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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李學智 | |
| dc.contributor.author | Wei-Chieh Huang | en |
| dc.contributor.author | 黃偉傑 | zh_TW |
| dc.date.accessioned | 2021-06-15T03:52:14Z | - |
| dc.date.available | 2012-07-15 | |
| dc.date.copyright | 2010-07-15 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-07-09 | |
| dc.identifier.citation | [1] T. Hwang, C. Yang, G. Wu, S. Li, and G. Y. Li, “OFDM and its wireless applications: a survey,” IEEE Trans. on Vehicular Tech., vol. 58, no. 4, pp. 1673-1694, May 2009.
[2] Z. Wang and G. B. Giannakis, “Wireless multicarrier communication: where Fourier meets Shannon,” IEEE Signal Processing Mag., vol. 17, pp. 29-48, May 2000. [3] H.-C. Wu, “Analysis and characterization of intercarrier and interblock interferences for wireless mobile OFDM systems,” IEEE Trans. Broadcasting, vol. 52, no. 2, pp. 203-210, Jun. 2006. [4] L. Goldfeld, V. Lyandres, and D. Wulich, 'Minimum BER power loading for OFDM in fading channel,' IEEE Trans. Commun., vol. 50, pp. 1729- 1733, Nov. 2002. [5] P. F. Xia, S. L. Zhou, and G. B. Giannakis, 'Adaptive MIMO-OFDM based on partial channel state information,' IEEE Trans. Signal Processing , vol. 52, no. 1, Jan. 2004 [6] A. M. Wyglinski, F. Labeaua, and P. Kabal, 'Bit loading with BER-constraint for multicarrier systems,' IEEE Trans. Wireless Commun., vol. 4, pp. 1383-1387, July 2005. [7] A. Marques, F. Digham, and G. Giannakis, 'Optimizing power efficiency of OFDM using quantized channel state information,' IEEE J. Select. Areas Commun., pp. 1582-1592, Aug. 2006 [8] G. G. Raleigh and J. M. Cioffi, “Spatio-temporal coding for wireless communication,” IEEE Trans. Commun., vol. 46, no. 3, pp. 357-366, Mar. 1998. [9] 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, p. 41-59, Autumn 1996. [10] M. Tao and R. Cheng, “Improved design criteria and new trellis codes for space-time coded modulation in slow flat fading channels,” IEEE Commun. Lett., vol. 5, pp. 313-315, July 2001. [11] Z. Chen, B. Vucetic, J. Yuan, and K. Lo, “Space-time trellis codes for 4-PSK with three and four transmit antennas in quasi static flat fading channels,” IEEE Commun. Lett., vol. 6, pp. 67-69, Feb. 2002. [12] V. Tarokh, N. Seshadri, and A. R. Calderbank, “Space-time codes for high data rate wireless communication: Performance criteria and code construction,” IEEE Trans. Inform. Theory, vol.44, no.2, pp. 744-764, Mar. 1998. [13] B. A. Sethuraman, B. S. Rajan, and V. Shashidhar, “Full-diversity, high-rate space-time block codes from division algebras,” IEEE Trans. Inform. Theory, vol. 49, no. 10, pp. 2596-2616, Oct. 2003. [14] S. M. Alamouti, “A simple transmit diversity technique for wireless communications,' IEEE J. Select. Areas Commun., vol. 16, pp. 1451-1458, Oct. 1998. [15] V. Tarokh, H. Jafarkhani, and A. Calderbank, “Space-time block codes from orthogonal designs,” IEEE Trans. Inform. Theory, pp. 1456-1467, July 1999. [16] H. Wang and X.-G. Xia, “Upper bounds of rates of complex orthogonal space-time block codes,” IEEE Trans. Inform. Theory, vol. 49, no. 10, pp. 2788-2796, Oct. 2003. [17] R. S. Blum, Y. (G.) Li, J. H. Winters, and Q. Yan, “Improved space-time coding for MIMO-OFDM wireless communications,” IEEE Trans. Commun., vol. 49, no. 11, pp. 1873-1878, Nov. 2001. [18] Z. Liu, G. B. Giannakis, S. Barbarossa, and A. Scaglione, “Transmit-antenna space-time block coding for generalized OFDM in the presence of unknown multipath,” IEEE J. Select. Areas Commun., vol. 19, no. 7, pp. 