IEEE Access
(Jan 2019)
Design of a Neural Network-Based VCO With High Linearity and Wide Tuning Range
Rui Guo,
Kun Qian,
Jinping Wei,
Tupei Chen,
Yanchen Liu,
Deyu Kong,
J. J. Wang,
Yuancong Wu,
S. G. Hu,
Qi Yu,
Yang Liu
Affiliations
Rui Guo
ORCiD State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Kun Qian
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Jinping Wei
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Tupei Chen
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Yanchen Liu
ORCiD State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Deyu Kong
ORCiD State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
J. J. Wang
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Yuancong Wu
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
S. G. Hu
ORCiD State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Qi Yu
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
Yang Liu
ORCiD State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, China
DOI
https://doi.org/10.1109/ACCESS.2019.2915335
Journal volume & issue
Vol. 7
Abstract
Read online
In this paper, a 2 GHz LC-VCO with neural network (Multilayer Perceptron) has been designed in a 0.13 ţm CMOS technology. With the integrated neural network, the linearity and tuning range of the LC-VCO has been substantially improved. Compared to a conventional VCO design, the proposed technique can improve the linearity by selecting optimized bias voltages obtained from the output of the neuron network. The result shows that the tuning nonlinearity of the proposed VCO is further optimized from 0.335% to 0.254%.
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