Artificial intelligence for satellite communication and non-terrestrial networks: A survey
This paper surveys the application and development of Artificial Intelligence (AI) in Satellite
Communication (SatCom) and Non-Terrestrial Networks (NTN). We first present a …
Communication (SatCom) and Non-Terrestrial Networks (NTN). We first present a …
Digital predistortion of RF power amplifiers with phase-gated recurrent neural networks
In this article, we present a novel recurrent neural network (RNN)-based behavioral model to
linearize radio frequency (RF) power amplifiers (PAs) under wideband excitations. Based on …
linearize radio frequency (RF) power amplifiers (PAs) under wideband excitations. Based on …
Gated dynamic neural network model for digital predistortion of RF power amplifiers with varying transmission configurations
The future intelligent transmitter will dynamically adjust the transmission configuration on
demand, which will bring new challenges to digital predistortion (DPD). In this article, we …
demand, which will bring new challenges to digital predistortion (DPD). In this article, we …
Fast multi-physics simulation of microwave filters via deep hybrid neural network
One fundamental difficulty in multiphysics numerical simulation is the complex interactions
between different physics domains leading to plenty of computational costs. Although neural …
between different physics domains leading to plenty of computational costs. Although neural …
Pruned basis space search for digital predistortion of RF power amplifiers
A novel behavioral modeling technique called pruned basis space search (PBSS) is
proposed for digital predistortion (DPD) of RF power amplifiers (PAs). The PBSS finds the …
proposed for digital predistortion (DPD) of RF power amplifiers (PAs). The PBSS finds the …
Neural-network-based digital predistortion for active antenna arrays under load modulation
In this letter, we propose an efficient solution to linearize mmWave active antenna array
transmitters that suffer from beam-dependent load modulation. We consider a dense neural …
transmitters that suffer from beam-dependent load modulation. We consider a dense neural …
Block-oriented time-delay neural network behavioral model for digital predistortion of RF power amplifiers
A novel block-oriented time-delay neural network (BOTDNN) model for dynamic nonlinear
modeling and digital predistortion (DPD) of RF power amplifiers (PAs) is proposed. The …
modeling and digital predistortion (DPD) of RF power amplifiers (PAs) is proposed. The …
Self-sensing digital predistortion of RF power amplifiers for 6G intelligent radio
The future intelligent communication systems will dynamically adjust the transmitted signal
according to the radio environment and human behavior, which will lead to the rapid change …
according to the radio environment and human behavior, which will lead to the rapid change …
Vector decomposed long short-term memory model for behavioral modeling and digital predistortion for wideband RF power amplifiers
H Li, Y Zhang, G Li, F Liu - IEEE Access, 2020 - ieeexplore.ieee.org
This paper proposes two novel vector decomposed neural network models for behavioral
modeling and digital predistortion (DPD) of radio-frequency (RF) power amplifiers (PAs) …
modeling and digital predistortion (DPD) of radio-frequency (RF) power amplifiers (PAs) …
Digital predistortion of RF power amplifiers with decomposed vector rotation-based recurrent neural networks
T Kobal, A Zhu - IEEE Transactions on Microwave Theory and …, 2022 - ieeexplore.ieee.org
In this article, we present a novel decomposed vector rotation (DVR)-based recurrent neural
network behavioral model for digital predistortion (DPD) of radio frequency (RF) power …
network behavioral model for digital predistortion (DPD) of radio frequency (RF) power …