- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 861704, 11 pages
doi:10.1155/2012/861704
Energy-Model-Based Optimal Communication Systems Design for Wireless Sensor Networks
The Key Lab for Health Informatics of Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Received 29 June 2012; Revised 22 September 2012; Accepted 3 October 2012
Academic Editor: George P. Efthymoglou
Copyright © 2012 Ye Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
As is widely used in our daily life, wireless sensor network (WSN) is considered as one of the most important technologies of the new century. Although, the sensor nodes are usually battery powered with limited energy sources, the system energy consumption must be minimized in order to extend the life time. Since the energy consumption of transceiver front ends is dominant in the whole sensor nodes, we focus on how to minimize energy consumption by the system level design. According to the applications, we analyze four types of RF architectures: on-off keying (OOK) transceiver, phase-shift keying (PSK) transceiver, quadrature amplitude modulation (QAM) transceiver, and frequency-shift keying (FSK) transceiver which are widely used in WSN and establish the related energy models for each kind of architecture, respectively. We connect the baseband parameters such as modulation level, data rate, bandwidth, and propagation distance. with the energy consumption of RF front end for WSN. Afterwards, through theoretical and numerical analysis in system level, we discuss and conclude how to design optimal energy-quality system in terms of various application scenarios.