| Autor: |
Deyu Kong, Shaogang Hu, Yuancong Wu, Junjie Wang, Canlong Xiong, Qi Yu, Zhengyu Shi, Zhen Liu, Tupei Chen, You Yin, Sumio Hosaka, Yang Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 6, Pp 68773-68781 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2018.2880033 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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