Adaptive Predistortion via Dual-Objective Optimization for Power Amplifier Linearization in the Baseband or RF Domain [Feature]
Abstract
Wideband transmission in current Wi-Fi 7 (IEEE 802.11be-evolution) and 5 G cellular communication systems has enabled significantly higher throughput in the 6-GHz band (5.925–7.125 GHz) worldwide. However, the use of wider bandwidths introduces several critical challenges for both Wi-Fi and 5 G networks. One of the most important challenges is maintaining high energy efficiency under wideband operation. To achieve high energy efficiency, power amplifiers (PAs) should operate in or near saturation, where nonlinear distortion is introduced and degrades transmitter performance. In this article, dynamic compensation techniques based on digital and RF predistortion are investigated to mitigate power-amplifier (PA) nonlinearity in broadband wireless transmitters. The work addresses key challenges in Wi-Fi 7 and 5G systems, including wide transmission bandwidths, high peak-to-average power ratios, and temperaturedependent PA behavior. A derivative-free adaptive algorithm with dual-objective optimization is developed to track and compensate for temperature-induced PA variations using either digital predistortion (DPD) or RF predistortion (RFPD). In additions, a metalearning framework is incorporated to enable rapid convergence across multiple operating environments. Finally, circuit- and sys-tem-level design considerations are presented to facilitate practical and energy-efficient implementations.