請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47390
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 闕志達(Tzi-Dar Chiueh) | |
dc.contributor.author | Chia-Yu Chang | en |
dc.contributor.author | 張家瑜 | zh_TW |
dc.date.accessioned | 2021-06-15T05:57:43Z | - |
dc.date.available | 2012-08-18 | |
dc.date.copyright | 2010-08-18 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-08-16 | |
dc.identifier.citation | [1] Telecommunications Industry Association, “2010 ICT Market Review and Forecast,” Jan. 2010.
[2] 財團法人台灣網路資訊中心, “2010年1月台灣網路使用調查報告,” Jan. 2010. [3] Intel My WiFi Technology. http://www.intel.com/network/connectivity/products/wireless/mywifi.htm [4] Harry L. Van Trees, Detection, Estimation, and Modulation theory, Vol. 4: Optimum Array Processing. New York, NY: John Wiley & Sons, Inc., 2002. [5] J. Capon, “High-resolution Frequency-wavenumber Spectrum Analysis,” Proc. of the IEEE, Vol .57, No. 8, pp. 1408-1418, August 1969. [6] D. D. Feldman and L. J. Griffiths, “A Projection Approach for Robust Adaptive Beamforming,” IEEE Trans. on Signal Processing, Vol. 42, No. 4, pp. 867-876, April 1994. [7] T. W. Anderson, “Asymptotic Theory for Principal Component Analysis,” Ann. of Mathematical Statistics, Vol. 34, No. 1, pp. 128-148, March 1963. [8] H. Akaike, “A New Look at the Statistical Model Identification,” IEEE Trans. on Automation and Control, Vol. 19, No. 6, pp. 716-723, Dec. 1974. [9] G. Schwartz, “Estimating the Dimension of A Model,” Ann. of Statistics, Vol.6, No. 2, pp. 461-464, March 1978. [10] K. M. Wong, Q. Zhang, J. P. Reilly and P. C. Yip, ”On Information Theoretic Criteria for Determining the Number of Signals in High Resolution Array Processing,” IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. 38, No. 11, pp.1959-1971, Nov. 1990. [11] R. O. Schmidt, “Multiple Emitter Location and Signal Parameter Estimation,” IEEE Trans. on Antennas and Propagation, Vol. 34, No. 3, pp. 276-280, March 1986. [12] R. Roy and T. Kailath, “Estimation of Signal Parameters via Rotational Invariance Techniques,” IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. 37, No. 7, pp. 984-995, July 1989. [13] X. Zhou, H. M. Jones, S. Durrani and H. M. Jones, “Connectivity of Ad hoc Networks: Is Fading Good or Bad?” in Proc. of the 2nd International Conference on Signal Processing and Communication Systems (ICSPCS), Gold Coast, Austraila, Dec. 2008, pp. 1-5. [14] R. A. Iltis, S. J. Kim and D. Hoang, “Noncooperative Iterative MMSE Beamforming Algorithms for Ad Hoc Networks,” IEEE Trans. on Communications, Vol. 54, No. 4, pp.748 - 759, April 2006. [15] V. Erceg, et al., “TGn Channel Models,” IEEE 802.11-03/940r4, May 2004. [16] C. Komninakis, “A Fast and Accurate Rayleigh Fading Simulator,” in Proc. of IEEE Conf. on Global Telecomunications, San Francisco, USA, Dec. 2003, pp.3306 - 3310. [17] K. Steiglitz, “Computer-aided Design of Recursive Digital Filters,” IEEE Trans. on Audio and Electroacoustics, Vol. 18, No. 2, pp. 123-129, June 1970. [18] M. Tomlinson, “New Automatic Equaliser Employing Modulo Arithmetic,” Electronics Letters, Vol. 7, No. 5, pp. 138-139, March 1971. [19] H. Harashima and H. Miyakawa, “Matched-transmission Technique for Channels with Intersymbol