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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林宗男(Tsung-Nan Lin) | |
| dc.contributor.author | Zan-Yu Chen | en |
| dc.contributor.author | 陳贊羽 | zh_TW |
| dc.date.accessioned | 2021-05-20T20:13:28Z | - |
| dc.date.available | 2009-07-24 | |
| dc.date.available | 2021-05-20T20:13:28Z | - |
| dc.date.copyright | 2009-07-24 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-22 | |
| dc.identifier.citation | [1] “IEEE standard for information technology-telecommunications and information
exchange between systems-local and metropolitan area networksspecific requirements - part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications,” IEEE Std 802.11-2007 (Revision of IEEE Std 802.11-1999), pp. C1–1184, 12 2007. [2] J. Camp and E. Knightly, “The IEEE 802.11s extended service set mesh networking standard,” Communications Magazine, IEEE, vol. 46, no. 8, pp. 120–126, August 2008. [3] D. Johnson, “Routing in ad hoc networks of mobile hosts,” Mobile Computing Systems and Applications, 1994. Proceedings., Workshop on, pp. 158–163, Dec 1994. [4] “Optimized link state routing protocol (olsr),” 2003. [5] C. Perkins and E. Royer, “Ad-hoc on-demand distance vector routing,” Mobile Computing Systems and Applications, 1999. Proceedings. WMCSA ’99. Second IEEE Workshop on, pp. 90–100, Feb 1999. [6] G. B.-S. A. D. Martin Heusse, Franck Rousseau, “Performance anomaly of 802.11b,” IEEE INFOCOM, 2003. [7] G. Holland, N. Vaidya, and P. Bahl, “A rate-adaptive mac protocol for multi-hop wireless networks,” in MobiCom ’01: Proceedings of the 7th annual international conference on Mobile computing and networking. NewYork, NY, USA: ACM, 2001, pp. 236–251. [8] A. Kamerman and L. Monteban, “Wavelan-ii: a high-performance wireless lan for the unlicensed band,” Bell Labs Technical Journal, vol. 2, no. 3, pp. 118–133, 1997. [Online]. Available: http://dx.doi.org/10.1002/bltj.2069 [9] S. H. Y. Wong, H. Yang, S. Lu, and V. Bharghavan, “Robust rate adaptation for 802.11 wireless networks,” in MobiCom ’06: Proceedings of the 12th annual international conference on Mobile computing and networking. New York, NY, USA: ACM, 2006, pp. 146–157. [10] D. Aguayo, J. Bicket, S. Biswas, G. Judd, and R. Morris, “Link-level measurements from an 802.11b mesh network,” SIGCOMM Comput. Commun. Rev., vol. 34, no. 4, pp. 121–132, 2004. [11] J. C. Bicket, “Bit-rate selection in wireless networks,” Master’s thesis, Department of EECS, MIT, February 2005, sampleRate. [12] M. Lacage, M. H. Manshaei, and T. Turletti, “IEEE 802.11 rate adaptation: a practical approach,” in MSWiM ’04: Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems. New York, NY, USA: ACM, 2004, pp. 126–134. [13] J. Kim, S. Kim, S. Choi, and D. Qiao, “CARA: Collision-aware rate adaptation for IEEE 802.11 WLANs,” in INFOCOM 2006. 25th IEEE International Conference on Computer Communications. Proceedings, Apr 2006, pp. 1–11. [14] D. S. Trrun Joshi, Disha Ahuja and I. Dharma P. Agrawal, Fellow, “Sara: Stochastic automata rate adaptation for IEEE 802.11 networks,” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, vol. 19, p. 11, 2008. [15] G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,” Selected Areas in Communications, IEEE Journal on, vol. 18, no. 3, pp. 535–547, Mar 2000. [16] http://www.scalablenetworks.com/, “Qualnet network modeler and simulator. [17] M. Haleem and R. Chandramouli, “Adaptive downlink scheduling and rate selection: a cross-layer design,” Selected Areas in Communications, IEEE Journal on, vol. 23, no. 6, pp. 1287–1297, June 2005. [18] P. Chatzimisios, A. Boucouvalas, and V. Vitsas, “Ieee 802.11 packet delaya finite retry limit analysis,” Global Telecommunications Conference, 2003. GLOBECOM ’03. IEEE, vol. 2, pp. 950–954 Vol.2, Dec. 2003. [19] K. Ramachandran, R. Kokku, H. Zhang, and M. Gruteser, “Symphony: synchronous two-phase rate and power control in 802.11 wlans,” pp. 132–145, 2008. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9220 | - |
