請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47573
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林宗男(Tsung-Nan Lin) | |
dc.contributor.author | Tsung-Hsun Chien | en |
dc.contributor.author | 簡琮訓 | zh_TW |
dc.date.accessioned | 2021-06-15T06:06:38Z | - |
dc.date.available | 2010-08-20 | |
dc.date.copyright | 2010-08-20 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-08-15 | |
dc.identifier.citation | [1] Z. H. Ekram Hossain, Dusit Niyato, Dynamic Spectrum Access and Manage-ment in Cognitive Radio Networks. Cambridge University Press, 2009.
[2] F. S. P. T. Force, “Report of the spectrum efficiency working group,” Tech. Rep., Tech. Rep., Nov. 2002. [3] I. Mitola, J. and J. Maguire, G.Q., “Cognitive radio: making software radios more personal,” Personal Communications, IEEE, vol. 6, no. 4, pp. 13 –18, aug 1999. [4] J. Mitola, “Cognitive radio: An integrated agent architecture for software defined radio,” Ph.D. dissertation, Royal Institute of Technology (KTH), Sweden, May, 2000. [5] S. Haykin, “Cognitive radio: Research challenges,” McMaster, University, Tech. Rep., 2008. [6] Haykin, “Cognitive radio: brain-empowered wireless communications,” Selected Areas in Communications, IEEE Journal on, vol. 23, no. 2, pp. 201 – 220, feb. 2005. [7] “1st international workshop on green wireless,” Tech. Rep., 2008. [8] E. Press, Ericsson Press, Tech. Rep., June 2008. [9] D. Fudenberg and J. Tirole, Game Theroy. The MIT Press, Cambridge, Aug. 1991. [10] S. Mehta and K. Kwak, “Game theroy and cognitive radio based wireless networks,” Springer, pp. 803–812, 2009. [11] J. N. Vivek Srivastava, “Using game theroy to analysis wireless ad hoc networks.” [12] J. O. Neel, “Analysis and design of cognitive radio networks and distributed radio resource management algorithms,” Ph.D. dissertation, Virginia Polytechnic Institute and State University, Sep. 2006. [13] L. S. S. Dov Monderer, “Potential games,” Games and Economic Behavior 14, pp. 124–143, 1996. [14] N. Nie and C. Comaniciu, “Adaptive channel allocation spectrum etiquette for cognitive radio networks,” IEEE, pp. 269 –278, 8-11 2005. [15] E. Del Re, G. Gorni, L. Ronga, and R. Suffritti, “A power allocation strategy using game theory in cognitive radio networks,” IEEE, pp. 117 –123, 13-15 2009. [16] S. Gunturi and F. Paganini, “Game theoretic approach to power control in cellular cdma,” in Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th, vol. 4, 6-9 2003, pp. 2362 – 2366 Vol.4. [17] J. Xiang, Y. Zhang, and T. Skeie, “Joint admission and power control for cognitive radio cellular networks,” in Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on, 19-21 2008, pp.1519 –1523. [18] L. S. R. R. S. Enrico Del Re, Gherardo Gorni, “Resource allocation in cognitive radio networks: a comparisonry based and heuristic approaches,” Wireless Pers. Commun, Springer, vol. 49, pp. 375–390, 2009. [19] F. Xu, L. Zhang, Z. Zhou, and Q. Liang, “Adaptive power control for cooperative uwb network using potential game theory,” in Wireless Communications and Networking Conference, 2007.WCNC 2007. IEEE, 11-15 2007, pp.1620 –1624. [20] R. Menon, A. MacKenzie, R. Buehrer, and J. Reed, “Joint power control and waveform adaptation for distributed networks,” in Global Telecommunications Conference, 2007. GLOBECOM ’07. IEEE, 26-30 2007, pp. 694–699. [21] P. K. Dutta, Strategies and Games, Theory and Practice. The MIT Press, Cambridge, 1999. [22] J.