Interference,” IEEE Trans. on Communications, Vol. 20, No. 4, pp. 774-780, August 1972. [20] M. Joham, “Optimization of Linear and Nonlinear Transmit Signal Processing,” Ph.D. dissertation, Department of Electrical Engineering and Information Technology, Technical University of Munich, Munich, Germany, 2004. [21] Y. Silva, “Adaptive Beamforming and Power Allocation in Multi-carrier Multicast Wireless Networks,” Ph.D. Dissertation, Department of Electrical Engineering and Information Technology, Darmstadt University of Technology, Darmstadt, Germany, 2008. [22] M. Schubert and H. Boche, “Solution of the Multiuser Downlink Beamforming Problem with Individual SINR Constraint,” IEEE Trans. on Vehicular Technology, Vol. 53, No. 1, pp. 18-28, Jan. 2004. [23] N. D. Sidiropoulos, T. N. Davidson, and Z.-Q. Luo, “Transmit Beamforming for Physical-layer Multicasting,” IEEE Trans. on Signal Processing, Vol. 54, No. 6, pp. 2239-2251, June 2006. [24] J. F. Sturm, “Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones,” Optimization Methods and Software, Vol. 11, pp. 625-653, 1999. [25] J. Löfberg, “YALMIP: A toolbox for modeling and optimization in Matlab,” in Proc. of IEEE Computer-Aided Control System Design Conf., Taipei, Taiwan, Sep. 2004, pp.284-289. [26] P. Lancaster, “On Eigenvalues of Matrices Dependent on A Parameter,” Numerische Mathematik, Vol. 6, pp. 377-387, May 1964. [27] X. Chen, H. Qi, L. Qi and K.-L. Teo, “Smooth Convex Approximation to the Maximum Eigenvalue Function,” Journal of Global Optimization, Vol. 30, No. 2, pp. 253-270, Nov. 2004. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47390 | - |
dc.description.abstract | 無線隨意網路隨著無線通訊的日新月異發展,也逐漸成為另一項無線網路的重要應用範疇,由於建構此種網路的過程中不需要額外的基礎建設,因此,此種網路適合建構於缺乏基礎設施之地區;並且,由於此網路之分散式控制結構可以提供不同於一般無線網路之強建的特點。所以無線隨意網路也近年來已逐漸蓬勃的發展,逐漸成為除了一般無線網路之外的另外一種不同的未來無線通訊發展之新方向。
在本論文當中,將針對無線隨意網路之特性,並且依據802.11的隨意模式,建構出此種網路之運作流程,並且依據運作流程中的兩種傳播方式:單一播送以及多重播送方式,建立起聯合傳送端與接收端之波束成型設計模式。由於無線隨意網路不同於一般的傳統無線網路,缺少了具有控制力的接取點或是基地台存在於網路當中,也常常造成了不必要的能量消耗。因此,將波束成型應用於無線隨意網路當中,可以減少傳送端所需要傳送能量消耗並且可以減少網路當中使用者之間的互相干擾,對於整體無線隨意網路效能有著顯著的改善。而本論文於介紹完兩種不同應用場景的波束成型設計方式之後,皆有與其他一些已知的波束成型設計方式做出比較,並作出模擬,以確定此種波束成型設計方式可以適用於無線隨意網路當中。而本論文將會仔細探討設計波束成型演算法之流程。 | zh_TW |
dc.description.abstract | Wireless Ad Hoc network, in recent several years, has been widely thought of as another possible development direction in wireless network in contrast with traditional infrastructure based wireless network. Because wireless ad hoc network doesn’t need any time or cost spent on infrastructure construction, so it can be used in remote area or the place where doesn’t exist any infrastructure. And because of its distributive nature, ad hoc network is more robust compared to traditional wireless network. Due to several unique advantages, wireless ad hoc network makes more researchers and engineers pay more attention to it.
