Multi-G – Universal Neural Receiver enables receipt of multiple waveforms

Deep-dive on a universal neural receiver designed for 6G and Multi-G wireless networks, which addresses the limitations of traditional model-based signal processing. An AI-native physical layer utilizes reservoir computing to perform real-time deconvolution, allowing the system to adapt at the sub-millisecond speed of wireless interference. The system avoids the need for extensive offline training that often fails across different geographic environments. This approach simplifies the receiver by focusing online learning only on unknown variables, making it compatible with various waveforms like CP-OFDM and Zak-OTFS.