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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/29118完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張進福(Jin-Fu Chang) | |
| dc.contributor.author | Min Her | en |
| dc.contributor.author | 何敏 | zh_TW |
| dc.date.accessioned | 2021-06-13T00:41:07Z | - |
| dc.date.available | 2011-08-08 | |
| dc.date.copyright | 2011-08-08 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-04 | |
| dc.identifier.citation | [1] Yang Xiao, Fei Hu, ‘‘Cognitive Radio Networks’’, 2009 by Taylor & Francis Group, LLC
[2] wikipedia, “IEEE 802.22”, 2011, http://en.wikipedia.org/wiki/IEEE_802.22 [3] Anh Tuan Hoang, Ying-Chang Liang, David Tung Chong Wong, Rui Zhang, and Yonghong Zeng Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, “Opportunistic Spectrum Access for Energy-constrained Cognitive Radios” ,Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE . [4] C. D. Jones, A. B. Smith, and E.F. Roberts, Book Title, Publisher, Location, Date. R. C. Gonzalez, R. E. Woods, Digital Image Processing second edition, Prentice Hall, 2002 [5] Y. Chen, Q. Zhao, and A. Swami, “Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors,” IEEE Trans. Inf. Theory, vol. 54, pp. 2053–2071, May 2008. [6] Q. Zhao, L. Tong, A. Swami, and Y. Chen, “Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework,” IEEE J. Sel. Areas Commun. (JSAC): Special Issue on Adapt., Spectrum Agile and Cogn. Wireless Networks, vol. 25, no. 3, pp. 589–600, Apr. 2007. [7] Tao Jiang, David Grace, “Performance of Cognitive Radio Reinforcement Spectrum Sharing Using Different Weighting Factors” Yiming Liu Communication Research Group, Department of Electronics, University of York, York, YO10 5DD, United Kingdom [8] Sen Song, Kenneth D. Miller* and L. F. Abbott, “Competitive Hebbian Learning Through Spike-Timing-Dependent Synaptic Plasticity”, Volen Center for Complex [9] J. Mitola, “Cognitive radio: an integrated agent architecture for software defined radio,” Ph.D. dissertation, KTH, Stockholm, Sweden, Dec. 2000. [10] A. Sahai, N. Hoven, S. M. Mishra, and R. Tandra, “Fundamental tradeoffs in robust spectrum sensing for opportunistic frequency reuse,” Technical Report, Mar. 2006. Available online at http://www.eecs.berkeley.edu/∼sahai/Papers/CognitiveTechReport06.pdf. [11] N. Hoven and A. Sahai, “Power scaling for cognitive radio,” Wireless- Com Symposium on Emerging Networks, Technologies and Standards, 2005. [12] S. Srinivasa and S. A. Jafar, “The throughput potential of cognitive radio: a theoretical perspective,” IEEE Commun. Mag., May 2007. [13] S. A. Jafar and S. Srinivasa, “Capacity limits of cognitive radio with distributed and dynamic spectral activity,” IEEE J. Sel. Areas Commun., vol. 25, pp. 529–537, Apr. 2007. [14] Srinivasa, S.; Jafar, S.A.; , 'Soft Sensing and Optimal Power Control for Cognitive Radio,' Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE , vol., no., pp.1380-1384, 26-30 Nov. 2007 [15] http://www.fiberwaves.com/prodetail.asp?ID=4 [16] C. T. Chen;, “Regulation and Technology Trends of TV White space”, NCP Newsletter, No. 26, April 2011 [17] Lijun Qian; Xiangfang Li; Attia, J.; Gajic, Z.; , 'Power Control for Cognitive Radio Ad Hoc Networks,' 15th IEEE Workshop on Local & Metropolitan Area Networks, 2007. LANMAN 2007., vol., no., pp.7-12, 10-13 June 2007 Systems and Department of Biology Brandeis University March 31, 2000 [18] J.G. Proakis, Digital Communications, fourth ed. McGraw Hill, 2001. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/29118 | - |
| dc.description.abstract | 在感知型無線電環境下,我們用三種技術去做傳輸且使得次要傳輸者的傳輸可以達到最佳化且限制對主要傳輸者的碰撞,其中包含重疊式傳輸,隱匿是傳輸,和結合重疊式傳輸和隱匿式傳輸的方法。
在知道主要傳輸者們的平均動作但不知道確切動作的條件下,我們用重疊式傳輸的方法來傳輸資料。我們用主要傳輸者的電視使用率分佈曲線和特性分佈曲線去找到一個最佳的封包長度來達到最好的吞吐量。 在次要傳輸者不知道主要傳輸者有沒有再使用通道但知道主要傳輸者的確切位置的條件下,我們用星球學理軌道的觀念和隱匿式的傳輸方法來找到最少的中繼點數和最佳的路徑。 在次要傳輸者能經由偵測漏電功率來知道主要使用者的確切動作的條件下,我們用結合重疊式和隱匿式的方法來傳送資料。經由感測主要使用者的漏電功率,次要使用者可以調整他的功率來達到最大的訊雜比和最大的容量。 | zh_TW |
| dc.description.abstract | In a cognitive radio network system with a collision constraint of primary user, approaches using the overlay, underlay, or the combination of the underlay and overlay methods have been purposed to optimize the transmission of the secondary user.
