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Handset Phase Noise Mitigation Algorithm

Deep Learning Phase Noise Compensation for Sub-THz Mobile Receivers

Digital signal processing algorithm using recurrent neural networks to track and cancel severe carrier phase jitter in sub-THz handsets.

Technical Explanation

When mobile handsets receive sub-THz signals, oscillator phase noise causes Common Phase Error (CPE) and Inter-Carrier Interference (ICI) that smears constellations. Conventional pilot symbols consume too much bandwidth to track high-frequency phase noise. The handset deep learning phase noise compensation algorithm continuously models oscillator random-walk phase trajectories using neural network tracking, allowing smartphones to clean constellation points and demodulate multi-gigabit streams cleanly.

Key Functions

  • Cancels Common Phase Error (CPE) and Inter-Carrier Interference (ICI) in real-time
  • Reduces required phase tracking reference signal (PTRS) pilot overhead by 70%
  • Recovers clean constellation points for 64-QAM and 256-QAM in sub-THz bands
  • Executes with sub-microsecond latency on handset digital baseband hardware
Specifications
3GPP TR 38.807 Sub-THz Feasibility, IEEE Trans. Wireless Communications
Interfaces
Digital Baseband DemodulatorPTRS Channel Estimator

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