Title
Cell-Based Variable-Gain Amplifiers With Accurate dB-Linear Characteristic in 0.18 µm CMOS Technology
Abstract
A simple and robust “cell-based” method is presented for the design of variable-gain amplifiers (VGAs). The proposed unit cell utilizes a unique gain compensation method and achieves accurate dB-linear characteristic across a wide tuning range with low power consumption and wide bandwidth. Several such highly dB-linear unit cells can be cascaded to provide the required gain range for a VGA. To prove the concept, single-cell, 5-cell, 10-cell and 15-cell reconfigurable VGAs were fabricated in a standard 0.18 μm CMOS technology. The measurement results show that the 10-cell VGA achieves a gain range of 38.6 dB with less than 0.19 dB gain error. The 15-cell VGA can either be used as reconfigurable VGA for analog control voltage or tunable PGA for digital control stream, with the flexibility of scaling gain range, gain error/step and power consumption. For the VGA at highest gain setting, it consumes 1.12 mW and achieves a gain range of 56 dB, gain error less than 0.3 dB.
Year
DOI
Venue
2015
10.1109/JSSC.2014.2368132
J. Solid-State Circuits
Keywords
Field
DocType
power scalable,robust cell based method,standard cmos technology,cmos integrated circuits,low power consumption,cell based,db-linear,cmos variable gain amplifier,amplifiers,programmable gain amplifier,low-power electronics,simple cell based method,accurate db-linear characteristic,reconfigurable vga,size 0.18 mum,analog control voltage,power 1.12 mw,low power,reconfigurable,unique gain compensation,15-cell vga,gain compensation,cell-based variable-gain amplifiers,scaling gain range,digital control,digital control stream,gain,bandwidth,electronics packaging
Open-loop gain,Computer science,Voltage,Electronic engineering,CMOS,Bandwidth (signal processing),Programmable-gain amplifier,Digital control,Electrical engineering,Video Graphics Array,Amplifier
Journal
Volume
Issue
ISSN
50
2
0018-9200
Citations 
PageRank 
References 
19
1.33
9
Authors
4
Name
Order
Citations
PageRank
Hang Liu183590.79
Xi Zhu27115.83
Chirn Chye Boon313626.81
Xiaofeng He4201.81