隨著通訊技術的進步，提供高速可靠傳輸服務之無線通訊系統已成為近年來的研究主題之一。其中，多輸入多輸出(Multiple-Input Multiple-Output, MIMO)為使用多天線於傳送和接收端的可靠通訊技術，它為上述需求提供了可能的解答。傳統智慧型天線(Smart Antenna)系統可視為MIMO的特殊形式，主要的技術為波束形成技術，它能運用具自我適應、調整功能之演算法驅動陣列天線，使之產生特定的波束形狀，將主波束對準目標訊號用以強化接收品質，同時調整零陷點，使之對準干擾訊號用以抑制(或消除)干擾，從而達到增加系統容量、擴大涵蓋面和提高傳輸率的多重目的。近年來，MIMO技術的發展趨勢可分為兩類：一為空間分集，另一為空間多工。MIMO雙邊陣列技術可提供發射及接收空間分集，有效對抗通道衰落現象，亦可提供空間多工，在傳送端陣列天線同時傳送多組不同之資料，並在接收端分別予以解出，以提高系統的整體傳輸速率。在無線傳輸環境中，不同的環境障礙物會造成不同的多路徑衰落效應。基於此一觀點，吾人將探討結合智慧型天線與MIMO之通訊系統架構，針對不同的環境效應，選取最適合之傳輸技術。吾人將進一步針對MIMO提出一種適應性傳收架構，使其能夠隨時間動態地在通道上調整傳輸參數，如：選取空時訊號處理技術以及調變階數，以便充分利用無線通道的特性以維持系統的目標錯誤率以及資料傳輸率。最後，吾人將以電腦模擬驗證上述架構在不同無線通訊環境中所呈現之優異效能。

The research and development of wireless communication systems for high speed reliable transmission has become one of the new challenging subjects in the telecommunication area. Multiple-input multiple-output (MIMO) is a reliable technology that employs multiple antennas at both the transmitter and receiver sides, and represents a potential solution to the above mentioned demand. Conventional smart antenna techniques can be regarded as a special form of MIMO, which main technique is beamforming. Recent researches on MIMO techniques can be categorized into two major types: one is spatial diversity (SD) and the other is spatial multiplexing (SM). In a wireless transmission environment, the transmitted signal is scattered by various environmental objects (buildings, trees, mountains, etc) causing different multi-path fading effects. With this point of view, we here consider a wireless communication system combining smart antenna and MIMO techniques. Depending on the channel condition, the optimal transmission technique will be selected to combat channel impairments. We also propose an adaptive MIMO transceiver architecture to dynamically adjust the transmission parameters such as space-time processing mode and modulation order, according to the instantaneous channel statistics, to meet the target error rate and data rate. Finally, the performance of the proposed transceiver is verified using computer simulations in different wireless communication environments.

[1]A. J. Paulraj and C. B. Papadias, “Space-time processing for wireless communications,” IEEE Signal Processing Magazine, vol. 14, pp. 49-83, Nov. 1997.
[2]G. J. Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multiple antennas,” Bell Labs Syst. Tech. J., vol. 1, pp. 41-59, Autumn 1996.
[3]G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas,” Wireless Personal Commun., vol. 6, no. 3, pp. 311-335, 1998.
[4]P. W. Wolniansky, G. J. Foschini, G. D. Golden, and R. A. Valenzuela, “V-BLAST: an 1rchitecture for realizing very high data rates over the rich-scattering wireless channel,” URSI International Symposium, pp. 295-300, 29 Sep. -2 Oct. 1998.
[5]X. Li, H. Huang, G. J. Foschini, and R. A. Valenzuela, “Effects of iterative detection and decoding on the performance of BLAST,” IEEE GLOBECOM, vol. 2, pp. 1061-1066, 2000.
[6]Ezio Biglieri, Giorgio Taricco and Antonia Tulino, “Decoding space-time codes with BLAST architectures,” IEEE Trans. Signal Processing, vol. 50, no. 10, pp. 2547-2552, Oct. 2002.
[7]Siavash M. Alamouti, “A simple transmitter diversity technique for wireless communications,” IEEE J. Select. Areas Commun., vol. 16, no. 8, pp. 1451-1458, Oct. 1998.
[8]V. Tarokh, N. Seshadri, and A. R. Calderbank, “Space-time codes for high data rate wireless communication: performance analysis and code construction,” IEEE Trans. Inform. Theory, vol. 44, no. 2, pp. 744-765, Mar. 1998.
[9]V. Tarokh, H. Jafarkhani, and A. R. Calderbank, “Space-time block codes from orthogonal designs,” IEEE Trans. Inform. Theory, vol. 45, no. 5, pp. 1456-1467, July 1999.
