本論文分成兩個主題的研究。第一個主題是提出將軟體定義網路架構應用至既有的網狀拓樸布拉格光纖光柵感測網路，第二個主題則是針對光學正交分頻多工系統之IQ不平衡提出低運算複雜度的IQ不平衡參數估測演算法及迭代補償的架構。
在本論文的第一個主題提出的架構中，我們利用多個軟體定義網路中央管理者將感測網路分成許多規模較小的感測子區域，透過中央管理者互相交換訊息，控制層面可以知道所有的感測子區域中的網路狀態。所有的感測程序都由中央管理者執行，其會依據個別的網路狀態，以軟體方式指示硬體層面執行對應的動作，如此一來可以解決傳統布拉格光柵光纖網狀感測網路由於光纖斷點發生時造成的遠程節點管控及如何維持網路存活率的問題。本論文使用Mininet及Floodlight分別模擬軟體定義網路之資料平台及控制平台展示以軟體管控網路之功能，並且以可用替代檢測光路徑比例、感測訊號之功率消耗及網路存活率等觀點說明軟體定義網路的特性能夠為此感測網路帶來更好的表現、更佳的光纖斷點容忍度及解決了網路管控的問題。
本論文第二個主題提出的低運算複雜度之估測演算法是藉由傳送簡單的訓練符元估測IQ不平衡參數，此演算法不需使用平方率計算或任何非線性的運算，僅需一些簡單的除法和減法運算即能準確地得到估計值。本論文在接收端先補償接收端的IQ不平衡之後再補償傳送端的IQ不平衡，並將這兩次補償定義為一次迭代補償。受到IQ不平衡影響之訊號在經過多次迭代補償後，其解出之訊號錯誤率皆能接近完美補償之訊號錯誤率的水準，論文中也呈現了當系統發生了不同嚴重性的IQ不平衡時，訊號經由估測演算法後進入迭代補償架構的結果。

For the first topic of this thesis, we propose a software-defined network (SDN) controlling FBG-based optical sensing system with mesh topology. In this system, we use a multiple sensing regions scheme supervised by many SDN controllers. Each SDN controller can know the whole network information of every sensing region by exchanging messages with other controllers. Every regular sensing procedure is automatically executed based on the built-in routing table in central office (CO). SDN controller will only participate in and update the sensing procedures based on software algorithms when abnormal occasions occur, such as link failures. This multiple sensing regions scheme is an effective solution to issues of remote nodes controlling and sensing network survivability enhancement. We apply Mininet and Floodlight as simulation platforms to simulate the data plane and control plane respectively. The numerical simulations, including evaluations of the available light path ratio, the sensing signal power loss, and the network survivability, are conducted based on different sensing regions schemes and link failures. As a result, by taking the advantages of the SDN scheme, our demonstration can not only enhance the performance of sensing procedures and the tolerance of link failures, but also offer an effective solution of the network controlling issues.
For the second topic of this thesis, we propose a low complexity I/Q imbalance estimation algorithm and iterative compensation scheme for orthogonal frequency division multiplexing (OFDM) system. The I/Q imbalance parameters can be estimated by simple training symbols. Instead of other complex nonlinear calculations, this estimation algorithm only applies simple linear operations, including division and subtraction, to obtain the estimated I/Q imbalance amplitude and phase factors. These compensations are designed as an iterative procedure by compensating imbalances from receiver and transmitter alternatively. With such a design, the distorted I/Q imbalance signals can be greatly improved, such that performance can be approaching to that of undistorted signals. This proposed estimation and compensation scheme is demonstrated by numerical simulations under various I/Q imbalance conditions.

