Research Article
A joint approach for PAPR reduction and predistortion by adding signal in Cognitive Radio
@INPROCEEDINGS{10.4108/icst.crowncom.2013.252009, author={Abel Gouba and Yves Lou\`{\i}t}, title={A joint approach for PAPR reduction and predistortion by adding signal in Cognitive Radio}, proceedings={8th International Conference on Cognitive Radio Oriented Wireless Networks}, publisher={ICST}, proceedings_a={CROWNCOM}, year={2013}, month={11}, keywords={papr predistortion joint approach power amplifier linearity efficiency radio environment}, doi={10.4108/icst.crowncom.2013.252009} }- Abel Gouba
Yves Louët
Year: 2013
A joint approach for PAPR reduction and predistortion by adding signal in Cognitive Radio
CROWNCOM
IEEE
DOI: 10.4108/icst.crowncom.2013.252009
Abstract
In this paper, we propose to use a joint approach for Peak-to-Average Power Ratio (PAPR) reduction and memoryless predistortion by adding signal in order to improve Power Amplifier linearity and efficiency performances depending on the radio environment. First, the radio environment is sensed and informations such as signal’s PAPR, channel estimation, Signal-to-Noise Ratio (SNR) and battery level are collected. Accordingly, a decision engine updates additional signals for PAPR reduction and predistortion in order to meet targeted linearity and power efficiency requirements. Ideally suited for Cognitive Radio (CR) systems, this dynamic joint approach by adding signal is simulated and validated through two scenarios represented on two examples of radio environment. The PAPR reduction performance is evaluated by the Complementary Cumulative Density Function(CCDF) and the PA linearity by Error Vector Magnitude (EVM) criteria.