Dynamic hierarchy resource management for heterogeneous cognitive network
A dynamic hierarchy resource management approach-DHRM based on intelligent prediction was proposed for heterogeneous cognitive network.In DHRM,according to different time scale,the method of wavelet neural network,wiener prediction and reinforcement learning were brought to get the variation of traf...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2012-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0107-07/ |
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| _version_ | 1841539935809568768 |
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| author | Juan WEN Min SHENG Yan ZHANG |
| author_facet | Juan WEN Min SHENG Yan ZHANG |
| author_sort | Juan WEN |
| collection | DOAJ |
| description | A dynamic hierarchy resource management approach-DHRM based on intelligent prediction was proposed for heterogeneous cognitive network.In DHRM,according to different time scale,the method of wavelet neural network,wiener prediction and reinforcement learning were brought to get the variation of traffic d ion,the resource requirement of the handover calls,and the information of users’preferences,and available hierarchical resources of all networks were allocated flexibly.Multi-attribute decision making method,based on network status and user preference was used to make decision to dynamically assign network traffic flow to the most appropriate network.Simulation results show that,the system capacity is improved about 20% by DHRM compared with the other joint radio resource management algorithms. |
| format | Article |
| id | doaj-art-2c71b7d775e74ec1bf52a62bf4e5b5a6 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2012-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-2c71b7d775e74ec1bf52a62bf4e5b5a62025-01-14T06:30:57ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2012-01-013310711359659643Dynamic hierarchy resource management for heterogeneous cognitive networkJuan WENMin SHENGYan ZHANGA dynamic hierarchy resource management approach-DHRM based on intelligent prediction was proposed for heterogeneous cognitive network.In DHRM,according to different time scale,the method of wavelet neural network,wiener prediction and reinforcement learning were brought to get the variation of traffic d ion,the resource requirement of the handover calls,and the information of users’preferences,and available hierarchical resources of all networks were allocated flexibly.Multi-attribute decision making method,based on network status and user preference was used to make decision to dynamically assign network traffic flow to the most appropriate network.Simulation results show that,the system capacity is improved about 20% by DHRM compared with the other joint radio resource management algorithms.http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0107-07/cognitive networkheterogeneous wireless networkradio resource managementintelligent learning |
| spellingShingle | Juan WEN Min SHENG Yan ZHANG Dynamic hierarchy resource management for heterogeneous cognitive network Tongxin xuebao cognitive network heterogeneous wireless network radio resource management intelligent learning |
| title | Dynamic hierarchy resource management for heterogeneous cognitive network |
| title_full | Dynamic hierarchy resource management for heterogeneous cognitive network |
| title_fullStr | Dynamic hierarchy resource management for heterogeneous cognitive network |
| title_full_unstemmed | Dynamic hierarchy resource management for heterogeneous cognitive network |
| title_short | Dynamic hierarchy resource management for heterogeneous cognitive network |
| title_sort | dynamic hierarchy resource management for heterogeneous cognitive network |
| topic | cognitive network heterogeneous wireless network radio resource management intelligent learning |
| url | http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0107-07/ |
| work_keys_str_mv | AT juanwen dynamichierarchyresourcemanagementforheterogeneouscognitivenetwork AT minsheng dynamichierarchyresourcemanagementforheterogeneouscognitivenetwork AT yanzhang dynamichierarchyresourcemanagementforheterogeneouscognitivenetwork |