1352-1364, July 2001. [19] M. Uysal, N. Al-Dhahir, and C. N. Georghiades, “A space-time block coded OFDM scheme for unknown frequency-selective fading channels,” IEEE Commun. Lett., vol. 5, no. 10,pp.393-395,Oct.2001. [20] W. Su, Z. Safar, M. Olfat, and K. J. R. Liu, “Obtaining full-diversity space-frequency codes from space-time codes via mapping,” IEEE Trans. Signal Processing, vol. 51, no. 11, pp. 2905-2916, Nov. 2003. [21] W. Su, Z. Safar, and K. J. R. Liu, “Full-rate full-diversity space-frequency codes with optimum coding advantage,” IEEE Trans. Inform. Theory, vol. 51, no. 1, pp. 229-49, Jan. 2005. [22] W. Su, Z. Safar, and K. J. R. Liu, “Towards maximum achievable diversity in space, time, and frequency: Performance analysis and code design,” IEEE Trans. Wireless Commun., vol. 4, no. 4, pp. 1847-1857, Jul. 2005 [23] A. Dammann and S. Kaiser, “Standard conformable antenna diversity techniques for OFDM systems and its application to the DVB-T system,” in Proc. IEEE GLOBECOM, 2001, pp. 3100-3105. [24] D. Gore, S. Sandhu, and A. Paulraj, “Delay diversity codes for frequency selective channels,” in Proc. IEEE ICC, 2002, pp. 1949-1953. [25] S. Kaiser, “Spatial transmit diversity techniques for broadband OFDM systems,” in Proc. IEEE GLOBECOM, 2000, pp. 1824-1828. [26] G. Bauch and J. S. Malik, “Cyclic delay diversity with bit-interleaved coded modulation in orthogonal frequency division multiple access,' IEEE Trans. Wireless Commun., vol. 5, pp. 2092-2100, Aug. 2006. [27] A. Assalini, “Maximizing Outage Capacity of OFDM Transmit Diversity Systems,” IEEE Trans. Vehicular Tech., vol. 55, no. 9, pp. 4786-4794, Nov. 2009. [28] Y.-J. Kim, H.-Y. Kim, M. Rim, and D.-W. Lim, “On the Optimal Cyclic Delay Value in Cyclic Delay Diversity,” IEEE Trans. Broadcasting, vol. 55, no. 4, pp. 790-795, Dec. 2009. [29] Y. H. Zeng and T. S. Ng, “Pilot cyclic prefixed single carrier communication: channel estimation and equalization,” IEEE Signal Processing Lett., vol. 12, no. 1, pp. 56-59, Jan. 2005. [30] J. coon, M. Beach, J. McGeehan, “Optimal training sequences for channel estimation in cyclic-prefix-based single-carrier systems with transmit diversity,” IEEE Signal Processing Lett., vol. 11, no. 9, pp. 729-732, Sep. 2004. [31] P. Hoeher, S. Kaiser, and P. Robertson, “Pilot-symbol-aided channel estimation in time and frequency,” in Proc. IEEE GLOBECOM, 1997, pp. 90-96. [32] O. Edfors, M. Sandell, J.-J. vandeBeek, S. K. Wilson, and P. O. Brjesson, “OFDM channel estimation by singular value decomposition,” IEEE Trans. Commun., vol. 46, no. 7, pp. 931-939, July 1998. [33] Y. (G.) Li, “Pilot-symbol-aided channel estimation for OFDM in wireless systems,” IEEE Trans. Vehicular Tech., vol. 49, no. 4, pp. 1207-1215, July 2000. [34] M. Morelli and U. Mengali, “A comparison of pilot-aided channel estimation methods for OFDM systems,” IEEE Trans. Signal Processing, vol. 49, no. 12, pp. 3065-3073, Dec. 2001. [35] S. Ohno and G. B. Giannakis, “Optimal training and redundant precoding for block transmissions with application to wireless OFDM,” IEEE Trans. Commun., Vol. 50, No. 12, Dec. 2002, pp. 211 [36] R. Negi and J. Cioffi, “Pilot tone selection for channel estimation in a mobile OFDM system,” IEEE Trans. Consumer Electronics, Vol. 44, No. 3, pp. 1122-1128, Aug. 1998. [37] X. Cai and G. B. Giannakis, “Error Probability Minimizing Pilots for OFDM With M-PSK Modulation Over Rayleigh-Fading Channels” IEEE Trans. Vehicular Tech, vol. 53, no. 1, pp. 146-155, Jan. 2004. [38] S. Adireddy, L. Tong, and H. Viswanathan, “Optimal