DeepSig Achieves Industry’s First AI-Native 5G Call
ARLINGTON, Va.–(BUSINESS WIRE)–DeepSig—experts in artificial intelligence (AI) and machine learning (ML) for wireless communications—today announced it completed the world’s first AI-Native 5G over-the-air call using OmniPHY-5G Neural Baseband. Featuring a commercial 5G handset and 5G standalone (SA) network to data services on the public internet, this major industry milestone proves the benefits of AI-Native wireless systems for 4G, 5G and 6G. The call was achieved in DeepSig’s Wireless AI Innovation Lab.
“This industry-first AI-Native 5G over-the-air call is a major milestone in using AI and ML to transform mobile networks and the user experiences they provide.”
AI and ML enable 5G networks to be predictive and proactive, including intelligent base stations that make decisions for themselves. This improves the efficiency, latency, and reliability of network applications. ML within the RAN minimizes power consumption, leverages channel information to support improved connections and enables full use of Massive MIMO systems.
DeepSig’s patented AI ML software significantly enhances 5G baseband performance at lower costs compared to traditional methods used in mobile networks today. Importantly, DeepSig replaced specific radio receiver algorithms within a 5G vRAN distributed unit (DU) with an AI neural network trained “natively” from actual radio environments. This completes over-the-air calls from commercial user equipment (UE) through the radio unit (RU) connected to the AI-enhanced DU, a standard central unit (CU) and 5G core.
“This industry-first AI-Native 5G over-the-air call is a major milestone using AI and ML to transform mobile networks and user experiences,” said James Shea, DeepSig CEO. “AI-Native 5G enables networks to work smarter and continually improve, using less energy and providing faster, more reliable connections. DeepSig’s pioneering work on AI-Native 5G sets the stage for 6G standards to make AI/ ML a fundamental part of tomorrow’s networks.
