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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳健輝 | |
dc.contributor.author | Shang-Ching Hung | en |
dc.contributor.author | 洪上清 | zh_TW |
dc.date.accessioned | 2021-06-13T05:53:44Z | - |
dc.date.available | 2009-07-05 | |
dc.date.copyright | 2006-07-05 | |
dc.date.issued | 2006 | |
dc.date.submitted | 2006-07-03 | |
dc.identifier.citation | 6 Reference
[1] Khaleghi A., Azoulay A., Bolomey J.C., “Evaluation of diversity antenna characteristics in narrow band fading channel using random phase generation process”, proceedings of IEEE Vehicular Technology Conference, pp.257-261, May 2005 [2] Kurt T., Le Helloco Y., Breton B., “Wideband Local Mean Estimation”, IEE Electronic Letters, pp.165-167, Feb. 2006. [3] J. Lansford, 'UWB Coexistence and Cognitive Radio', proceedings of IEEE Conference on Ultrawideband Systems and Technologies, pp.35 - 39, 2004. [4] 802.11a wireless LAN medium access control (MAC) and physical layer (PHY) specifications amendment 1: high-speed physical layer in the 5 GHz band, IEEE Std. 802.11a, 1999. [5] Loskot P., Beaulieu N.C., “A family of low-complexity binary linear codes for Bluetooth and BLAST signaling applications”, IEEE Communication letters, pp.1061-1063, Dec. 2005. [6] Siriwongpairat W.P., Weifeng Su, Olfat M., Liu K.J.R., “Multiband-OFDM MIMO coding framework for UWB communication systems”, IEEE Transactions on Signal Processing, pp.214-224, Jan. 2006. [7] Danijela Cabric, Shridhar Mubaraq Mishra, and Robert W. Brodersen, 'Implementation Issues in Spectrum Sensing for Cognitive Radios“, proceedings of Thirty-Eighth Asilomar Conference, pp.772-776, 2004. [8] Chakravarthy V.D., Shaw A.K., Temple M.A., Stephens J.P., “Cognitive radio - an adaptive waveform with spectral sharing capability”, proceedings of IEEE Wireless Communications and Networking Conference (WCNC), pp.724-729, March 2005. [9]Simon M., Dolinar S., “Signal-to-noise ratio estimation for autonomous receiver operation”, IEEE Global Telecommunications Conference, pp. 282-287, Nov. 2004. [10] A. Hills, B Fridaiy, “Radio resource management in wireless LANs”, IEEE Communications Magazine, pp.S9-14, Dec. 2004. [11] Howitt I., “WLAN and WPAN coexistence in UL band”, proceedings of IEEE Transactions on Vehicular Technology, pp. 1114 – 1124, July 2001. [12] Qian Zhang, Chuanxiong Guo, Zihua Guo, Wenwu Zhu, “Efficient mobility management for vertical handoff between WWAN and WLAN”, IEEE Communications Magazine, pp. 102 – 108, Nov. 2003. [13] Santivanez C., Stavrakakis I., “Study of various TDMA schemes for wireless networks in the presence of deadlines and overhead”, IEEE Journal on Selected Areas in Communications, pp. 1284 – 1304, July 1999. [14] Mitola, 'Cognitive Radio an Integrated Agent Architecture forSoftware Defined Radio' Doctorial Thesis, 2000. [15] Simon Haykin, Life Fellow, IEEE, 'Cognitive Radio: Brain-Empowered Wireless Communications', IEEE Journal on Selected Areas in Communication, pp. 201-220, 2005. [16] Marcus M.J., “Unlicensed cognitive sharing of TV spectrum: the controversy at the Federal Communications Commission”, IEEE Communication Magazine, pp.24-25, May 2005. [17] Babu T.V.J.G., Anpalagan A., Hayes J.F., “A study of DiffServ based QoS issues in next generation mobile networks”, proceedings of Electrical and Computer Engineering Canadian Conference, pp 2359-2362, May 2004. [18] Krenik W., Batra A., “Cognitive radio techniques for wide area networks”, proceedings of Design Automation Conference, pp.409-412, June 2005. [19] Thomas W. Rondeau, Christian J. Rieser, Timothy M. Gallagher, and Charles W. Bostian, 'Online Modeling of Wireless Channel with Hidden Markov Models and Channel Impulse Response for Cognitive Radio', proceeding of IEEE MTT-S International, pp. 739-742,2004. [20] Massey W.A., Ramakrisluian K.G., Aravamudan M., Pai G., ”Scheduling algorithms for downlink services in wireless networks: a Markov decision process approach”, proceedings of IEEE Global Telecommunications Conference, pp.4038-4042, Nov. 2004. [21] J. Neel, R. M. Buehrer, J. H. Reed, R. P. Gills, 'Game Theoretic Analysis of a Network of Cognitive Radio', Circuits and Systems, MWSCAS-2002 IEEE, vol 3, pp.409-412, 2002. [22] Neel J.O., Reed J.H., Gilles R.P., “Convergence of cognitive radio networks”, proceedings of IEEE Wireless Communications and Networking Conference (WCNC), pp. 2250-2255, March 2004. [23] Rieser C.J., Rondeau T.W., Bostian C.W., Gallagher T.M., “Cognitive radio testbed: further details and testing of a distributed genetic algorithm based cognitive engine for programmable radios”, IEEE Military Communications Conference, pp. 1437-1443, 2004. [24] Haleem M.A., Chandramouli R., “Adaptive stochastic iterative rate selection for wireless channels”, IEEE