This technology is a deep learning platform that uses curriculum learning-based strategies to train neural networks for real-time optimization of beamforming, thus improving communication in 5G and wireless networks.
Current beamforming optimization methods rely on iterative algorithms that are computationally expensive and introduce significant latency. These approaches are too slow for real-time use in modern wireless systems such as 5G, which require rapid, adaptive responses to changing network conditions. The complexity of these algorithms limits their scalability and makes them impractical for widespread use. Addressing these shortcomings is critical to enabling fast, efficient, wireless communication in next-generation networks.
This technology uses artificial intelligence (AI) and machine learning approaches to train a neural network to compute optimal beamforming solutions in real time. This improves wireless signal direction, replacing slow, iterative, and complex methods with improved performance. With the AI model, this technology adapts to changing environments and outperforms current heuristic methods in multiple-input-single-output (MISO) and multiple-input-multiple-output (MIMO) systems, making it ideal for fast, reliable 5G and future communication networks.
Patent Pending (US20250165780)
IR CU24175
Licensing Contact: Greg Maskel