Placement of Training for Frequency-Selective Block-Fading Channels” IEEE Trans. Inform. Theory, vol. 48, no. 8, pp. 2338-2353, Aug. 2002. [39] M. Dong and L. Tong, “Optimal Design and Placement of Pilot Symbols for Channel Estimation,” IEEE Trans. Signal Processing, vol. 50, no. 12, pp. 3055-3069, Dec. 2002. [40] I. Barhumi, G. Leus, and M. Moonen, “Optimal training design for MIMO OFDM systems in mobile wireless channels,” IEEE Trans. Signal Processing, vol. 51, No. 6, pp 1615-1624, June 2003. [41] H. Minn and N. Al-Dhahir, “Optimal Training Signal for MIMO-OFDM Channel Estimation,” IEEE Trans. Wireless Commun., vol. 5, no. 5, pp. 1158-1168, May. 2006. [42] F. Gao and A. Nallanathan, “Blind Channel Estimation for OFDM Systems via a Generalized Precoding,” IEEE Trans. Vehicular Tech., vol. 56, pp. 1155-1164, May 2007. [43] R. W. Heath and G. B. Giannakis, “Exploiting input cyclostationarity for blind channel identification in OFDM systems,” IEEE Trans. Signal Processing, vol. 37, no. 3, pp. 848-856, Mar. 1999. [44] B. Muquet, M. de Courville, and P. Duhamel, “Subspace-based blind and semi-blind channel estimation for OFDM systems,” IEEE Trans. Signal Processing, vol. 50, pp. 1699-1712, July 2002. [45] C. Li and S. Roy, “Subspace-based blind channel estimation for OFDM by exploiting virtual carriers,” IEEE Trans. Wireless Commun., vol. 2, no. 1, pp. 141-150, Jan. 2003. [46] C. Shin, R. W. Heath, Jr., and E. J. Powers, “Blind channel estimation for MIMO-OFDM systems,” IEEE Trans. Vehicular Tech., vol. 56, no. 2, pp. 670-685, Mar. 2007. [47] B. Farhang-Boroujeny, “Pilot-based channel identification: proposal for semi-blind identification of communication channels,” IEE Electron. Lett., vol. 31, no. 13, pp. 1044-1046, June 1995. [48] G. T. Zhou, M. Viberg, and T. McKelvey, “First-order statistical method for channel estimation,” IEEE Signal Processing Lett., vol. 10, no. 3, pp. 57-60, Mar. 2003. [49] J. Tugnait and W. Luo, “On channel estimation using superimposed training and first-order statistics,” IEEE Commun. Lett., vol. 7, no. 9, pp. 413-415, Sep. 2003. [50] A. G. Orozco-Lugo, M. M. Lara, and D. C. McLernon, “Channel estimation using implicit training,” IEEE Trans. Signal Processing, vol. 52, no. 1, pp. 240-254, Jan. 2004. [51] M. Ghogho, D. McLernon, E. Alameda-Hernandez, and A. Swami, “Channel estimation and symbol detection for block transmission using data-dependent superimposed training,” IEEE Signal Processing Lett., vol. 12, no. 3, pp. 226-229, Mar. 2005. [52] C.-P. Li and W.-C. Huang, “Semi-blind channel estimation using superimposed training sequences with constant magnitude in dual domain for OFDM Systems” in Proc. IEEE VTC-Spring, 2006, vol. 4, pp. 1575-1579. [53] T. Cui and C. Tellambura, 'Superimposed pilot symbols for channel estimation in OFDM systems' in Proc. IEEE GLOBECOM, 2005, vol. 4, pp. 2229-2233. [54] W.-C. Huang, C.-P. Li, and H.-J. Li, “On the power allocation and system capacity of OFDM systems using superimposed training schemes,” IEEE Trans. Vehicular Tech., vol. 58, pp. 1731-1740, May 2009. [55] J. K. Tugnait and X. Meng, “On superimposed training for channel estimation: performance analysis, training power allocation, and frame synchronization,” IEEE Trans. Signal Processing, vol. 54, no. 2, pp.752-765, Feb. 2006. [56] Y. Wang, J. Oostveen, A. Filippi, and S. Wesemann, “A novel preamble scheme for packet-based OFDM WLAN,” in Proc IEEE WCNC, 2007, pp. 1483-1487. [57] M. Ahmadi and A. S. Mehr, “Superimposed training aided carrier frequency offset estimation in OFDM systems,” in Proc. IEEE EIT, 2007, pp. 296-299. [58] C.