Dissertation
Energy Harvesting DCDC Converter and High Efficient Power Amplifier Bias Modulator for Ubiquitous Wireless Sensor Networks
Doctor of Design (DDes), Washington State University
01/2013
Handle:
https://hdl.handle.net/2376/111844
Abstract
In wireless sensor networks, one of the challenges is to find a renewable power source that can provide sufficient and continuous power for wireless high voltage sensors, since it is very hard to manually change the batteries over all the networks. Energy harvesting system (EHS) with high efficiency and high output voltage provides one good solution to produce the required power by the wireless sensors. In EHS, stepup converter is a key component to generate high voltage. However, startup stepup converter from low voltage level is a challenge for designers. Meanwhile, on the load side of wireless sensor networks, power amplifier (PA) consumes the most of power in the transmitter. Thus, it is very urgent to improve PA power efficiency.
This dissertation develops a new charge pump and a subthreshold CMOS voltage reference to start up stepup converter under low power supply condition. Under 320 mV voltage supply, the novel charge pump can generate 2 V high voltage to start up the stepup converter in EHS. Meanwhile, voltage reference is important part to provide a constant voltage bias to control stepup converter. The dissertation also exploits the load side of wireless sensor network by designing a high efficient bias modulator for CMOS power amplifier (PA). The bias modulator can envelop track the input LTE baseband signal and provide a variable bias voltage supply to the drain side of the CMOS PA. Envelop tracking bias modulator largely decrease the power loss in power amplifier, compared to the fixed voltage supply.
Metrics
Details
- Title
- Energy Harvesting DCDC Converter and High Efficient Power Amplifier Bias Modulator for Ubiquitous Wireless Sensor Networks
- Creators
- Huan Peng
- Contributors
- Deukhyoun Heo (Advisor)John Ringo (Committee Member)Partha Pande (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Doctor of Design (DDes), Washington State University
- Number of pages
- 87
- Identifiers
- 99900581847201842
- Language
- English
- Resource Type
- Dissertation