In this thesis, an ad hoc network operation flow chart is proposed based on ad hoc network feature and 802.11 Ad Hoc mode standard. And in this flow chart, we have two communication scenarios in wireless ad hoc network: unicast and multicast. So, we will design the joint transmitter-receiver beamformer algorithm at both ends to utilize the power-saving and interference-mitigation characteristics of beamforming. And both two characteristics are important to build up a power-efficient transceiver in wireless ad hoc network. After each of the two beamforming design algorithms, we will make some simulation results and compared with some existing algorithms to see its performance. From the comparison result, we can find these two beamforming design algorithms are efficient in reducing the transmit power. Here we will discuss the detail derivations in how to design these two types of beamforming algorithms. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T05:57:43Z (GMT). No. of bitstreams: 1 ntu-99-R97943036-1.pdf: 4364106 bytes, checksum: 9acb3e8633aeab7169ef104759c554ee (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | 目錄 I
圖目錄 V 表目錄 VII 1. 第一章 緒論 1 1.1. 研究背景 1 1.2. 研究動機 3 1.3. 無線隨意網路介紹 4 1.3.1. 無線隨意網路定義 4 1.3.2. 無線隨意網路特點 5 1.3.3. 無線隨意網路分類 5 1.3.4. 無線隨意網路應用 6 1.3.5. 無線隨意網路所面臨的問題 7 1.3.6. IEEE 802.11 隨意模式簡介 8 1.4. 論文組織介紹 9 2. 第二章 波束成型器介紹 11 2.1. 波束成型簡介 11 2.2. 傳送端波束成型設計 14 2.2.1. 系統模型 14 2.2.2. 傳送機波束成型方式介紹 15 2.2.2.1. 匹配濾波器 15 2.2.2.2. 線性強制歸零法 16 2.2.2.3. 線性最小均方差估計法 18 2.2.3. 本節概要 19 2.3. 接收機波束成型設計 19 2.3.1. 系統模型 21 2.3.2. 接收機波束成型方式介紹 21 2.3.2.1. 最小化變異數無失真響應 21 2.3.2.2. 訊雜比最佳化 22 2.3.2.3. 最小化能量無失真響應 23 2.3.2.4. 本節概要 24 2.3.3. 偵測與評估演算法運用於接收端波束成型設計 25 2.3.3.1. 傳送訊號源偵測演算法 25 2.3.3.2. 評估演算法 27 3. 第三章 網路模型 29 3.1. 網路運作流程 29 3.2. 改變指引方向以提升網路連通度 33 3.2.1. 無線隨意網路系統模型 33 3.2.1.1. 天線模型 34 3.2.1.2. 使用者節點分布模型 36 3.2.1.3. 無線通道模型 37 3.2.2. 指引方向選擇於無線隨意網路之影響 38 3.2.2.1. 評斷標準 39 3.2.2.2. 用於比較之指引方向選擇法 40 3.2.2.3. 效能比較 40 3.2.2.4. 增進廣域連通度於貪婪指引方向選擇 47 3.2.3. 本節概要 49 4. 第四章 單一播送用聯合傳送機與接收機之波束成型設計 51 4.1. 系統模型 51 4.2. 波束成型演算法應用單一播送通訊場景之最新發展 52 4.2.1. 傳送端波束成型設計 53 4.2.1.1. 線性強制歸零法 53 4.2.1.2. 線性最小均方差估計法 53 4.2.2. 無空間分流干擾之最小化變異數無失真響應之接收端波束成型 54 4.2.3. 奇異值分解聯合波束成型設計 55 4.2.4. 本節概要 56 4.3. 聯合傳送機與接收機之波束成型設計 57 4.4. 模擬結果與效能比較 66 4.4.1. 應用提出之演算法於無線隨意網路 66 4.4.1.1. TGn無線通道模型 67 4.4.1.2. 應用提出之演算法於建基於TGn模型之無線隨意網路 72 4.4.2. 傳送能量比較 77 4.4.3. 運算複雜度比較 82 4.5. 本章概要 83 5. 第五章 多重播送用聯合傳送機與接收機之波束成型設計 85 5.1. 系統模型 85 5.2. 波束成型演算法應用於多重播送通訊場景之最新發展 86 5.2.1. 系統模型特化 87 5.2.2. 多重播送之傳送端波束成型設計介紹 88 5.2.2.1. 匹配濾波器 88 5.2.2.2. 線性強制歸零法 89 5.2.2.3. 線性最小均方差估計法 90 5.2.2.4. 湯林森-何洛緒瑪預編碼 91 5.2.2.5. 使用者選擇匹配濾波器 93 5.2.2.6. 迭代式訊號對干擾加雜訊比平均法 94 5.2.2.7. 服務品質波束成型設計之半定鬆弛演算法 95 5.2.3. 接收端波束成型設計 96 5.3. 聯合傳送機與接收機之波束成型設計 97 5.4. 模擬結果與效能比較 111 5.4.1. 應用提出之演算法於建基於TGn模型之無線隨意網路 111 5.4.2. 傳送能量比較 114 5.4.3. 運算複雜度比較 118 5.4.4. 本節概要 120 5.5. 降低提出演算法之運算複雜度 122 5.6. 本章概要 124 6. 第六章 結論與展望 125 參考文獻 127 | |
dc.language.iso | zh-TW | |
dc.title | 應用於無線隨意網路之聯合波束成型器設計 | zh_TW |
dc.title | Power-efficient Joint Transmitter-Receiver Beamformer Design for Wireless Ad Hoc Network | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳安宇(An-Yeu Wu),蘇炫榮(Hsuan-Jung Su),黃元豪(Yuan-Hao Huang) | |
dc.subject.keyword | 聯合波束成型器,無線隨意網路,節能,單一播送,多重播送, | zh_TW |
dc.subject.keyword | Joint Beamformer,Wireless Ad Hoc network,Power-efficient,unicast,multicast, | en |
dc.relation.page | 129 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-08-18 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
顯示於系所單位: | 電子工程學研究所 |
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 | 4.26 MB | 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。