technologies to enable them to use VIAVI’s TeraVM RIC Test to provide large scale data sets for RANGPT.”
RANGPT allows MNOs to interact with the network through conversational queries, to gain insights on the state of the RAN by analyzing network data. The result of the analyses is rendered back to the user in any convenient form, including text, graphics, and charts. RANGPT retains the context of queries to allow for more sophistication in successive probing. The insights gained from such analyses help address performance issues and optimize drivers of MNO opex, including energy consumption. A sequence of RANGPT queries and control instructions can easily be stitched together to create RAN automation applications required to meet network opex reduction targets.
The utility also can be used for control of the RAN, allowing for manipulation of the actual underlying hardware to troubleshoot or isolate faults. Query and control features, coupled with the ability to generate software code as required, means that RANGPT can serve as an automatic code generator for new xApps and rApps.
RANGPT is built with security and privacy of MNO Key Performance Indicator (KPI) data in mind. The LLM used can be a proprietary capability, residing in a private cloud, so the MNO has full control of all the RANGPT modules.
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