超寬頻(Ultra-wideband)主要用於室內環境，和多天線系統的結合可以提供更高的傳輸效能，但環境會產生多路徑效應(multi-path effect)。由於此效應造成的符際間干擾(Inter Symbol Inference, ISI),使得通訊位元錯誤率及失效率(outage probability)增加,導致通話品質變差。因此在本論文中，透過使用實數正交設計(Real Orthogonal design, ROD)可以有效的改善超寬頻多天線系統，將模擬環境透過射線彈跳追蹤法結合反複利葉轉換可以求出該環境的時域脈衝響應，並使用耙式接收機(RAKE receiver)增加接收信號強度以抑制多路徑效應。在本篇論文中，我們將針對天線的排列方式(CASE A)和發射端的高度與演算法搜尋之位置(CASE B)進行探討無線存取點在環境中之最佳位置。CASE A以線形、L形、圓形、Y形四種不同類型的8 x 8發射和接收天線陣列，探討在3.1~10.6GHz之頻段時的超頻寬通訊(Ultra-wideband, UWB)之性能。數值結果顯示，在一般環境中，圓形的排列方式的失效率(定義為錯誤率>10-6)，在大部分的情況下，是優於其他三種(線形、L形、Y形)排列方式的。CASE B 根據已知的室內環境以及所選定的UWB-MIMO系統，藉由隨機式全域最佳化演算法找到發射端在環境中之最佳位置，並分別調整發射端的高度，其中以非同步粒子群聚最佳化法（Asynchronous Particle Swarm Optimization, APSO），所找到之最佳位置，效果比自我適應之動態差異型演化法(Self-Adaptive Dynamic Differential Evolution, SADDE)來的更好、更迅速。本研究在學理與實際之通信系統規劃上，皆具有其重要性。

Ultra-wideband (UWB) combined with multiple input and multiple output (MIMO) are proposed to increase the data rate. UWB mainly used for indoor environments. Due to the multi-path effect, the Inter Symbol Inference (ISI) increases the bit error rate and outage probability of the MIMO-UWB system. In this thesis, the application of Real Orthogonal design is employed to improve MIMO-UWB system. The ray-tracing technique and inverse fast Fourier transform are used to get the impulse response of the indoor environment. Moreover, RAKE receiver is used to increase the strength of received signal against multiple path effect.
In this thesis, different antennas array (case A) and the best position for different height of transmitter are presented (case B). There are four different shapes of arrays for the transmitter and receiver, such as linear array, L array, circular array and Y array, for CASE A. The performance for these array in UWB frequency between 3.1~10.6GHz are discussed. The outrage probability of circular array is better than the other three arrays. For Case B, two antenna element arrays are used for the transmitter with different height. The optimal location for the transmitter is searched by Asynchronous Particle Swarm Optimization (APSO) and  Self-Adaptive Dynamic Differential Evolution ( SADDE). The numerical results show that the performance for APSO is better than SADDE.