| dc.description.abstract | In recent years, IEEE 802.11 wireless networks have become the most popular wireless technology. IEEE 802.11 supports multiple transmission rates. How to determine the appropriate transmission rate is challenging. In this paper, we propose a novel rate adaptation algorithm to tackle this problem. We utilize the maximum likelihood estimator to robustly predict the transmission statistics for each transmission rate. Then we exploit the cross-layer correlation between PHY and MAC to determine the transmission cost for each transmission rate. The goal of our design is to achieve the maximum spectral efficiency.
Based on extensive simulation experiments, the proposed algorithm outperforms existing well-known algorithms. Wireless mesh networks (WMNs) have experienced an enormous growth over the past few years. The performance of WMNs depends on the joint effect of both routing algorithms and rate adaptive algorithms. The performance of various routing algorithms has been studied extensively in the literature.However, little work has been done to evaluate the cross-layer impact of rate adaptive algorithms inWMN environments. In this paper, we compare the performance of several rate adaptive algorithms to exploit the multi-hop performance in WMN environments. In addition, a novel rate adaptive algorithm is proposed via the machine learning approach to robustly reflect the channel information. The goal of our design is to maximize the spectral efficiency. Through extensive computer simulations under different channel and topology environments, experimental results demonstrate the proposed algorithm outperforms other existing algorithms in WMN environments. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T20:13:28Z (GMT). No. of bitstreams: 1 ntu-98-R96942099-1.pdf: 512418 bytes, checksum: 405c4bffaa579de32bdfe6e4d71fc722 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | List of Figures iii
List of Tables v 1 Introduction 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Related Work 5 2.1 ARF and AARF . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 CARA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 RRAA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.4 SampleRate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.5 SLA and SARA . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 Proposed Algorithm 9 3.1 Cross-layer performance betweenMAC and PHY layers . . . . . . 9 3.2 AlgorithmDescription . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3 Maximum Likelihood Estimator . . . . . . . . . . . . . . . . . . . 13 4 Simulation Set-up 17 5 Simulation Results 19 5.1 Single Transmission Link with the Fixed Distance . . . . . . . . . 19 5.2 Single Transmission Link with Different Distances . . . . . . . . . 23 5.3 Multiple Static Stations in an InfrastructureMode . . . . . . . . . 24 5.4 MultipleMobile Stations in an InfrastructureMode . . . . . . . . 29 5.5 Topologies of Equal Distances . . . . . . . . . . . . . . . . . . . . 32 5.6 Topology ofMixed Distances . . . . . . . . . . . . . . . . . . . . . 35 6 Conclusions 41 Bibliography 43 | |
| dc.language.iso | en | |
| dc.title | 無線網路中以機器學習方法為基礎的新穎速率適應演算法 | zh_TW |
| dc.title | A Novel Rate Adaptation Algorithm via Machine Learning Approaches for Wireless Networks | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳俊良,蔡子傑 | |
| dc.subject.keyword | 自應性調速,速率控制,無線網路,IEEE 802.11,WMN, | zh_TW |
| dc.subject.keyword | rate adaptation,rate control,wireless network,IEEE 802.11,WMN, | en |
| dc.relation.page | 45 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2009-07-22 | |
| 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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