Frequency Transfer Learning for AI-aided Beam Management in cmWave Spectrum

This letter focuses on the AI-aided beam management (AI-BM) scheme design for FR3 centimeter-Wave (cmWave) spectrum. A spindle-like decoder-encoder neural network is proposed to conduct spatial prediction with reduced measurements. To facilitate the AI-BM deployment for multi-frequency scenarios in 6G, an efficient frequency transfer learning solution is further proposed based on the antenna array theory. Moreover, a fully 3GPP compliant real-time proof-of-concept (PoC) platform is developed to evaluate the proposed scheme. By experimental results, we validate the advanced performance and robustness of the proposed AI-BM scheme.