Maximize Spectral Efficiency with AI-Native RAN and NVIDIA AI Aerial | NVIDIA Technical Blog

This post details how NVIDIA AI Aerial leverages GPU acceleration for AI-native RAN architectures to overcome traditional compute constraints. It highlights the benefits for Layer 1 and Layer 2 models, specifically for massive MIMO scenarios. The post quantifies gains in AI-based beamforming (up to 1.62x throughput) and DRL-based link adaptation (1.3x throughput improvement over OLLA) compared to CPU-based methods. It emphasizes the practical deployment of large models and low-latency inference, and discusses the platform's support for scalable, software-defined RAN evolution, cross-cell coordination, integrated sensing and communication, and monetization of GPU resources.