第1章 緒論
1.1 前言
1.2 研究動機
1.3 論文編排
第2章 布拉格光纖光柵感測網路之原理與網路存活率
2.1 布拉格光纖光柵之感測原理
2.2 網狀拓樸布拉格光纖光柵感測網路
2.2.1 實驗架構
2.2.2 網狀拓樸布拉格光纖光柵感測網路最短路徑之計算
2.2.3 網狀拓樸布拉格光纖光柵感測網路之優缺點
2.3 網路存活率之定義
2.3.1 雙路徑保護之推導與網路存活率
2.3.2 多重路徑保護之推導
第3章 以軟體定義網路控制之網狀布拉格光纖光柵感測網路
3.1 軟體定義網路
3.1.1 OpenFlow技術標準介紹
3.1.2 軟體定義光學網路
3.1.3 以軟體定義網路控制之無線感測網路架構
3.1.4 軟體定義網路之挑戰
3.2 軟體定義網路之模擬平台
3.3 模擬結果及討論
3.3.1 可用替代檢測光路徑比例之模擬結果及討論
3.3.2 感測訊號的功率消耗之模擬結果及討論
3.3.3 網路存活率之模擬結果及討論
第4章 光學正交分頻多工系統之IQ不平衡
4.1 光學正交分頻多工系統之傳送端與接收端
4.2 光學正交分頻多工系統之IQ不平衡
4.3 IQ不平衡之補償架構
4.4 傳送端IQ不平衡之估計及結果
4.5 傳送端與接收端IQ不平衡之估計及結果
4.6 傳送端與接收端皆發生IQ不平衡之迭代補償及結果
第5章 結論
附錄
參考文獻

[1] B. Li, Z. Sun, K. Mechitov, G. Hackmann, C. Lu, S. J. Dyke, G. Agha, and B. F. Spencer Jr. “Realistic case studies of wireless structural control,” ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), pp. 179-188, 2013.
[2] N. Mohamed and I. Jawhar, “A fault tolerant wired/wireless sensor network architecture for monitoring pipeline infrastructures,” The Second International Conference on Sensor Technologies and Applications (SENSORCOMM ‘08), pp. 179-184, 2008.
[3] A. D. Kersey, M. A. Davis, H. J. Patrick, M. LeBlanc, K. P. Koo, C. G. Askins, M. A. Putnam, and E. Joseph Friebele, “Fiber grating sensors,” Journal of Lightwave Technology, vol. 15, no. 8, pp. 1442-1463, 1997.
[4] H. N. Li, D. S. Li, and G. B. Song, ” Recent applications of fiber optic sensors to health monitoring in civil engineering,” Engineering Structure, vol.26, pp.1647-1657,2004.
[5] Fibre Sensing Innovations, Yokogawa, 2008.
[6] Daniel O. McPolin, P. A. Muhammed Basheer, Adrian E. Long, Weiguo Xie, Tong Sun, and Kenneth T. V. Grattan, “Development and longer term in situ evaluation of fiber-optic sensors for monitoring of structural concrete”, IEEE Sensors Journal, vol. 9, no. 11, pp. 1537-1545, 2009.
[7] NTT Access Network Service Systems Laboratories, Apr. 22, 2015, [Online], http://www.ansl.ntt.co.jp/history/infra/in0308.html
[8] P. C. Peng, H. Y. Tseng, and S. Chi, “A novel fiber-laser-based sensor network with self-healing function,” IEEE Photonics Technology Letters, vol. 15, no. 2, pp. 275-277, 2003.
[9] P. C. Peng, H. Y. Tseng, and S. Chi, “A hybrid star-ring architecture for fiber Bragg grating sensor system,” IEEE Photonics Technology Letters, vol. 15, no. 9, pp. 1270 -1272, 2003.
[10] P. C. Peng, J. H. Lin, H. Y. Tseng, and S. Chi, “Intensity and wavelength division multiplexing FBG sensor system using a tunable multiport fiber ring laser,” IEEE Photonics Technology Letters, vol. 16, no. 1, pp. 230 -232, 2004.
[11] P. C. Peng, H. Y. Tseng, and S. Chi, “Long-distance FBG sensor system using a linear-cavity fiber Raman laser scheme,” IEEE Photonics Technology Letters, vol. 16, no. 2, pp. 575 - 577, 2004.
[12] P. C. Peng, W. P. Lin, and S. Chi, “A self-healing architecture for fiber Bragg sensor network” in Proc. Of IEEE Sensors, 60-63 (2004).
[13] P. C. Peng and K. Y. Huang, “Fiber Bragg grating sensor system with two-level ring architecture,” IEEE Sensors Journal, vol. 9, pp. 309 - 313, 2009.
[14] C. Y. Wu, K. M. Feng, P. C. Peng and C. Y. Lin, “Three-dimensional mesh-based multipoint sensing system with self-healing functionality,” IEEE Photonics Technology Letters, vol. 22, no. 8, pp. 565-567, 2010.
[15] M. Channegowda, R. Nejabati, and D. Simeonidou, “Software defined optical networks technology and infrastructure: Enabling software-defined optical network operations [Invited],” IEEE/OSA Journal of Optical Communications and Networking, vol. 5, no. 10, pp. A274-A282, 2013.