目錄
第一章 概論	1
1.1 研究背景	1
1.1.1 超寬頻(UWB)	1
1.1.2 多輸入多輸出(MIMO)	3
1.2 研究動機	7
1.3 研究內容簡介	9
1.4 本論文研究之貢獻	9
第二章 系統理論	11
2.1  UWB通道計算模型	11
2.1.1 無線電波傳播通道分析	11
2.1.2 通道計算模型分析	12
2.1.3利用射線追蹤法計算出頻域響應	14
2.1.4 利用何米特法與快速反傅立葉轉換計算出時域響應	17
2.1.5 射線彈跳追蹤法程式流程分析	19
2.2 耙式接收機（RAKE receiver）	22
2.3 錯誤率性能分析	23
2.3.1 使用實數正交設計之位元錯誤率公式	36
2.3.2 未使用實數正交設計之位元錯誤率公式	37
第三章 隨機式全域最佳化演算法	40
3.1自我適應之動態差異型演化法(Self-Adaptive Dynamic Differential Evolution)	40
3.2.1 粒子群聚最佳化法(Particle Swarm Optimization)	47
3.2.2非同步粒子群聚最佳化法（Asynchronous Particle Swarm Optimization）	53
第四章 數值模擬結果	55
4.1 模擬環境	55
4.2 針對天線的排列方式進行探討	58
4.2.1 天線排列方式	58
4.2.2 模擬結果	59
4.3 針對發射端的高度與演算法搜尋之最佳位置進行探討	64
4.3.1 參數設定	64
4.3.2 模擬結果	65
第五章 結論	73
參考文獻	80
圖目錄
圖1.1 SISO, SIMO, MISO和MIMO 示意圖	4
圖1.2多輸入多輸出系統通道模型示意圖	6
圖2.1 系統流程圖	11
圖2.2 求得通道脈衝響應的步驟圖	13
圖2.3 何米特程序的信號處理步驟與快速反傅立葉轉換過程	18
圖2.4 SBR/Image 程式流程圖	20
圖2.5 對應NF 個分支的耙式接收機之系統架構圖	23
圖2.6 脈衝發射訊號示意圖	25
圖2.7 超寬頻多輸入多輸出系統圖	37
圖3.1 自我適應之動態差異型進化法流程圖	39
圖3.2 自我適應之動態差異型進化法中突變方法一的示意圖	43
圖3.3 自我適應之動態差異型進化法中突變方法二的示意圖	44
圖3.4 自我適應之動態差異型進化法中的交配向量於一個二
維目標函數等位線圖描述的示意圖	46
圖3.5粒子群聚法流程圖	49
圖3.6 粒子群聚法中於二維目標函數等位線圖	50
圖3.7三種不同邊界條件示意圖。X^k id '與V^k id '表示更新後的粒
子位置與速度	53
圖4.1 模擬環境	56
圖4.2 發射與接收點於環境中的位置圖	57
圖4.3(a) 圓形	58
圖4.3(b) 線形	58
圖4.3(c) L形	58
圖4.3(d) Y形	58
圖4.4 直接波的發射端與接收端分布圖	60
圖4.5 非直接波的發射端與接收端分布圖	61
圖4.6 四種陣列天線錯誤率比較圖(直接波)	62
圖4.7 四種陣列天線錯誤率比較圖(非直接波)	62
圖4.8 四種天線陣列的錯誤率比較圖	63
圖4.9 四種天線的失效率比較圖	63
圖4.10 比較兩種發射端高度在SNR=40dB ~ 80dB之失效點數	66
圖4.11發射端於環境中心(2.5,5.0,4.5)在SNR=70dB，時失效點
在環境中之分布圖	67
圖4.12發射端於環境中心(2.5,5.0,2.0)在SNR=56dB，時失效點
在環境中之分布圖	68
圖4.13 由SADDE調整其發射端位置(0.5,9.424589,4.5)在SNR=70dB時失效點在環境中之分布圖	69
圖4.14 由APSO調整其發射端位置(0.10, 9.89615,4.5)在SNR=70dB時，失效點在環境中之分布圖	70
圖4.15 由SADDE調整其發射端位置(2.814834,5.076447,2.0)在SNR=56dB時失效點在環境中之分布圖	71
圖4.16 由APSO調整其發射端位置(2.607637,3.953182,2.0)在SNR=56dB時，失效點在環境中之分布圖	72
表目錄
表4.1 SADDE & APSO設定參數	64
表A.1 混泥土的材質係數	74
表A.2 合成纖維板的材質係數	75
表A.3 木材的材質係數	76
表A.4 鐵的材質係數	77
表A.5 磚的材質係數	78
表A.6 夾板的材質係數	79

[1]Alamouti, S. (1998). A simple transmit diversity technique for wireless communications. Selected Areas in Communications, IEEE Journal on, 16(8), 1451-1458. doi:10.1109/49.730453

[2]Alavi, B., Alsindi, N., & Pahlavan, K. (2006). UWB channel 
measurements for accurate indoor localization. Military Communications Conference, 2006. MILCOM 2006. IEEE, 1-7.doi:10.1109/MILCOM.2006.302143

[3]Asif, H. M., Honary, B., & Ahmed, H. (2012). Multiple-input 
multiple-output ultra-wide band channel modelling method based on ray tracing. Communications, IET, 6(10), 1195-1204. doi:10.1049/iet-com.2011.0265

[4]Bas, C. U., & Ergen, S. C. (2013). Ultra-wideband channel model for intra-vehicular wireless sensor networks beneath the chassis: From statistical model to simulations. Vehicular Technology, IEEE Transactions on, 62(1), 14-25. doi:10.1109/TVT.2012.2215969

[5]Boche, H., Bourdoux, A., Fonollosa, J. R., Kaiser, T., Molisch, A., & Utschick, W. (2006). Antennas: State of the art. Vehicular Technology Magazine, IEEE, 1(1), 8-17. doi:10.1109/MVT.2006.1663946

[6]Cassioli, D., Win, M. Z., Vatalaro, F., & Molisch, A. F. (2007). Low complexity rake receivers in ultra-wideband channels. Wireless Communications, IEEE Transactions on, 6(4), 1265-1275. doi:10.1109/TWC.2007.348323

[7]Chen, C. H., Liu, C. L., Chiu, C. C., & Hu, T. M. (2006). Ultra-wide band channel calculation by SBR/Image techniques for indoor communication. Journal of Electromagnetic Waves and Applications, 20(1), 41-51. doi:10.1163/156939306775777387

[8]Chen, S. H., & Jeng, S. K. (1997). An SBR/image approach for radio wave propagation in indoor environments with metallic furniture. Antennas and Propagation, IEEE Transactions on, 45(1), 98-106. doi:10.1109/8.554246

[9]Chen, S. H., & Jeng, S. K. (1996). SBR/image approach for radio wave propagation in furnished environments. Antennas and Propagation Society International Symposium, 1996. AP-S. Digest, , 1 453-456 vol.1. doi:10.1109/APS.1996.549635

[10]Chen, S. H., & Jeng, S. K. (1996). SBR image approach for radio wave propagation in tunnels with and without traffic. Vehicular Technology, IEEE Transactions on, 45(3), 570-578.

