Cooperative transmission schemes for energy efficient collaborative wireless sensor networks

Naeem, Muhammad and Patwary, Mohammad and Soliman, Abdel-Hamid and Abdel-Maguid, Mohamed (2014) Cooperative transmission schemes for energy efficient collaborative wireless sensor networks. IET Science, Measurement and Technology, 8 (6). pp. 391-398. ISSN 1751-8822

Full text not available from this repository. (Request a copy)

Abstract

Energy conservation is one of the prime concerns that leads the researcher to investigate collaborative wireless
sensor networks with some application specific challenges. Such challenges include combining distributed data
synchronously, performing power aware signal processing, defining communication methods that can provide
progressive accuracy and, optimising processing and communication for signal transmission. A cooperative resource selection and transmission scheme is proposed to improve the performance of collaborative wireless sensor networks in terms of maintaining link reliability. A measure of Channel Quality Index (CQI) is also proposed to obtain dynamic adaptivity and to optimise resource usage within wireless sensor networks according to environment conditions. As part of the proposed cooperative nature of transmission, the recently proposed transmit-receive antenna selection scheme and
lattice reduction algorithm have also been considered. It is assumed that channel state information (CSI) is estimated at receiver and also there is a feedback link between the wireless sensing nodes and the fusion centre receiver. From the simulation results it is observed that for 99.99% detection reliability, the proposed adaptive transmission scheme and proposed hybrid scheme consume only 15% and 18% of energy respectively as compared to the conventional cooperative transmission.

Item Type: Article
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cloud Computing
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 07 Mar 2017 12:08
Last Modified: 07 Mar 2017 12:08
URI: http://www.open-access.bcu.ac.uk/id/eprint/3992

Actions (login required)

View Item View Item

Research

In this section...