-P. Li and W.-W. Hu, “Super-imposed training scheme for timing and frequency synchronization in OFDM systems,” IEEE Trans. Broadcasting, vol. 53, issue 2, pp. 574-583, June 2007. [59] S. Lu and N. Al-Dhahir, “A novel CDD-OFDM scheme with pilot-aided channel estimation,” IEEE Trans. Wireless. Commun., vol. 8, no. 3, pp. 1122-1127, Mar. 2009. [60] M. Medard, “The effect upon channel capacity in wireless communication of perfect and imperfect knowledge of channel,” IEEE Trans. Inform. Theory, vol. 46, pp. 933-946, May 2000. [61] B. R. Saltzberg, “Performance of an efficient parallel data transmission system,” IEEE Trans. Commun. Technol., vol. COM-15, no.6, pp. 805-811, Dec.1967. [62] S. Weinstein and P. Ebert, “Data transmission by frequency-division multiplexing using the discrete Fourier transform,” IEEE Trans. Commun. Technol., vol. COM-19, no. 5, pp. 628-634, Oct. 1971 [63] Z. Liu, Y. Xin, and G. B. Giannakis, “Linear constellation precoding for OFDM with maximum multipath diversity and coding gains,” IEEE Trans. Commun., vol. 51, no. 3, pp. 416-427, Mar. 2003. [64] D. Huang, K. B. Letaief, and J. Lu, “Bit-interleaved time-frequency coded modulation for OFDM systems over time-varying channels,” IEEE Trans. Commum., vol. 53, no. 7, pp. 1191-1199, July, 2005. [65] J. I. Montojo and L. B. Milstein, “Effects of imperfections on the performance of OFDM systems,” IEEE Trans. Commun., vol. 57, no. 7, pp. 2060-2070, July 2009. [66] X. Wang, P. Ho, and Y. Wu, “Robust channel estimation and ISI cancellation for OFDM systems with suppressed features,” IEEE J. Select. Areas Commun., vol. 23, no. 5, pp. 963-972, May 2005. [67] S. Chen and C. Zhu, “ICI and ISI analysis and mitigation for OFDM systems with insufficient cyclic prefix in time-varying channels,” IEEE Trans. Consumer Electronics, vol. 50, no. 1, pp. 78-83, Feb. 2004. [68] K. Dukhyun and G.L. Stuber, “Residual ISI cancellation for OFDM with applications to HDTV broadcasting,” IEEE J. Select. Areas Commun., vol. 16, no. 8, pp. 1590-1599, Oct. 1998. [69] J. Yang and K. Cheun, “Low complexity implementation of Alamouti space-time coded OFDM transmitters,” IEEE Commun. Lett., vol. 8, no. 4, pp. 229-231, Apr. 2004. [70] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall 1993. [71] S. Ohno and G. B. Giannakis, “Capacity maximizing MMSE-optimal pilots for wireless OFDM over frequency-selective block Rayleigh-fading channels,” IEEE Trans. Inform. Theory, vol. 50, pp. 2138-2145, Sep. 2004. [72] N. Chen and G. T. Zhou, “Superimposed training for OFDM: a peak-to-average power ratio analysis,” IEEE Trans. Signal Processing, vol. 54, no. 6, pp. 2277-2287, June 2006. [73] C.-P. Li and W.-C. Huang, “A constructive representation for the Fourier dual of the Zadoff-Chu sequences,” IEEE Trans. Inform. Theory, vol. 53, no. 11, pp. 4221-4224, Nov. 2007. [74] B. M. Popovic “Generalized chirp-like polyphase sequences with optimum correlation properties,” IEEE Trans. Inform. Theory, vol. 38, no. 4, pp. 1406-1409, July 1992. [75] D. Bini. and V. Pan, Polynomial and Matrix Computations, Vol. 1: Fundamental Algorithms, Boston, MA: Birkhauser, 1994. [76] S. Ohno and G. B. Giannakis, “Capacity maximizing MMSE-optimal pilots for wireless OFDM over frequency-selective block Rayleigh-fading channels,” IEEE Trans. Inform. Theory, vol. 50, pp. 2138-2145, Sep. 2004. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44646 | - |
