Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103407
Title: Realization of a power-efficient transmitter based on integrated artificial neural network
Authors: Kong, Deyu
Hu, Shaogang
Wu, Yuancong
Wang, Junjie
Xiong, Canlong
Yu, Qi
Shi, Zhengyu
Liu, Zhen
Chen, Tupei
Yin, You
Hosaka, Sumio
Liu, Yang
Keywords: Radiofrequency Amplifiers
DRNTU::Engineering::Electrical and electronic engineering
Radio Transmitters
Issue Date: 2018
Source: Kong, D., Hu, S., Wu, Y., Wang, J., Xiong, C., Yu, Q., . . . Liu, Y. (2018). Realization of a power-efficient transmitter based on integrated artificial neural network. IEEE Access, 6, 68773-68781. doi:10.1109/ACCESS.2018.2880033
Series/Report no.: IEEE Access
Abstract: In wireless devices, a transmitter normally consumes most of power due to its power amplifier (PA), especially in the applications such as radar, base station, and mobile phone. It is highly desirable to design a transmitter that can emit signals smartly, i.e., the power emission is exactly based on the emitting distance required and the target. Such a design can save huge amount of power as there are almost countless wireless devices in use currently. In this paper, an intelligent radio-frequency transmitter integrated with artificial neural network (ANN) is implemented. The intelligent transmitter consists of an ANN module, a frequency generation module, and a switch-mode PA. The integrated three-layered fully connected ANN can be offline trained to smartly classify input data according to the required power and assign the transmission channel. Furthermore, with the integrated ANN, the average power consumption of the PA is reduced to 34.3 mW, which is 46.5 % lower than PA without the ANN. With the intelligent transmitter, wireless devices can save a large amount of energy in their operations.
URI: https://hdl.handle.net/10356/103407
http://hdl.handle.net/10220/47303
DOI: 10.1109/ACCESS.2018.2880033
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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