Energy-Efficient Channel Estimation
We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are considered. We first formulate the energy-eff...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8950407/ |
| _version_ | 1818557457169907712 |
|---|---|
| author | Guandong Wei Kai Yang Xiaozheng Gao Ye Yu Jinsong Wu Jianping An |
| author_facet | Guandong Wei Kai Yang Xiaozheng Gao Ye Yu Jinsong Wu Jianping An |
| author_sort | Guandong Wei |
| collection | DOAJ |
| description | We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are considered. We first formulate the energy-efficient channel estimation problem into a mixed integer nonlinear programming (MINLP) problem, where the variables include the transmitted power and the number of data slots. Due to the NP-hard nature, we degenerate the MINLP problem into a series of non-concave optimization problems without integer variables. Then we solve these problems using successive convex approximation, geometric programming, and the Dinkelbach algorithm to obtain a point satisfying the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, we develop a low-complexity sub-optimal scheme through binary variable relaxation to obtain a solution, and the convergence point satisfies the KKT conditions of the relaxed non-concave problem. Simulation results demonstrate the convergence and effectiveness of our proposed schemes. |
| first_indexed | 2024-12-13T23:59:44Z |
| format | Article |
| id | doaj.art-6030874e823f435da8ed6ff5eaa3d00c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T23:59:44Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6030874e823f435da8ed6ff5eaa3d00c2022-12-21T23:26:23ZengIEEEIEEE Access2169-35362020-01-0189702971410.1109/ACCESS.2020.29643938950407Energy-Efficient Channel EstimationGuandong Wei0https://orcid.org/0000-0002-2802-902XKai Yang1https://orcid.org/0000-0003-1059-0705Xiaozheng Gao2https://orcid.org/0000-0002-0340-679XYe Yu3https://orcid.org/0000-0003-3783-0684Jinsong Wu4https://orcid.org/0000-0003-4720-5946Jianping An5https://orcid.org/0000-0002-6441-9711School of Information and Electronics, Beijing Institute of Technology, Beijing, ChinaSchool of Information and Electronics, Beijing Institute of Technology, Beijing, ChinaSchool of Information and Electronics, Beijing Institute of Technology, Beijing, ChinaSchool of Information and Electronics, Beijing Institute of Technology, Beijing, ChinaDepartment of Electrical Engineering, Universidad de Chile, Santiago, ChileSchool of Information and Electronics, Beijing Institute of Technology, Beijing, ChinaWe investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are considered. We first formulate the energy-efficient channel estimation problem into a mixed integer nonlinear programming (MINLP) problem, where the variables include the transmitted power and the number of data slots. Due to the NP-hard nature, we degenerate the MINLP problem into a series of non-concave optimization problems without integer variables. Then we solve these problems using successive convex approximation, geometric programming, and the Dinkelbach algorithm to obtain a point satisfying the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, we develop a low-complexity sub-optimal scheme through binary variable relaxation to obtain a solution, and the convergence point satisfies the KKT conditions of the relaxed non-concave problem. Simulation results demonstrate the convergence and effectiveness of our proposed schemes.https://ieeexplore.ieee.org/document/8950407/Energy efficiencychannel estimationpower control |
| spellingShingle | Guandong Wei Kai Yang Xiaozheng Gao Ye Yu Jinsong Wu Jianping An Energy-Efficient Channel Estimation IEEE Access Energy efficiency channel estimation power control |
| title | Energy-Efficient Channel Estimation |
| title_full | Energy-Efficient Channel Estimation |
| title_fullStr | Energy-Efficient Channel Estimation |
| title_full_unstemmed | Energy-Efficient Channel Estimation |
| title_short | Energy-Efficient Channel Estimation |
| title_sort | energy efficient channel estimation |
| topic | Energy efficiency channel estimation power control |
| url | https://ieeexplore.ieee.org/document/8950407/ |
| work_keys_str_mv | AT guandongwei energyefficientchannelestimation AT kaiyang energyefficientchannelestimation AT xiaozhenggao energyefficientchannelestimation AT yeyu energyefficientchannelestimation AT jinsongwu energyefficientchannelestimation AT jianpingan energyefficientchannelestimation |