Optimal Finite Horizon Sensing for Wirelessly Powered Devices
We are witnessing a significant advancements in the sensor technologies which has enabled a broad spectrum of applications. Often, the resolution of the produced data by the sensors significantly affects the output quality of an application. We study a sensing resolution optimization problem for a w...
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8836517/ |
| _version_ | 1818603108551360512 |
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| author | Mehdi Salehi Heydar Abad Ozgur Ercetin |
| author_facet | Mehdi Salehi Heydar Abad Ozgur Ercetin |
| author_sort | Mehdi Salehi Heydar Abad |
| collection | DOAJ |
| description | We are witnessing a significant advancements in the sensor technologies which has enabled a broad spectrum of applications. Often, the resolution of the produced data by the sensors significantly affects the output quality of an application. We study a sensing resolution optimization problem for a wireless powered device (WPD) that is powered by wireless power transfer (WPT) from an access point (AP). We study a class of harvest-first-transmit-later type of WPT policy, where an access point (AP) first employs RF power to recharge the WPD in the down-link, and then, collects the data from the WPD in the up-link. The WPD optimizes the sensing resolution, WPT duration and dynamic power control in the up-link to maximize an application dependant utility at the AP. The utility of a transmitted packet is only achieved if the data is delivered successfully within a finite time. Thus, we first study a finite horizon throughput maximization problem by jointly optimizing the WPT duration and power control. We prove that the optimal WPT duration obeys a time-dependent threshold form depending on the energy state of the WPD. In the subsequent data transmission stage, the optimal transmit power allocations for the WPD is shown to posses a channel-dependent fractional structure. Then, we optimize the sensing resolution of the WPD by using a Bayesian inference based multi armed bandit problem with fast convergence property to strike a balance between the quality of the sensed data and the probability of successfully delivering it. |
| first_indexed | 2024-12-16T13:17:56Z |
| format | Article |
| id | doaj.art-ed44d2fd97ca49e1a7a0c42d8124d229 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T13:17:56Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ed44d2fd97ca49e1a7a0c42d8124d2292022-12-21T22:30:26ZengIEEEIEEE Access2169-35362019-01-01713147313148710.1109/ACCESS.2019.29413778836517Optimal Finite Horizon Sensing for Wirelessly Powered DevicesMehdi Salehi Heydar Abad0https://orcid.org/0000-0002-5281-946XOzgur Ercetin1Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, TurkeyFaculty of Engineering and Natural Sciences, Sabanci University, Istanbul, TurkeyWe are witnessing a significant advancements in the sensor technologies which has enabled a broad spectrum of applications. Often, the resolution of the produced data by the sensors significantly affects the output quality of an application. We study a sensing resolution optimization problem for a wireless powered device (WPD) that is powered by wireless power transfer (WPT) from an access point (AP). We study a class of harvest-first-transmit-later type of WPT policy, where an access point (AP) first employs RF power to recharge the WPD in the down-link, and then, collects the data from the WPD in the up-link. The WPD optimizes the sensing resolution, WPT duration and dynamic power control in the up-link to maximize an application dependant utility at the AP. The utility of a transmitted packet is only achieved if the data is delivered successfully within a finite time. Thus, we first study a finite horizon throughput maximization problem by jointly optimizing the WPT duration and power control. We prove that the optimal WPT duration obeys a time-dependent threshold form depending on the energy state of the WPD. In the subsequent data transmission stage, the optimal transmit power allocations for the WPD is shown to posses a channel-dependent fractional structure. Then, we optimize the sensing resolution of the WPD by using a Bayesian inference based multi armed bandit problem with fast convergence property to strike a balance between the quality of the sensed data and the probability of successfully delivering it.https://ieeexplore.ieee.org/document/8836517/Bayesian inferencemulti-armed banditreinforcement learningwireless power transfer |
| spellingShingle | Mehdi Salehi Heydar Abad Ozgur Ercetin Optimal Finite Horizon Sensing for Wirelessly Powered Devices IEEE Access Bayesian inference multi-armed bandit reinforcement learning wireless power transfer |
| title | Optimal Finite Horizon Sensing for Wirelessly Powered Devices |
| title_full | Optimal Finite Horizon Sensing for Wirelessly Powered Devices |
| title_fullStr | Optimal Finite Horizon Sensing for Wirelessly Powered Devices |
| title_full_unstemmed | Optimal Finite Horizon Sensing for Wirelessly Powered Devices |
| title_short | Optimal Finite Horizon Sensing for Wirelessly Powered Devices |
| title_sort | optimal finite horizon sensing for wirelessly powered devices |
| topic | Bayesian inference multi-armed bandit reinforcement learning wireless power transfer |
| url | https://ieeexplore.ieee.org/document/8836517/ |
| work_keys_str_mv | AT mehdisalehiheydarabad optimalfinitehorizonsensingforwirelesslypowereddevices AT ozgurercetin optimalfinitehorizonsensingforwirelesslypowereddevices |