Transmission scheduling scheme based on deep Q learning in wireless network
To cope with the problem of data transmission in wireless networks,a deep Q learning based transmission scheduling scheme was proposed.The Markov decision process system model was formulated to describe the state transition of the system.The Q learning algorithm was adopted to learn and explore the...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2018-04-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018058/ |
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| _version_ | 1841539442677907456 |
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| author | Jiang ZHU Tingting WANG Yonghui SONG Yali LIU |
| author_facet | Jiang ZHU Tingting WANG Yonghui SONG Yali LIU |
| author_sort | Jiang ZHU |
| collection | DOAJ |
| description | To cope with the problem of data transmission in wireless networks,a deep Q learning based transmission scheduling scheme was proposed.The Markov decision process system model was formulated to describe the state transition of the system.The Q learning algorithm was adopted to learn and explore the system states transition information in the case of unknown system states transition probability to obtain the approximate optimal strategy of the schedule node.In addition,when the system state scale was big,the deep learning method was employed to map the relation between state and behavior to solve the problem of the large amount of computation and storage space in Q learning process.The simulation results show that the proposed scheme can approach the optimal strategy based on strategy iteration in terms of power consumption,throughput,packets loss rate.And the proposed scheme has a lower complexity,which can solve the problem of the curse of dimensionality. |
| format | Article |
| id | doaj-art-93a77bf8ee4a42ea87964db6761fcad2 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2018-04-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-93a77bf8ee4a42ea87964db6761fcad22025-01-14T07:14:30ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2018-04-0139354459717421Transmission scheduling scheme based on deep Q learning in wireless networkJiang ZHUTingting WANGYonghui SONGYali LIUTo cope with the problem of data transmission in wireless networks,a deep Q learning based transmission scheduling scheme was proposed.The Markov decision process system model was formulated to describe the state transition of the system.The Q learning algorithm was adopted to learn and explore the system states transition information in the case of unknown system states transition probability to obtain the approximate optimal strategy of the schedule node.In addition,when the system state scale was big,the deep learning method was employed to map the relation between state and behavior to solve the problem of the large amount of computation and storage space in Q learning process.The simulation results show that the proposed scheme can approach the optimal strategy based on strategy iteration in terms of power consumption,throughput,packets loss rate.And the proposed scheme has a lower complexity,which can solve the problem of the curse of dimensionality.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018058/wireless network transmissionMarkov decision processQ learningdeep learning |
| spellingShingle | Jiang ZHU Tingting WANG Yonghui SONG Yali LIU Transmission scheduling scheme based on deep Q learning in wireless network Tongxin xuebao wireless network transmission Markov decision process Q learning deep learning |
| title | Transmission scheduling scheme based on deep Q learning in wireless network |
| title_full | Transmission scheduling scheme based on deep Q learning in wireless network |
| title_fullStr | Transmission scheduling scheme based on deep Q learning in wireless network |
| title_full_unstemmed | Transmission scheduling scheme based on deep Q learning in wireless network |
| title_short | Transmission scheduling scheme based on deep Q learning in wireless network |
| title_sort | transmission scheduling scheme based on deep q learning in wireless network |
| topic | wireless network transmission Markov decision process Q learning deep learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018058/ |
| work_keys_str_mv | AT jiangzhu transmissionschedulingschemebasedondeepqlearninginwirelessnetwork AT tingtingwang transmissionschedulingschemebasedondeepqlearninginwirelessnetwork AT yonghuisong transmissionschedulingschemebasedondeepqlearninginwirelessnetwork AT yaliliu transmissionschedulingschemebasedondeepqlearninginwirelessnetwork |