[16] G. Xing, M. Shen, and H. Liu, “Frequency offset and I/Q imbalance compensation for direct-conversion receivers,” IEEE Transactions on Wireless Communications, vol. 4, no. 2, pp. 673–680, 2005.
[17] S. Cao, C. Yu, and P. Y. Kam, “Decision-aided joint compensation of transmitter IQ mismatch and phase noise for coherent optical OFDM,” IEEE Photonics Technology letters, vol. 24, no. 12, pp. 1066-1068, 2012.
[18] S. Cao, C. Yu, and P. Y. Kam, “Decision-aided joint compensation of channel distortion and transmitter IQ imbalance for coherent optical OFDM,” in Proc. IEEE Topical Meeting on & Microwave Photonics Conference, pp. 312–315,2011.
[19] W. J. Jiang, C. T. Lin, E. Z. Wong, P. T. Shih, J. Chen, and S. Chi, “A novel optical direct-detection I/Q up-conversion with I/Q imbalance compensation via Gram-Schmidt orthogonalization procedure,” ECOC Conference on Optical Communication, 2009.
[20] Y. Xiao, G. He and J. Ma, “A novel method for estimation and compensation of transmitter I/Q imbalance,” International SoC Design Conference (ISOCC), pp. 261 – 265, 2009.
[21] I-T. Lu and J. Chang, “Joint transmitter and receiver IQ imbalance estimation and compensation for OFDM systems,” IEEE Radio and Wireless Symposium (RWS), pp. 476 – 279, 2010.
[22] Y. C. Pan and S. M. Phoong, “A time-domain joint estimation algorithm for CFO and I/Q imbalance in wideband direct-conversion receivers,” IEEE Transactions on Wireless Communications, vol. 11, no. 7, pp. 2353 – 2361, 2012.
[23] E. J. Friebele, M. A. Putnam, H. J. Patrick, A. D. Kersey, and A. S. Greenblatt, “Ultrahigh-sensitivity fiber-optic strain and temperature sensor,” Optics Letters, vol. 23, no. 3, pp.222-224, 1998.
[24] E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, vol. 1, issue 1, pp. 269-271, 1959.
[25] J. F. Kurose and K. W. Ross, “The Network Layer,” in Computer Networking a Top-Down Approach, 5th ed. Boston, Pearson Addison-Wesley, 2010, ch. 4, sec. 5, pp. 400-419.
[26] Q. She, X. Huang, and J. P. Jue, “How reliable can two-path protection be?” IEEE/ACM Transactions on Networking, vol. 18, no. 3, pp. 922-933, 2010.
[27] Open Networking Foundation, “Software-Defined Networking: The New Norm for Networks,” Apr. 22, 2015, [Online], https://www.opennetworking.org/images/
stories/downloads/sdn-resources/white-papers/wp-sdn-newnorm.pdf
[28] Y. H. Chu, H. J. Hsu, M. C. Tseng, L. M. Chang, W. C. Tai, C. H. Kao and Y.C. Chang, “Introduction of SDN standards and related organizations,” TL Technical Journal, vol.44, no.3, 2014.
[29] P. N. Ji, “Software defined optical network,” Proc. of International Conference on Optical Communications and Networks (ICOCN), no. THU-07, Nov, 2012.
[30] Z. J. Han and W.Ren, “A novel wireless sensor networks structure based on the SDN,” International Journal of Distributed Sensor Networks, vol. 2014, 2014.
[31] P. Dely and A. Kassler, “OpenFlow for wireless mesh networks,” In Proc. of 20th International Conference on Computer Communications and Networks (ICCCN), Workshop on Wireless Mesh and Ad Hoc Networks, Hawaii, USA, 2011.
[32] E. I. Oyman, C. Ersoy, “Multiple sink network design problem in large scale wireless sensor networks,” IEEE International Conference on Communications, vol. 6, pp. 3663-3667, 2004.
[33] M. Younis, K. Akkaya, “Strategies and techniques for node placement in wireless sensor networks: A survey,” Ad Hoc Networks, vol 6, issue 4, pp. 621-655, 2008.
[34] Mininet Team, Apr. 22, 2015, [Online], http://mininet.org/
[35] Project Floodlight, Apr. 22, 2015, [Online], http://www.projectfloodlight.org/
floodlight/
[36] R. A. Shafik, S. Rahman and R. Islam, “On the extended relationships among EVM, BER and SNR as performance metrics,” International Conference on Electrical and Computer Engineering(ICECE), pp. 408 – 411, 2006.