NVIDIA AI Aerial is an AI-native Radio Access Network (RAN) platform that uses GPU acceleration to close the Massive MIMO performance gap in wireless networks. Traditional RAN systems are compute-constrained, forcing algorithmic compromises that leave spectral efficiency far below theoretical limits. By shifting to a GPU-based, algorithms-first architecture, AI Aerial enables advanced workloads like ML-based beamforming (up to 1.62x throughput gain over classical zero-forcing), deep reinforcement learning link adaptation (1.3x gain at cell edge), and neural receivers. The platform also supports integrated sensing and communications (ISAC), cross-cell coordination, and dynamic allocation of spare GPU compute for edge AI inference during off-peak hours. SoftBank field trials demonstrated roughly 3x spectral efficiency over a conventional 4-layer baseline using this GPU-based AI-RAN platform.