| dc.description.abstract | 多重輸入與多重輸出 (multiple-input multiple-output, MIMO)技術可以有效增進正交分頻多工 (orthogonal frequency division multiplexing, OFDM)系統的效能。近幾年來，有文獻提出循環延遲多樣性(cyclic delay diversity, CDD)技術以利用多根傳送天線所提供的多樣性。和傳統的傳送多樣性技術相比，例如塊狀時空編碼(space-time block coding , STBC)，循環延遲多樣性技術的主要優點為對通道響應的限制條件較寬鬆以及傳輸端和接收端都有較低的複雜度。
一般而言，通道資訊(channel state information, CSI)在同調解調中是不可或缺的。而在多路徑通道的環境當中，通道估測多半利用領航訊號輔助調變法(pilot symbol assisted modulation, PSAM)而達成。領航訊號的架構更對通道估測的準確度有決定性的影響。然而，針對傳統多重輸入與多重輸出正交分頻多工系統所提出最小化通道估測均方誤差(mean square error, MSE)的最佳化領航訊號序列，並不適用於循環延遲多樣性正交分頻多工系統。在本篇論文當中，我們將推導出最佳化領航訊號的架構，能最小化循環延遲多樣性正交分頻多工系統中通道估測的均方誤差。理論推導結果顯示，妥善設計領航訊號以及循環延遲可以最小化通道估測的均方誤差。我們並利用模擬結果驗證所推導出的領航訊號序列的確能達到通道估測均方誤差的下限。 由於領航訊號輔助調變法中領航訊號子載波的使用會降低頻寬使用效率，本論文將更進一步探討在循環延遲多樣性正交分頻多工系統中利用疊加序列法(superimposed training, ST)進行通道估測的架構。在疊加序列法當中，領航訊號直接和資料序列相加後送出。理論分析結果顯示，針對領航訊號輔助調變法所推導的最佳化領航訊號序列，也能夠最小化疊加序列通道估測法的均方誤差。此外，當假設領航序列的能量固定時，我們發現通道估測的效能和領航序列的長度無關。 本論文最後分析在領航訊號輔助調變法和疊加序列法這兩種架構中循環延遲多樣性正交分頻多工系統的平均通道容量(average channel capacity)。我們推導出領航訊號的最佳傳送能量比值，以最大化平均通道容量的下限。研究結果顯示，當通道假設在連續多個正交分頻多工符元中有相同的通道響應，疊加序列法可以達到比領航訊號輔助調變法更高的系統容量(system capacity)。 | zh_TW |
| dc.description.abstract | Multiple-input multiple-output (MIMO) technique is an attractive candidate for performance improvement in orthogonal frequency division multiplexing (OFDM) systems. Recently, cyclic delay diversity (CDD) scheme is developed in order to exploit the transmit diversity offered by multiple transmit antennas. The main advantages of CDD over traditional transmit diversity technique, e.g., space-time block coding (STBC), are the easier requirement for channel response and the fact that transmitter and receiver both have relatively lower complexity.
Channel state information (CSI) is generally required for coherent demodulation technique. In multi-path environments, channel estimation is typically performed by using pilot symbol assisted modulation (PSAM) scheme. The accuracy of channel estimation is critically dependent on the structure of pilot sequences. However, the optimal pilot sequences, being derived to minimize the mean square error (MSE) of channel estimation in traditional MIMO-OFDM systems, are not suitable for CDD-OFDM systems. In this dissertation, we present a general expression of the optimal pilot sequences for channel estimation in CDD-OFDM systems. The derived results illustrate that the MSE of channel estimation can be minimized if pilot sequences and cyclic-delays are appropriately designed. Through simulation experiments, we confirm that the MSE of channel estimation using the proposed pilot sequences achieves the lower bound in CDD-OFDM systems. Since PSAM schemes require the use of dedicated pilot sub-carriers, the bandwidth utilization is substantially reduced. Therefore, the dissertation further investigates a channel estimation approach for CDD-OFDM systems using a superimposed training (ST) scheme, in which pilot symbols are superimposed onto data streams prior to transmission. It is revealed that the developed pilot sequences are also optimal for ST-based channel estimation in CDD-OFDM systems. Additionally, under the assumption that the total power of pilot sequence is a constant, we show that the performance of channel estimation is independent of the length of pilot sequence. Under both PSAM and ST schemes, the average channel capacity of CDD-OFDM systems is investigated. Moreover, the optimal ratios of pilot symbol power to total transmission power are analyzed in order to maximize the lower bound of average channel capacity. The current results show that, when channel is assumed to be stationary over a number of OFDM symbols, the ST-based channel estimation schemes yield a higher system capacity than PSAM-based channel estimation schemes. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T03:52:14Z (GMT). No. of bitstreams: 1 ntu-99-D95942017-1.pdf: 801778 bytes, checksum: ba3cb5bb9716f3126d9eb86c7e9f110f (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | ABSTRACT I
