Smart City Gnosys
Smart city article details
| Title | Collaborative Energy And Information Transfer In Green Wireless Sensor Networks For Smart Cities |
|---|---|
| ID_Doc | 14714 |
| Authors | Lu, WD; Gong, Y; Liu, X; Wu, JY; Peng, H |
| Year | 2018 |
| Published | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 14, 4 |
| DOI | http://dx.doi.org/10.1109/TII.2017.2777846 |
| Abstract | Smart city is able to make the city source and infrastructure more efficiently utilized, which improves the quality of life for citizens. In this framework, wireless sensor networks (WSNs) play an important role to collect, process, and analyze the corresponding information. However, the massive deployment of WSNs consumes a significant energy consumption, which has raised the growing demand for green WSNs for smart cities. Exploiting the recent advance in collaborative energy and information transfer to power the WSNs and transmit the data has been considered a promising approach to realize the green WSNs for smart cities. We propose an architecture design of the green WSNs for smart cities, by exploiting the collaborative energy and information transfer protocol, and illustrate the challenging issues in this design. To achieve a green system design, the sensor nodes in WSNs harvest the energy simultaneously with the information decoding (ID) from the received radio frequency signals. Specifically, the energy-constrained sensor nodes partition the received signals into two independent groups to perform energy harvesting (EH) and ID. The sensor nodes then use the harvested energy to amplify and forward the information signals. We study the joint optimization of subcarrier grouping, subcarrier pairing, and power allocation such that the transmission rate performance is maximized with the EH constraint. The joint optimization problem is solved via dual decomposition after transforming it into an equivalent convex optimization problem. Simulation results tested with the real WSNs system data indicate that the performance of our proposed protocol can be significantly improved. |
| Author Keywords | Collaborative energy and information transfer; power allocation; subcarrier allocation; wireless sensor networks (WSNs) |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
40057  | 0.879 | Kim Y.; Jung B.C.; Song Y. | Online Learning For Joint Energy Harvesting And Information Decoding Optimization In Iot-Enabled Smart City | IEEE Internet of Things Journal, 10, 12 (2023) |
| 36508 | 0.852 | Liu Y.; Qin X.; Huang Y.; Tang L.; Fu J. | Maximizing Energy Efficiency In Hybrid Overlay-Underlay Cognitive Radio Networks Based On Energy Harvesting-Cooperative Spectrum Sensing | Energies, 15, 8 (2022) |
| 3752 | 0.852 | Mori S. | A Preliminary Analysis Of Data Collection And Retrieval Scheme For Green Information-Centric Wireless Sensor Networks | NET4us 2022 - Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for Sustainable Society (2022) |
| 19064 | 0.851 | Minhas D.; Suresh V.G.; Patil M.S.; Kumar R.; Kumar A.; Primmia D.R. | Designing An Energy-Efficient Virtual Cell-Based Data Propagation Scheme For Wireless Sensor Networks With Single Mobile Sink | 2024 IEEE 4th International Conference on ICT in Business Industry and Government, ICTBIG 2024 (2024) |
| 13062 | 0.85 | Banerjee A.; De S.K.; Majumder K.; Das V.; Chattopadhyay S.; Shaw R.N.; Ghosh A. | Building Of Efficient Communication System In Smart City Using Wireless Sensor Network Through Hybrid Optimization Technique | Studies in Computational Intelligence, 1002 (2022) |