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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳光禎 | |
| dc.contributor.author | Tzu-Huan Liau | en |
| dc.contributor.author | 廖孜桓 | zh_TW |
| dc.date.accessioned | 2021-06-07T17:54:32Z | - |
| dc.date.copyright | 2012-08-19 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-16 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15886 | - |
| dc.description.abstract | 在今日的頻譜分配策略下，為了提高頻譜利用率，感知無線電技術是眾所周知的一種加強效果的方法。通過伺機傳輸鏈路級，感知無線電技術能在今日的網路頻譜分配政策下有效提供一種頻譜使用率過低的問題。然而，使用頻譜感知無線電技術之後的系統時間動態相當未知。我們注意到，該系統行為是在一個共存的不同物種之間的相互作用非常相似生態系統。因此，我們以著名的的優勢兩個代表異構用戶的天敵種類飼料實物捕食代表資源。用人自然種群動態的頻譜共享的生態系統，以如此的生態模型，我們可以有效地識別感知無線電網路的時間動態和開發有效的方法來實現的感知無線電系統穩定性評估。論文的第一部分將簡述生態模型的歷史以及眾多分類。我們考慮到使用生態模型以及其數學模型的理論分析以及性質。第二部分將此模型應用到三個不同的感知無線電系統以及其時間動態分析，以著名的捕食與被捕食模型的優勢兩個代表異構用戶的天敵種類飼料實物捕食代表資源並以不同的網路作為分析對象以闡明感知無線電網路的時間特性。第三部分則簡述了使用空間蓋念的生態模型來描述一感知無線電網路的時間動態以及其系統分析。最後我們在最後一章對於整個研究的貢獻做出了簡單的結論以及此研究未來的發展方向。 | zh_TW |
| dc.description.abstract | Cognitive radio technology is well known to enhance spectrum utilization via opportunistic transmission at link level. However, the time dynamics of spectrum utilization among primary system users and secondary cognitive radio users in such cognitive radio networks are pretty unknown at this time. We note that the system behaviors are very similar to interaction among different species coexisting in an ecosystem. Therefore, we take advantage of well-known predator-prey model where two species of predators representing heterogeneous users feed on the one specie of prey representing resources. Employing nature population dynamics in the spectrum sharing ecosystem, we could efficiently identify the time dynamics of CRs and the develop efficient ways to achieve system stability assessment for CRs. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-07T17:54:32Z (GMT). No. of bitstreams: 1 ntu-101-R99942100-1.pdf: 2560606 bytes, checksum: ac6f50de327e2b14eef67f96b20fe17b (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | Abstract i
Contents ii List of Figures iv 1 Introduction 1 1.1 Cognitive Radio Networks and Ecology Models . . . . . . . . . . . . . 1 1.2 Scope and Propositions of the Thesis . . . . . . . . . . . . . . . . . . 4 2 Preliminaries 7 2.1 Biological Population Models . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Spatial Ecological Models . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Construction of a Biological Model . . . . . . . . . . . . . . . . . . . 9 2.3.1 Gain in the Fitness Function . . . . . . . . . . . . . . . . . . . 10 2.3.2 Loss in the Fitness Function . . . . . . . . . . . . . . . . . . . 10 2.3.3 The Fitness of Preys . . . . . . . . . . . . . . . . . . . . . . . 11 2.3.4 Equilibrium of the model . . . . . . . . . . . . . . . . . . . . . 11 3 Biological Approach to Dynamics of Cognitive Radio 14 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 ii 3.1.1 Superframe Structure . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Mathematical evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2.1 Traffic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2.2 Direct Access . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.3 Sequential access . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3 Throughput Optimization for Collision Avoidance . . . . . . . . . . . 28 3.3.1 Mathematical Evaluation . . . . . . . . . . . . . . . . . . . . . 28 3.3.2 Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . 31 4 Cognitive Radio Automata Network 36 4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.2 Cognitive Radio Automata Network . . . . . . . . . . . . . . . . . . . 40 4.2.1 Automata Network . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2.2 Mean-Field Approximation . . . . . . . . . . . . . . . . . . . . 40 4.3 Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.3.1 Properties of Equilibriums . . . . . . . . . . . . . . . . . . . . 43 4.3.2 Mathematical Evaluation . . . . . . . . . . . . . . . . . . . . . 45 5 Conclusion and Future Works 48 Bibliography50 | |
| dc.language.iso | en | |
| dc.subject | 系統穩定度 | zh_TW |
| dc.subject | 感知無線電 | zh_TW |
| dc.subject | 生態學 | zh_TW |
| dc.subject | 捕食與被捕食模型 | zh_TW |
| dc.subject | 頻譜分享 | zh_TW |
| dc.subject | system stability | en |
| dc.subject | spectrum sharing | en |
| dc.subject | predator-prey model | en |
| dc.subject | ecology | en |
| dc.subject | Cognitive Radio (CR) | en |
| dc.title | 以生物模型探討認知無線網路之動態時變 | zh_TW |
| dc.title | Biological approaches to the Dynamics of Cognitive Radio
Networks | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 張進福,韓永祥,黃崇明 | |
| dc.subject.keyword | 感知無線電,生態學,捕食與被捕食模型,頻譜分享,系統穩定度, | zh_TW |
| dc.subject.keyword | Cognitive Radio (CR),ecology,predator-prey model,spectrum sharing,system stability, | en |
| dc.relation.page | 53 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2012-08-16 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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| ntu-101-1.pdf 未授權公開取用 | 2.5 MB | Adobe PDF |
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