Communications Letters, pp. 292-294, May 2004. [25] Tang C., Stolpman V., “An adaptive learning approach to adaptive OFDM”, Wireless Communications and Networking Conference (WCNC), pp. 1406-1410, March 2004. [26] The Network Simulator - ns2, http://www.isi.edu/nsnam/ns. [27] IEEE Std 802.11-1997 Information Technology- telecommunications And Information exchange Between Systems-Local And Metropolitan Area Networks-specific Requirements-part 11: Wireless Lan Medium Access Control (MAC) And Physical Layer (PHY) Specifications, IEEE Std. 802.11, 1997. [28] Supplement To IEEE Standard For Information Technology- Telecommunications And Information Exchange Between Systems- Local And Metropolitan Area Networks- Specific Requirements- Part 11: Wireless LAN Medium Access Control (MAC) And Physical Layer (PHY) Specifications: Higher-speed Physical Layer Extension In The 2.4 GHz Band, IEEE Std. 802.11b, 1999. [29] Walko J., “Cognitive radio”, IEE Review, pp.34-47, May 2005. [30] Yamaguchi H., “Active interference cancellation technique for MB-OFDM cognitive radio”, proceedings of Microwave Conference 34th European, pp.1105-1108, Oct. 2004. [31] J. Lansford, 'UWB Coexistence and Cognitive Radio', proceedings of IEEE Conference on Ultrawideband Systems and Technologies, pp.35 - 39, 2004. [32] Taesoo Kwon, Dong-Ho Cho, “Adaptive radio resource management based on cell load in CDMA-based hierarchical cell structure”, proceedings of IEEE Vehicular Technology Conference, pp.2337-2341, Sept. 2002. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34083 | - |
dc.description.abstract | 隨著無線網路技術的發展,造成了所制定的許多無線網路標準必須共享無線傳輸頻帶。然而另一方面,也因為許多不穩定的資料流採用最高需求流量和許多爆發性的資料現象,造成在大部分的時間,頻道的使用率是相當低的。因此,無線傳輸頻道的這項資源是相當珍貴的,而技術關於提昇或是平衡頻道的使用率也被高度地重視。感知無線電(Cognitive Radio)技術於是被發展來解決這項問題。感知無線電的技術包含了許多範圍,包括不被察覺地使用頻帶的空檔、學習使用者之行為、自動調整以適應外在環境的變化等。這篇論文提出了一個可以確保主要使用者傳輸品質的感知借取演算法(cognitive borrowing algorithm)。在可以掃描環境的前提之下,若採用這個演算法,感知無線電通訊可以增加頻帶的使用率,並且對主要使用者只產生極小傷害。此外,此演算法還有分散式系統、適應性、低運算複雜度、和公平性等等優點。 | zh_TW |
dc.description.abstract | With the fast development of wireless technology, a lot of user demands rely on wireless communication. Therefore, many wireless network standards are developed for certain purpose and that causes the radio frequency spectrums of the standards to have the overlap part. On the other hand, because of the usage of many requests from instable multimedia traffic and some user behavior of bursted traffic, the utilization of the channel might be low in most of the time. Therefore, the limited radio frequency spectra are treasurable. Issues about increasing or balancing spectrum utilization become more important. Moreover, issues about using spectrum holes have also been focused. CR (Cognitive Radio) technology is now developing for solving this critical problem. CR device is able to use a large range of frequency spectrum. The goal of CR is raise the channel utilization without influencing the original users. CR technology includes many aspects of researches, such as reusing spectrum holes invisibly, learning form users’ behavior, adjusting changes form the environment automatically. This thesis gives out a cognitive borrowing algorithm which can ensure the QoS of primary users. By using this algorithm with environment scanning capability, CR traffics increase the utilization of the channel with only rare damage to prior users. Moreover, the algorithm has the advantages of decentralized system, flexibility, low computing complexity, and fairness. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T05:53:44Z (GMT). No. of bitstreams: 1 ntu-95-R93922139-1.pdf: 611898 bytes, checksum: 92e3160506a180b050ae2bcda663f4df (MD5) Previous issue date: 2006 | en |
dc.description.tableofcontents | Contents
Abstract 5 中文摘要 6 1 Introduction 7 1.1 Importance of Channel Utilization 7 1.2 Traditional Ways to Raise Channel Utilization 9 1.3 Cognitive Radio 14 2 Related Works 18 2.1 Active Groups and Ongoing Researches about CR 18 2.2 Channel Modeling Researches 19 2.3 Channel State Learning 22 3 Proposed Cognitive Borrowing Algorithm 25 3.1 Decentralized CR System 25 3.2 Cognitive Borrowing algorithm 28 3.3 Historical Maintenance and Complexity analysis32 3.4 Fairness 33 4 Simulation Results 36 5 Conclusion 55 6 Reference 56 | |
dc.language.iso | en | |
dc.title | 應用於競爭性無線網路之不易被偵測感知無線電方案 | zh_TW |
dc.title | Insensible CR Scheme for Contention-based Wireless Network | en |
dc.type | Thesis | |
dc.date.schoolyear | 94-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳曉光,周承復,胡家正 | |
dc.subject.keyword | 感知無線電, | zh_TW |
dc.subject.keyword | cognitive radio, | en |
dc.relation.page | 61 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2006-07-04 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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