CONTENTS V LIST OF FIGURES IX LIST OF TABLES XI Chapter 1 INTRODUCTION 1 1.1 OFDM and MIMO 1 1.2 Channel estimation 3 1.3 Motivation and contribution 5 1.4 Overview 7 Chapter 2 MIMO-OFDM SYSTEMS 9 2.1 Introduction 9 2.2 Channel model 11 2.3 Concept of OFDM 12 2.4 OSTBC-based technique in OFDM systems 15 A. OSTBC-OFDM 16 B. OSFBC-OFDM 22 2.5 Cyclic-delay diversity in OFDM systems 23 A. The concept of CDD-OFDM systems 23 B. The value of cyclic-delay 27 2.6 Simulation results and discussions 28 2.7 Summary 32 Chapter 3 PSAM CHANNEL ESTIMATION IN CDD-OFDM SYSTEMS 35 3.1 Introduction 35 3.2 PSAM channel estimation 37 A. Analysis on LS channel estimation 41 B. Analysis on MMSE channel estimation 42 3.3 Optimal pilot sequence design 44 A. The case of k=i 45 B. The case of k≠i 46 3.4 Discussions and examples 50 A. Optimal pilot sequences design with specified λq 50 B. Optimal pilot sequence design with specified tq 51 3.5 Simulation results 53 3.6 Summary 57 Appendix-3A 59 Appendix-3B 60 Chapter 4 ST CHANNEL ESTIMATION IN CDD-OFDM SYSTEMS 61 4.1 Introduction 61 4.2 System model 62 4.3 Analysis on ST channel estimators 65 A. LS channel estimator 66 B. MMSE channel estimator 68 4.4 Simulation results and discussions 70 4.5 Summary 73 Chapter 5 SYSTEM CAPACITY AND POWER ALLOCATION 75 5.1 Introduction 75 5.2 Analysis on PSAM-based CDD-OFDM systems 76 A. The range of optimal power allocation factor 81 B. Approximated optimal power allocation factor 82 5.3 Analysis on ST-based CDD-OFDM systems 84 A. The range of optimal power allocation factor 87 B. Approximated value of optimal power allocation factor 88 5.4 Simulation results and discussions 90 5.5 Summary 101 Appendix-5A 103 Chapter 6 CONCLUSIONS 107 REFERENCES 111 AUTHOR PUBLICATIONS 121 | |
| dc.language.iso | en | |
| dc.subject | 系統容量 | zh_TW |
| dc.subject | 正交分頻多工系統 | zh_TW |
| dc.subject | 多重輸入與多重輸出 | zh_TW |
| dc.subject | 循環延遲多樣性 | zh_TW |
| dc.subject | 通道估測 | zh_TW |
| dc.subject | 領航訊號輔助調變 | zh_TW |
| dc.subject | 疊加序列 | zh_TW |
| dc.subject | system capacity | en |
| dc.subject | Orthogonal frequency division multiplexing (OFDM) | en |
| dc.subject | multiple input multiple output (MIMO) | en |
| dc.subject | cyclic delay diversity (CDD) | en |
| dc.subject | channel estimation | en |
| dc.subject | pilot symbol assisted modulation (PSAM) | en |
| dc.subject | superimposed training (ST) | en |
| dc.title | 循環延遲多樣性正交分頻多工系統中通道估測之領航訊號最佳化設計 | zh_TW |
| dc.title | Optimal Design of Pilot Symbols for Channel Estimation in CDD-OFDM Systems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.coadvisor | 李志鵬 | |
| dc.contributor.oralexamcommittee | 闕志達,陳光禎,蘇炫榮,李啟民,陳柏穎 | |
| dc.subject.keyword | 正交分頻多工系統,多重輸入與多重輸出,循環延遲多樣性,通道估測,領航訊號輔助調變,疊加序列,系統容量, | zh_TW |
| dc.subject.keyword | Orthogonal frequency division multiplexing (OFDM),multiple input multiple output (MIMO),cyclic delay diversity (CDD),channel estimation,pilot symbol assisted modulation (PSAM),superimposed training (ST),system capacity, | en |
| dc.relation.page | 122 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-07-09 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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