A Cost-Efficient and Energy Harvesting Design of Wireless Sensor Networks,
funded by DFG (2017 - Present)
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 environment, health, military 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. As sensor nodes carry limited, in general irreplaceable power sources, one of the most important constraints for WSNs is a low power consumption requirement. Thus, power conservation is of tremendous importance. In this proposal, we first investigate and devise cost-efficient solutions for the physical layer and cross layer designs for WSNs when battery-powered nodes are considered. This includes low-complexity algorithms for channel estimation and data censoring, joint design of data fusion, resource allocation and relay selection. The proposed algorithms are aimed at substantially reducing the amount of data processing and transmission while still allowing an improvement in the performance of the networks. Second, we employ energy harvesting techniques for WSNs. An optimization of energy harvesting parameters, an adaptive sampling with two energy-efficient retransmission protocols and a novel relay selection scheme are proposed under the condition of using energy harvesting nodes as cooperative relays. As a result, the network lifetime will be extended and data processing capabilities will be greatly enhanced compared to the battery powered nodes. The practicability of our approaches will be verified by experimental validation.
- P. Ghofrani, T. Wang and A. Schmeink, "A Fast Converging Channel Estimation Algorithm for Wireless Sensor Networks", IEEE Transactions on Signal Processing, accepted.
© ISEK at RWTH Aachen