This work introduces joint power amplifier (PA) and I/Q modulator modelling and compensation for LongTerm Evolution (LTE) transmitters using artificial neural networks (ANNs). The proposed solution util-izes a powerful nonlinear autoregressive with exogenous inputs (NARX) ANN architecture, which yieldsnoticeable results for high peak to average power ratio (PAPR) LTE signals. Given the ANNs learning capa-bilities, this one-step solution, which includes the mitigation of both PA nonlinearity and I/Q modulatorimpairments, is both accurate and adaptabl
Abstract- In this paper, we propose a feed-forward neural network model (FFNN) of the class B power ...
In this paper, an efficient Class-F power amplifier (PA) is designed, simulated and modeled. This ty...
International audienceDigital predistorsion (DPD) is a commonly used approach to compensate for the ...
In this article, a real valued time delay neural networks (RVTDNN) based power amplifier predistorte...
Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose ...
Power Amplifiers (PAs) are the key building blocks of the emerging wireless radios systems. They dom...
This work presents a digital predistortion (DPD) scheme to linearize power amplifiers (PAs) using a ...
This paper represents a neural network based joint mitigation of the IQ imbalance and power amplifie...
This paper is focused on the linearization of the radio frequency power amplifier of a professional ...
The purpose of the project is to investigate the possibility of using modern machine learning to mod...
This paper represents an experimental study on the linearisation of Power Amplifiers especially on h...
This paper presents a novel Two Hidden Layers Artificial Neural Networks (2HLANN) model for behavior...
Fifth-generation telecommunications networks are expected to have technical requirements which far o...
This work presents a novel Digital Predistortion (DPD) scheme based on a NARX network, suitable for ...
This paper presents a Two Layer Artificial Neural Network (2LANN) model for linearization of pico-ce...
Abstract- In this paper, we propose a feed-forward neural network model (FFNN) of the class B power ...
In this paper, an efficient Class-F power amplifier (PA) is designed, simulated and modeled. This ty...
International audienceDigital predistorsion (DPD) is a commonly used approach to compensate for the ...
In this article, a real valued time delay neural networks (RVTDNN) based power amplifier predistorte...
Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose ...
Power Amplifiers (PAs) are the key building blocks of the emerging wireless radios systems. They dom...
This work presents a digital predistortion (DPD) scheme to linearize power amplifiers (PAs) using a ...
This paper represents a neural network based joint mitigation of the IQ imbalance and power amplifie...
This paper is focused on the linearization of the radio frequency power amplifier of a professional ...
The purpose of the project is to investigate the possibility of using modern machine learning to mod...
This paper represents an experimental study on the linearisation of Power Amplifiers especially on h...
This paper presents a novel Two Hidden Layers Artificial Neural Networks (2HLANN) model for behavior...
Fifth-generation telecommunications networks are expected to have technical requirements which far o...
This work presents a novel Digital Predistortion (DPD) scheme based on a NARX network, suitable for ...
This paper presents a Two Layer Artificial Neural Network (2LANN) model for linearization of pico-ce...
Abstract- In this paper, we propose a feed-forward neural network model (FFNN) of the class B power ...
In this paper, an efficient Class-F power amplifier (PA) is designed, simulated and modeled. This ty...
International audienceDigital predistorsion (DPD) is a commonly used approach to compensate for the ...