-P. H. Mark Felegyhazi, “Game theory in wireless networks: A tutorial,” Tech. Rep., 2007. [23] “http://en.wikipedia.org/wiki/round-robin.” [24] A. B. M. James Hicks, “A convergence result for potential games,” 2004. [25] H. N. Mark Voorneveld, “A characterization of ordinal potential games,” Games and Economic Behavior 19, pp. 235–242, 1997. [26] A. B. MacKenzie and L. A. DaSilva, Game Theory for Wireless Engineers. Morgan & Claypool Publishers, 2006. [27] M. Voorneveld, “Best-response potential games,” Economics Letters, pp. 289–295, 2000. [28] A. P. David Dragone, Luca Lambertini, “A class of best-response potential games.” [29] J. Neel, “How does game theoy apply to radio resource management?” Virginia Polytechnic Institute and State University, Tech. Rep. [30] “Potential games: Theory and application in wireless networks,” Department of Computer Science, University of British Columbia, Tech. Rep., 2008. [31] J. G. Proakis, Digital Communications. McGraw Hill, 2001. [32] Y. Zhao, S. Mao, J. Neel, and J. Reed, “Performance evaluation of cognitive radios: Metrics, utility functions, and methodology,” Proceedings of the IEEE, vol. 97, no. 4, pp. 642 –659, april 2009. [33] “Ieee recommended practice for information technology - telecommunications and information exchange between systems - local and metropolitan area networks - specific requirements part 15.2: Coexistence of wireless per-sonal area networks with other wireless devices operating in unlicensed frequency bands,” IEEE Std 802.15.2-2003, Tech. Rep., 2003. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47573 | - |
dc.description.abstract | 近幾年感知無線電(Cognitive Radio, CR)被視為極具潛力的無線通訊應用。在本篇論文中,提出的演算法是基於賽局理論中的潛在賽局,並在感知無線電網路中使用調適性功率控制來解決網路吞吐量與使用者因過大傳輸功率造成的相互干擾問題。模擬的環境是分散式與合作式傳輸模型,由一個主要使用者與數個次要使用者使用Ad-Hoc模式在相同傳輸通道下組成。在演算法的架構下,沒有任何次要使用者會使用過大的傳輸功率來增加自己的SINR,演算法會驅使所有次要使用者收斂到奈許平衡點(Nash Equilibrium)。三個功率指標會在演算法中會被個別考慮到。第一個和主要使用者的SINR需求有關;第二個功率考慮到次要使用者的SINR需求;第三個功率指標從潛在賽局中所提出的效用函數得到。由於從效用函數中得到的最佳響應未必能實際應用在感知無線電的環境中,於是演算法流程明確地用特定限制條件分類來使用適合的功率指標,並改善在潛在賽局中的最佳收斂響應。因此,演算法提供次要使用者更健全的決策方法有效地使網路吞吐量增加與相互干擾的問題減少,而且使用者會選擇合適的傳輸功率,避免不必要的功率浪費。本論文提出的演算法能達到節省功率的效果,也適合應用在綠色通訊上與有效的動態頻譜分配改善頻譜使用情況。
關鍵字:感知無線電; 軟體定義無線電; 賽局理論; 潛在賽局; 功率控制; 綠色通訊 | zh_TW |
dc.description.abstract | In recent years, Cognitive Radio(CR) is a potential application in wireless communications. The algorithm, which uses Potential Game, proposed in this thesis solving the throughput and mutual interference problems, caused by excess transmission power, with adaptive power control in Cognitive Radio networks. The simulation environment is distributive and cooperative transmission model, which is composed of a primary users and some secondary users on the same channel with Ad-Hoc mode. Under the algorithm architecture, no user would choose excess power to gain their own larger SINR. The algorithm would make all secondary users converge to Nash Equilibrium. In addition, three power levels is concerned. First, power from primary user’s SINR requirement. Second, secondary user’s SINR requirement power. Third, the power obtained from utility function in Potential Game. The algorithm flow clearly classify with specific constraints to choose suitable power levels and improve Best Response Convergence in Potential Game due to the best response in utility function is not always established in real Cognitive Radio environment. Therefore, the algorithm provides secondary users with more robust decision making to efficiently cope with increment of throughput and decrement of mutual interference. Secondary users would choose proper power level to avoid power waste. The algorithm in this thesis can facilitate power saving and is available for Green Communications and dynamic spectrum access(DSA) in efficient spectrum utilization.
