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Communication Dans Un Congrès Année : 2013

Predistortion system implementation based on analog Neural Networks for linearizing High Power Amplifiers transfer characteristics

Résumé

In order to correct non-linearities due to High Power Amplifiers (HPA) operating near saturation in telecommunication transceivers, a new adaptive predistortion system based on analog Neural Networks (NNs) was developed. Based on size, consumption and bandwidth considerations, Multi-Layer Perceptron (MLP) type NNs were implemented in a 0.6 µm CMOS ASIC. The NNs parameters are digitally updated with a computer, depending on simulation conditions (temperature drifts, ageing variations). The interface between the analog part and the software updating system is integrated in an analog/digital PCB including a FPGA, 6 analog-to-digital converters and 62 digital-to-analog converters. This paper describes the realization of each part of the breadboard system and presents experimental validation results of the whole predistortion module.
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Dates et versions

hal-00942355 , version 1 (27-05-2014)

Identifiants

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Blaise Mulliez, Emmanuel R. Moutaye, Hélène Tap, Laurent Gatet, Francis Girard. Predistortion system implementation based on analog Neural Networks for linearizing High Power Amplifiers transfer characteristics. Telecommunications and Signal Processing (TSP), 2013 36th International Conference on, Jul 2013, Rome, Italy. pp.412-416, ⟨10.1109/TSP.2013.6613964⟩. ⟨hal-00942355⟩
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