Enhancing Spectral and Energy Efficiency in Wireless Transmitters: From Baseband I/Q Modulation and RF Power Amplifiers to AI-Assisted Linearization

#communication #learning #linearity #mobile-communication #baseband #bandwidth #mobile-communications #nonlinear-distortion #Learning #internet #Edge #AI

This lecture will introduce the fundamental challenges in modern wireless transmitters, from spectrally shaped baseband I/Q modulation to RF power amplification and the potential for nonlinear distortion and spectral regrowth caused by power amplifiers (PAs). It will explain how RF predistortion (RFPD) compensates for PA nonlinearities to improve transmitter linearity, reduce spectral regrowth, and enhance spectral and energy efficiency. The lecture will also explore how meta-learning can enable rapid adaptation of predistortion coefficients to changing operating conditions, including temperature, signal bandwidth, and PA variations. Tailored to students’ technical backgrounds, the presentation will emphasize practical applications in Wi-Fi and mobile communications, emerging wireless technologies, and promising directions for future research.