key words: Cognitive Radio; Software Defined Radio; Game Theory; Potential Game; Power Control; Green Communications | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T06:06:38Z (GMT). No. of bitstreams: 1 ntu-99-R97942133-1.pdf: 1019819 bytes, checksum: 4052fb0ea4713acd9a61be3b7882f9f0 (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | List of Figures iii
List of Tables v 1 Introduction 1 1.1 Dynamic Spectrum Access . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Cognitive Radio and Green Communications . . . . . . . . . . . . 3 1.3 Game Theory and Wireless Communications . . . . . . . . . . . . 4 1.4 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.5 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2 Game Theory and Potential Game . . . . . . . . . 7 2.1 Introduction to Game Theory . . . . . . . . . . . . . . . . . . . . 7 2.2 Introduction to Potential Game . . . . . . . . . . . . . . . . . . . 10 2.2.1 Exact Potential Game . . . . . . . . . . . . . . . . . . . . 11 2.2.2 Weighted Potential Game . . . . . . . . . . . . . . . . . . 12 2.2.3 Ordinal Potential Game . . . . . . . . . . . . . . . . . . . 12 2.3 Better Response Convergence and Best Response Convergence . . . . . . . . . 13 3 Problem Formulation . . . . . . . . . 15 3.1 System Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2 Proof of Potential Game . . . . . . . . . . . . . . . . . . . . . . . 19 3.3 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.3.1 Basic Information . . . . . . . . . . . . . . . . . . . . . . . 21 3.3.2 Channel Gain Information . . . . . . . . . . . . . . . . . . 22 3.3.3 Primary User’s Interference . . . . . . . . . . . . . . . . . 22 3.3.4 Secondary User’s Power Selection . . . . . . . . . . . . . . 24 4 Proposed Algorithm . . . . . . . . . 26 4.1 Introduction to Proposed Algorithm . . . . . . . . . . . . . . . . . 27 4.1.1 Less Interference for Primary User with Random Power . . 28 4.1.2 Less Interference for Primary User with Round Robin Power 30 4.1.3 Exceeded Interference for Primary User . . . . . . . . . . . 36 5 Simulation Results and Discussion 43 5.1 Evaluation of Potential Game . . . . . . . . . . . . . . . . . . . . 44 5.1.1 Evaluation of Utility and Potential Function . . . . . . . . 44 5.1.2 Evaluation of Exact Potential Game . . . . . . . . . . . . 46 5.1.3 Evaluation of Round Robin Scheduling . . . . . . . . . . . 48 5.2 Evaluation of the Proposed Algorithm . . . . . . . . . . . . . . . 50 5.2.1 Evaluation of Throughput Improvement . . . . . . . . . . 50 5.2.2 Evaluation of Interference Reduction . . . . . . . . . . . . 52 6 Conclusions 68 | |
dc.language.iso | en | |
dc.title | 在感知網路中使用潛在賽局的動態頻譜分配 | zh_TW |
dc.title | Dynamic Spectrum Access in Cognitive Radio Networks Using
Potential Game | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳俊良(Jiann-Liang Chen),蔡子傑(Tzu-Chieh Tsai),魏宏宇(Hung-Yu Wei) | |
dc.subject.keyword | 感知無線電,軟體定義無線電,賽局理論,潛在賽局,功率控制,綠色通訊, | zh_TW |
dc.subject.keyword | Cognitive Radio,Software Defined Radio,Game Theory,Potential Game,Power Control,Green Communications, | en |
dc.relation.page | 71 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-08-16 | |
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 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-99-1.pdf 目前未授權公開取用 | 995.92 kB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。