[11]Coenen, A. J. R. M., & de Vos, A. J. (1992). FFT-based interpolation for multipath detection in GPS/GLONASS receivers. Electronics Letters, 28(19), 1787-1788. doi:10.1049/el:19921139

[12]Demir, U., Bas, C. U., & Coleri Ergen, S. (2013). Engine compartment UWB channel model for intra-vehicular wireless sensor networks doi:10.1109/TVT.2013.2294357

[13]Hamalainen, M., & Iinatti, J. (2005). Analysis of interference on DS-UWB system in AWGN channel. Ultra-Wideband, 2005. ICU 2005. 2005 IEEE International Conference on, 719-723. doi:10.1109/ICU.2005.1570077

[14]Kaiser, T., Feng Zheng, & Dimitrov, E. (2009). An overview of ultra-wide-band systems with MIMO. Proceedings of the IEEE, 97(2), 285-312. doi:10.1109/JPROC.2008.2008784

[15]Kandukuri, S., & Boyd, S. (2002). Optimal power control in interference-limited fading wireless channels with outage-probability specifications. Wireless Communications, IEEE Transactions on, 1(1), 46-55. doi:10.1109/7693.975444

[16]Khaleghi, A, Chavez -Santiago, R., & Balasingham, I. (2011). Ultra-wideband statistical propagation channel model for implant sensors in the human chest. Microwaves, Antennas & Propagation, IET, 5(15), 1805-1812. doi:10.1049/iet-map.2010.0537
[17]Kshetrimayum, R. S. (2009). An introduction to UWB communication systems. Potentials, IEEE, 
28(2), 9-13. doi:10.1109/MPOT.2009.931847

[18]Loredo, S, Rodriguez -Alonso, A., & Torres, R. P. (2008). Indoor MIMO channel modeling by rigorous GO/UTD-based ray tracing. Vehicular Technology, IEEE Transactions on, 
57(2), 680-692.doi:10.1109/TVT.2007.906362

[19]Mielczarek, B., Wessman, M. -., & Svensson, A. (2003). Performance of coherent UWB rake receivers with channel estimators. Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th, , 3 1880-1884 Vol.3. doi:10.1109/VETECF.2003.1285351

[20] Migliore, M. D., Pinchera, D., Massa, A., Azaro, R., Schettino, F., & Lizzi, L. (2008). An investigation on UWB-MIMO communication systems based on an experimental channel characterization. Antennas and Propagation, IEEE Transactions on, 56(9), 3081-3083.
doi:10.1109/TAP.2008.928814

[21] Paulraj, A. J., Gore, D. A., Nabar, R. U., & Bolcskei, H. (2004). An overview of MIMO communications - a key to gigabit wireless. Proceedings of the IEEE, 92(2), 198-218.
doi:10.1109/JPROC.2003.821915

[22] Priebe, S., Kannicht, M., Jacob, M., & Kurner, T. (2013). Ultra broadband indoor channel measurements and calibrated ray tracing propagation modeling at THz frequencies. Communications and Networks, Journal of, 15(6), 547-558.
doi:10.1109/JCN.2013.000103

[23] Rappaport, T. S. (2002). Wireless communications: Principles and practice (2nd ed.) Prentice Hall.

[24] Sadi, Y., & Ergen, S. C. (2013). Optimal power control, rate adaptation, and scheduling for UWB-based intravehicular wireless sensor networks. Vehicular Technology, IEEE Transactions on, 62(1) 
219-234. doi:10.1109/TVT.2012.2217994
[25] Talepour, Z., Ahmadi-Shokouh, J., & Tavakoli, S. (2012). Optimality of transmitter location in a wireless network with RAKE receivers. Communications, IET, 6(18),3059-3064.
 doi:10.1049/iet-com.2012.0272

[26] Tarokh, V., Jafarkhani, H., & Calderbank, A. R. (1999). Space-time block codes from orthogonal designs. Information Theory, IEEE Transactions on, 45(5), 1456-1467. doi:10.1109/18.771146

[27] Tian, Z., & Giannakis, G. B. (2005). BER sensitivity to mistiming in ultra-wideband impulse radios - part II: Fading channels. Signal Processing, IEEE Transactions on, 53(5), 1897-1907.
doi:10.1109/TSP.2005.845485