Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network
© 2013 IEEE. Network utility maximization has been widely adopted to allocate the resource of networks. However, it suffers from slow convergence under distributed computational environment. This paper proposes a fast rate control algorithm to maximize network utility for energy harvesting in a wire...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
IEEE Access
2018
|
| Online Access: | http://hdl.handle.net/20.500.11937/71503 |
| _version_ | 1848762497033568256 |
|---|---|
| author | Zhao, C. Chen, S. Wu, Changzhi Chen, F. Ji, Y. |
| author_facet | Zhao, C. Chen, S. Wu, Changzhi Chen, F. Ji, Y. |
| author_sort | Zhao, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2013 IEEE. Network utility maximization has been widely adopted to allocate the resource of networks. However, it suffers from slow convergence under distributed computational environment. This paper proposes a fast rate control algorithm to maximize network utility for energy harvesting in a wireless sensor network. Energy harvesting and channel bandwidth limits are considered together to formulate as a utility maximization problem. Then, an accelerated distributed gradient method is proposed to solve the problem for energy harvesting. Numerical experiments show that the accelerated method achieves faster convergence to the optimal sampling rate under energy and channel constraints than traditional gradient descent methods. |
| first_indexed | 2025-11-14T10:48:30Z |
| format | Journal Article |
| id | curtin-20.500.11937-71503 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:48:30Z |
| publishDate | 2018 |
| publisher | IEEE Access |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-715032018-12-13T09:34:01Z Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network Zhao, C. Chen, S. Wu, Changzhi Chen, F. Ji, Y. © 2013 IEEE. Network utility maximization has been widely adopted to allocate the resource of networks. However, it suffers from slow convergence under distributed computational environment. This paper proposes a fast rate control algorithm to maximize network utility for energy harvesting in a wireless sensor network. Energy harvesting and channel bandwidth limits are considered together to formulate as a utility maximization problem. Then, an accelerated distributed gradient method is proposed to solve the problem for energy harvesting. Numerical experiments show that the accelerated method achieves faster convergence to the optimal sampling rate under energy and channel constraints than traditional gradient descent methods. 2018 Journal Article http://hdl.handle.net/20.500.11937/71503 10.1109/ACCESS.2018.2869524 IEEE Access restricted |
| spellingShingle | Zhao, C. Chen, S. Wu, Changzhi Chen, F. Ji, Y. Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title | Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title_full | Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title_fullStr | Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title_full_unstemmed | Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title_short | Accelerated Sampling Optimization for RF Energy Harvesting Wireless Sensor Network |
| title_sort | accelerated sampling optimization for rf energy harvesting wireless sensor network |
| url | http://hdl.handle.net/20.500.11937/71503 |