6G • RAN
On-Device Neural Beam Predictor
Recurrent Deep Learning Beam Direction Predictor on Handset
Lightweight temporal neural network running on the handset predicting which base station beam will be optimal several slots in advance.
Technical Explanation
Due to rapid user head or hand movements, line-of-sight sub-THz beams are frequently blocked before legacy feedback protocols can react. The on-device neural beam predictor runs a tiny recurrent neural network (such as an LSTM or GRU) on the handset sensor coprocessor. By analyzing past channel state metrics, device acceleration, and spatial trajectory, it predicts future beam quality 10-20 ms ahead, enabling proactive seamless beam handover with zero throughput drops.
Key Functions
- Predicts optimal sub-THz beam indices 10-20 milliseconds ahead of time
- Pre-empts beam blockage caused by body turning or obstacles
- Reduces continuous beam sweep power consumption on the mobile terminal
- Maintains sustained multi-gigabit connections during rapid walking or jogging
Specifications
3GPP TR 38.843 (AI for Beam Management), ITU-R M.2160
Interfaces
Handset IMU Sensor BusBaseband Beam EngineUu Control Channel
Related 6G Concepts
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