Under the condition that the secondary user knows the general actions but not the exact actions of the primary users, an overlay method was purposed. In this overlay method, both the TV utility distribution (TUD) and the characteristic distribution (CD) of primary users were used to find an optimal frame length with highest throughput. Under the condition that the secondary user has no idea whether the primary user is using the channel or not but knows the exact locations of primary users, an underlay method based on the concept of orbits in astronomy was developed to find the least number of relay and the optimal routing. Under the condition that the secondary user can have the exact actions of the primary user by detecting the leakage power of primary user, an approach utilized both the overlay and underlay method was purposed. By sensing the leakage power of the primary user, the power transmitted by secondary user was adjusted to maximize the SNR and the capacity of the secondary user. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T00:41:07Z (GMT). No. of bitstreams: 1 ntu-100-R98942126-1.pdf: 2321462 bytes, checksum: f4e132d07da9135d46287e750865de3c (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i ABSTRACT ii CONTENTS iii LIST OF FIGURES vi Chapter 1 Introduction 1 1.1 Cognitive radio 1 1.1.1 Secondary users 2 1.1.2 Spectrum sensing and detection 2 1.1.3 Spectrum sharing 3 1.1.4 Spectrum access 4 1.2 802.22 5 1.3 Motivation 7 1.3.1 The optimal frame length 7 1.3.2 Power adaptation with sensed leakage power 8 1.3.3 The adoption of relay 9 1.4 Conclusion Remarks 9 Chapter 2 Collision avoidance in cognitive radio network 11 2.1 Collision avoidance 11 2.1.1 Acknowledgment 12 2.1.2 Reward and Penalty 13 2.1.3 Hebbian learning 13 2.2 System model 13 2.2.1 Common used method 14 2.2.2 Structure 15 2.3 Algorithm 19 2.3.1 Optimal packet length 21 2.4 Simulation results and Discussions 22 2.5 Conclusion 32 Chapter 3 Indoor adaptive power control 33 3.1 Primary receiver detection 33 3.1.1 Local oscillator leakage power 34 3.1.2 Soft decision 35 3.2 System model 35 3.2.1 Structure 36 3.3 Algorithm 38 3.3.1 Power adaptation with maximum SNR 39 3.3.2 Power adaptation with maximum capacity 41 3.4 Simulation results 45 3.4.1 Results of power adaptation with maximum SNR 46 3.4.2 Results of power adaptation with maximum capacity 50 3.5 Conclusion 52 Chapter 4 Topology control in cognitive radio network 54 4.1 Topology control 54 4.2 System model 57 4.2.1 Structure 57 4.2.2 Reducing power consumption 63 4.2.3 Optimal routing and sub-optimal routing 64 4.3 Algorithm 66 4.4 Simulation results 69 4.4.1 Success rate 73 4.5 Conclusion 74 Chapter 5 Conclusion 76 REFERENCE 78 | |
| dc.language.iso | en | |
| dc.subject | 隱匿式傳輸 | zh_TW |
| dc.subject | 感知型無線電 | zh_TW |
| dc.subject | 重疊式傳輸 | zh_TW |
| dc.subject | cognitive radio | en |
| dc.subject | underlay | en |
| dc.subject | overlay | en |
| dc.title | 在感知無線電下的重疊式和隱匿式傳輸 | zh_TW |
| dc.title | Underlay and Overlay Transmission in Cognitive Radio | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 魏學文,金力鵬 | |
| dc.subject.keyword | 感知型無線電,重疊式傳輸,隱匿式傳輸, | zh_TW |
| dc.subject.keyword | cognitive radio,underlay,overlay, | en |
| dc.relation.page | 79 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-04 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位: | 電機工程學系 | |
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