Cost Effective Design and Performance Evaluation for Cooperative Wireless Sensor Networks

Recently, wireless sensor networks (WSNs) have been proven extremely powerful because of their unique features that allow a wide range of applications in the areas of military, environment, health and home. WSNs are usually composed of a large number of densely deployed sensing devices which can transmit their data to the desired destination through multihop relays (see Figure). As sensor nodes carry limited, in general irreplaceable power sources, one of the most important constraints for WSNs is the low power consumption requirement. Thus, power conservation is of tremendous importance.

Wireless Sensor Network

General Tasks

The focus of our research is on WSNs and the need for cost effective solutions, increased capacity and enhanced performance for data fusion and processing. We consider WSNs that operate in a cooperative way with two or multiple hops. The sensor nodes are battery powered, have a limited lifetime, reduced communications and data processing capabilities. Therefore, a major focus is on low-energy solutions. The aim of our research on algorithms, designs and strategies for WSNs is to achieve high performance by still reducing the power consumption. As a result, the network lifetime will be extended and data processing capabilities will be greatly enhanced. Current topics are:

Low-complexity Channel Estimation

For this topic, we focus on low complexity channel estimation methods for WSNs. Because most of the research on other layers are based on the assumption of perfect synchronization and available channel state information (CSI) at each node, more accurate estimates of the CSI will bring better performance for WSNs. We investigate the set-membership filtering (SMF) framework and incorporate it into the conventional channel estimation algorithms such as least-mean-square (LMS), recursive least-square (RLS), conjugate gradient (CG), affine projection (AP) and date reusing algorithms, etc. These set-membership channel estimation algorithms can reduce the computational complexity significantly and extend the lifetime of the WSN by reducing its power consumption.

Joint Design Strategies with Resource Allocation

For this topic, we investigate strategies to jointly design resource allocation, data fusion, relay selection strategies, and energy harvesting (see Figure). The aim of our research is to improve the performance under the constraint of the limited power consumption of the sensor nodes.

Joint Algorithm

Analysis of Relaying Strategies and Protocol Design

Related research topics and publications

Related projects


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