Cost-Minimized Crowdsourced Spectrum Sensing
Cooperative spectrum sensing which enhances the sensing accuracy is an important research issue for cognitive radio networks, especially in complicated environment. Considering the extensive use of mobile intelligent terminals such as smart phones and tablets, crowdsourced spectrum sensing, which as...
| Main Authors: | , , , |
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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/8880618/ |
| _version_ | 1818349352027947008 |
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| author | Xinyu Qiu Linbo Zhai Yinuo Fan Hua Wang |
| author_facet | Xinyu Qiu Linbo Zhai Yinuo Fan Hua Wang |
| author_sort | Xinyu Qiu |
| collection | DOAJ |
| description | Cooperative spectrum sensing which enhances the sensing accuracy is an important research issue for cognitive radio networks, especially in complicated environment. Considering the extensive use of mobile intelligent terminals such as smart phones and tablets, crowdsourced spectrum sensing, which assigns spectrum sensing tasks to mobile terminals, can take advantage of mobile terminals' cooperation and obtain the accurate sensing results. In this paper, crowdsourced spectrum sensing is studied to propose assignment scheme of spectrum sensing tasks in large geographical areas. There may be several kinds of terrains affecting sensing in large-scale regions. Hence, according to the terrains, we divide a large region into several sub-regions and introduce sensing effect function to evaluate the sensing accuracy based on the number of sensing sub-regions. Furthermore, considering energy consumption is an important issue which mobile terminals focus on, we use the relative energy consumption to evaluate the cost of mobile terminals during spectrum sensing. Then, we formulate the crowdsourced sensing problem to minimize the total cost while keeping sensing effect not lower than the predefined threshold to maintain sensing accuracy. Since the problem is NP-hard, a heuristic algorithm is proposed to solve the crowdsourced sensing problem. At first, our algorithm arranges all sensing tasks in a priority queue based on their urgency. Then, sensing tasks are sequentially assigned to terminals with higher energy to prolong their survival time under makespan and energy constraints. To obtain the lowest system cost, we introduce remaining time and reassign sensing tasks from high-cost terminals to low-cost terminals based on the remaining time. Simulation results show our algorithm achieves higher performance than the other algorithms. |
| first_indexed | 2024-12-13T18:04:35Z |
| format | Article |
| id | doaj.art-a81720c9b7c6402ab81af00610d8cb04 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T18:04:35Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a81720c9b7c6402ab81af00610d8cb042022-12-21T23:36:06ZengIEEEIEEE Access2169-35362019-01-01715464015464810.1109/ACCESS.2019.29492028880618Cost-Minimized Crowdsourced Spectrum SensingXinyu Qiu0Linbo Zhai1https://orcid.org/0000-0002-5064-0255Yinuo Fan2Hua Wang3School of Information Science and Engineering, Shandong Normal University, Jinan, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan, ChinaSchool of Software, Shandong University, Jinan, ChinaCooperative spectrum sensing which enhances the sensing accuracy is an important research issue for cognitive radio networks, especially in complicated environment. Considering the extensive use of mobile intelligent terminals such as smart phones and tablets, crowdsourced spectrum sensing, which assigns spectrum sensing tasks to mobile terminals, can take advantage of mobile terminals' cooperation and obtain the accurate sensing results. In this paper, crowdsourced spectrum sensing is studied to propose assignment scheme of spectrum sensing tasks in large geographical areas. There may be several kinds of terrains affecting sensing in large-scale regions. Hence, according to the terrains, we divide a large region into several sub-regions and introduce sensing effect function to evaluate the sensing accuracy based on the number of sensing sub-regions. Furthermore, considering energy consumption is an important issue which mobile terminals focus on, we use the relative energy consumption to evaluate the cost of mobile terminals during spectrum sensing. Then, we formulate the crowdsourced sensing problem to minimize the total cost while keeping sensing effect not lower than the predefined threshold to maintain sensing accuracy. Since the problem is NP-hard, a heuristic algorithm is proposed to solve the crowdsourced sensing problem. At first, our algorithm arranges all sensing tasks in a priority queue based on their urgency. Then, sensing tasks are sequentially assigned to terminals with higher energy to prolong their survival time under makespan and energy constraints. To obtain the lowest system cost, we introduce remaining time and reassign sensing tasks from high-cost terminals to low-cost terminals based on the remaining time. Simulation results show our algorithm achieves higher performance than the other algorithms.https://ieeexplore.ieee.org/document/8880618/Costcrowdsourcedspectrum sensing |
| spellingShingle | Xinyu Qiu Linbo Zhai Yinuo Fan Hua Wang Cost-Minimized Crowdsourced Spectrum Sensing IEEE Access Cost crowdsourced spectrum sensing |
| title | Cost-Minimized Crowdsourced Spectrum Sensing |
| title_full | Cost-Minimized Crowdsourced Spectrum Sensing |
| title_fullStr | Cost-Minimized Crowdsourced Spectrum Sensing |
| title_full_unstemmed | Cost-Minimized Crowdsourced Spectrum Sensing |
| title_short | Cost-Minimized Crowdsourced Spectrum Sensing |
| title_sort | cost minimized crowdsourced spectrum sensing |
| topic | Cost crowdsourced spectrum sensing |
| url | https://ieeexplore.ieee.org/document/8880618/ |
| work_keys_str_mv | AT xinyuqiu costminimizedcrowdsourcedspectrumsensing AT linbozhai costminimizedcrowdsourcedspectrumsensing AT yinuofan costminimizedcrowdsourcedspectrumsensing AT huawang costminimizedcrowdsourcedspectrumsensing |