Aira Technologies develops world’s first AI-based channel estimation and prediction xApp and is awarded Telecom Infrastructure Project "Silver Badge"
Press Releases
Apr 08, 2024
The world’s first vendor to deliver an xApp that utilizes cutting edge proprietary machine learning algorithms to dramatically improve channel estimation, prediction, and beam management, delivering significant throughput enhancement.
SARATOGA, Calif., April 8, 2024 /PRNewswire-PRWeb/ — Aira Technologies, a pioneer in the application of Artificial Intelligence (AI) and Machine Learning (ML) to radically improve wireless telecommunications, today announced that it has been awarded a Silver Badge from the Telecom Infrastructure Project (TIP), for delivering an AI-based High Fidelity MIMO Channel Estimation and Prediction application (UC2 xApp). The requirements of the UC2 xApp have been specified by the RAN Intelligence & Automation (RIA) subgroup of the TIP OpenRAN Project Group.
The TIP RIA subgroup is focused on bringing the benefits of Artificial Intelligence (AI), Machine Learning (ML), and data science technologies to the Open RAN ecosystem. In particular, AI/ML algorithms running as applications (xApps and rApps) on top of the RAN Intelligent Controller (RIC) platform can help operators improve network utilization and customer experience through automation.
The algorithms themselves are trained with actual network data and infer how to manage network resources optimally. In this way Mobile Network Operators (MNOs) are able to contain operational expenses, even as they scale their networks, leading to more competitive Total Cost of Ownership (TCO).
The RIA subgroup has developed advanced Use Cases including AI-based use cases for Radio Resource Management (RRM) and Self Organizing Network (SON) that will help improve network coverage, capacity, handover, and interference in an automated manner. Other AI-based use cases address the optimization of Massive MIMO system performance, thus increasing their spectral efficiency.
“The application of ML to wireless baseband processing is an industry first. The RAN Intelligence and Automation (RIA) subgroup of TIP has articulated an outstanding need for a near real-time application to perform better channel estimation to improve MU-MIMO performance,” said Anand Chandrasekher, co-Founder and CEO of Aira Technologies. “Aira’s xApp delivers against this need by providing high-fidelity beam management through improved channel estimation and prediction. We are proud of the recognition from the TIP organization and very pleased to be working with our TIP partners.”
“Radio Access Networks (RAN) operate in varied network conditions and radio environments. ML presents a natural framework to classify these conditions accurately and process the RAN signals optimally for each of these conditions,” said RaviKiran Gopalan, co-Founder and CTO of Aira. “We are seeing tremendous MU-MIMO throughput gains from our ML-based channel prediction xApp.”
The setup consisted of a VIAVI TM500 Network Tester emulating multiple UEs under varying channel conditions, as seen by a Foxconn (4T4R) RU. The RU was connected in an end-to-end fashion to the Aira DU, a Capgemini CU and a Capgemini Core. Aira defined a service model that passed data from the DU to the VMware RIC via the E2 interface. The Aira AI-based High Fidelity MIMO Channel Estimation and Prediction xApp ran atop the RIC. The function of this xApp was to estimate and predict the channel which was then compared to ground truth as established by the Realistic UE traffic generated by the VIAVI TM500. The output of the xApp is the prediction of channel evolution in-between S-slots, which results in improvements in RAN throughput and coverage.
“The TIP RIA OpenRAN subgroup is focused on driving and enabling the OpenRAN ecosystem to leverage AI/ML automation within the RAN domain to enhance the RAN performance. TIP has worked with leading MNOs and vendors to define RIC use cases and demonstrated them on RIC platforms over the past two years. One of the focus areas for TIP RIA is near-RT RIC applications that focus on improving MU-MIMO and maMIMO performance,” said Abdel Bagegni, TPM, TIP OpenRAN PG. “We are very excited to be working with our participants to unlock additional use case applications for near-RT control and optimization of open RAN networks.”
“Benchmarking and testing of RIC xApp performance under realistic channel conditions is crucial for gaining operator acceptance. We are very pleased to have supported Aira Technologies in achieving this important milestone,” added Stephen Hire, Vice President for Wireless Marketing and Partnerships at VIAVI Solutions.
About Aira Technologies Inc.
Aira Technologies, an AI software technology company, was founded in 2019 by wireless industry veterans including CEO Anand Chandrasekher (ex-Intel, ex-Qualcomm) and CTO Dr. Ravikiran Gopalan (ex-Bell Labs, ex-Qualcomm) and wireless researchers Dr. Pramod Viswanath (Professor, Princeton University) and Dr. Sreeram Kannan (Professor, University of Washington, Seattle). Aira’s vision is to use a data-driven, ML powered approach to radically re-imagine wireless design, deployment, and control to improve efficiency, and performance. Aira is laser focused on enabling the RAN of the future – a fully autonomous, self-learning RAN. Aira has assembled a team with a rare combination of 5G wireless technology and cutting-edge AI expertise. For more information, visit https://www.aira-technology.com.
CONTACT: Maureen Bradford, Aira Technologies, 1 833-689-3133, pr@triaza.com, https://www.aira-technology.com/
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SOURCE Aira Technologies