[10]V. Tarokh, H. Jafarkhani, and A. R. Calderbank, “Space-time block coding for wireless communications: performance results,” IEEE J. Select. Areas Commun., vol. 17, no. 3, pp. 451-460, Mar. 1999.
[11]W. C. Y. Lee, “Mobile Communication Engineering,” New York: Mc-Graw Hill, 1982.
[12]C. Shannon, “A Mathematical Theory of Communication,” Bell Labs Tech. J., 27, 379-423, 623-656, July and October 1948.
[13]I. Telatar, “Capacity of multi-antenna gaussian channels,” European Trans., November/December 1999.
[14]T. Cover and J. Thomas. “Elements of Information Theory,” Wiley, New York, 1991.
[15]C. Chuah, J. Kahn, and D. Tse. “Capacity of multi-antenna array systems in indoor wireless environment,” Proc. IEEE GLOBECOM. 4, 1894-1899, Sydney, Australia, November 1998.
[16]C. Chuah, D. Tse, J. Kahn, and R. Valenzuela. “Capacity scaling in MIMO wireless systems under correlated fading,” IEEE Trans. Inf. Theory, 48(3), 637-650, March 2002.
[17]D. Gesbert, H. Bölcskei, D. Gore, and A. Paulraj, “MIMO wireless channels: capacity and performance prediction,” GLOBECOM’00., vol. 2, pp. 1038-1088, Nov.2000.
[18]T. S. Rappaport, “Wireless communications: principles and practice,” Prentice Hall, 1999.
[19]G. J. Foschini, G. D. Golden, R.A. Valenzuela, and P. W. Wolniansky, “Simplified processing for high spectral efficiency wireless communication employing multi-element arrays,” IEEE J. Select. Areas Commum. Vol. 39, no. 1, pp. 100-108, Jan. 2001.
[20]G. Giannakis, Y. Hua, P. Stoica, and L. Tong, “Signal processing advances in communications,” Prentice Hall, New Jersey, USA, 2001, Chapter 3, Space-Time Diversity.
[21]J. Choi, S. R. Kim, and I. K. Choi, “Eigenbeamforming for OFDM downlink,” Oct. 2003.
[22]Spatial Channel Model AHG, “Spatial channel model text description,” Tech. Rep. (File No: SCM-095-SCM Text v2.1b), 3GPP & 3GPP2, Jan. 2003.
[23]D. Gesbert, H. Bölcskei, D. A. Gore, and A. Paulraj, “Outdoor MIMO Wireless Channels: Models and Performance Prediction,” IEEE Trans. on Comm., vol. 50, no. 12, Dece. 2002.
[24]F. R. Farrokhi, G. J. Foschini, A. Lozano, and R. A. Valenzuela, “Link-optimal space-time processing with multiple transmit and receive antennas,” IEEE Commun. Letters, vol. 5, no. 3, March 2001.
[25]F. R. Farrokhi, G. J. Foschini, A. Lozano, and R. A. Valenzuela, “Link-optimal BLAST processing with multiple-access interference,” in VTC’2000, Boston, MA, 2000.
[26]S. Rice, “Mathematical analysis of random noise,” Bell Syst. Tech. J., vol. 23, 1944.
[27]R. W. Heath Jr. and A. Paulraj, “Switching between spatial multiplexing and transmit diversity based on constellation distance,” in Proc. of Alleton Conf. on Comm. Cont. and Comp., Oct. 2000.
[28]H. Zhang, “The capacity and error probability analysis for high data rate IEEE 802.11 handbook: A designer’s companion,” New York: IEEE Press, 1999.
[29]S. Sandhu and A. Paulraj, “Space-time block codes: A capacity perspective,” IEEE Commun. Letters. Vol. 4, no. 12, pp.384-386, Dec, 2000.
[30]H. Shin and J. H. Lee, “Exact symbol error probability of orthogonal space-time block codes,” in Proc. IEEE GLOBECOM’02, Taipei, Taiwan, R.O.C., 2002.
[31]J. G. Proakis, “Digital Communications,” 4th Ed., McGraw-Hill, 2001.
[32]R. W. Heath and A. J. Paulraj, “Switch between multiplexing and diversity in MIMO communication links,” IEEE Trans. Commun., 2001. Submitted.
[33]V. Erceg, P. Soma, D. S. Baum, and A. J. Paulraj, “Capacity obtained from multiple-input multiple-output channel measurements in fixed wireless environments at 2.5 GHz,” Communications, ICC 2002. IEEE International Conference on, vol. 1, pp. 396-400, May 2002.
[34]A. J. Paulraj, R. Nabar, and D. Gore “Introduction to Space-Time Wireless Communications,” Cambridge University Press 2003.
[35]R. A. Horn and C. R. Johnson “Matrix Analysis,” Cambridge University Press 1985.