臺灣博碩士論文加值系統

在本篇研究中我們提出一個盲式資料估測器的低複雜度方案。在本篇論文中我們採用廣義可能性比率測試(Generalized Likelihood Ratio Test, GLRT)資料檢測器，但由於傳統廣義可能性比率測試(Generalized Likelihood Ratio Test, GLRT)資料檢測器的計算複雜度太高，因此在先前的研究中有提出子載波分組切割的方案。在文獻中提到子載波的大小不能小於通道階數的限制，因此我們提出了一個新的在廣義可能性比率測試(Generalized Likelihood Ratio Test, GLRT)資料檢測器上的子載波分組切割的想法，使用子載波連續切割的方式，讓子組的通道長度可以視為更小，突破文獻中交錯切割子組時，子載波大小必須要大於通道長度的限制，使得在做分組的GLRT資料檢測的時候可以讓子組的大小更小，藉此讓複雜度進一步降低。
此外我們把原先的OFDM系統架構推廣到SFBC-OFDM (Space Frequency Block Code Orthogonal Frequency Division Multiplexing)系統上，發現到在經過SFBC編碼後在做GLRT資料檢測的時候除了既有的相位模糊(Phase Ambiguity)問題之外，還會有額外的編碼模糊(Code Ambiguity)問題。先前的研究是使用領航訊號(Pilot Signal)解決相位模糊問題，在本篇研究中，我們提出一種利用調變的方式同時解決兩種模糊性問題。
模擬結果顯示我們提出的方法可以同時解決這兩種模糊性問題，並且透過子載波連續切割的方式可以降低系統的運算複雜度，同時我們使用的旋轉星座點的方法不會損失頻寬效益也不用加領航訊號，可以稱作完全的盲式(Totally Blind)估測。

In this research, a low-complexity blind data detector scheme for orthogonal frequency division multiplexing (OFDM) system is proposed, where the generalized likelihood ratio test (GLRT) approach is adopted. The traditional GLRT data detector (GDD) suffers from prohibitively high computational complexity since all the subcarriers are jointly considered. Therefore, previous studies proposed a sub-group GDD (SGDD) by progressively dealing with a subgroup of subcarriers at one time. It is shown that, the unique solution of SGDD is guaranteed if the size of sub-group is larger than the order of channel impulse response (CIR). In this study, we proved that the size of SGDD can be even smaller than the channel order if the partition meets some requirements. Furthermore, the proposed partition method is extended to SFBC-based MIMO-OFDM systems. It is worth noting that, most of the SFBC, including Alamouti-SFBC, are rotatable, which leads to a code ambiguity. In this research, we introduce an asymmetric modulation to solve this problem. Simulation results show that the computational complexity is significantly reduced by adopting this novel sub-carrier partition scheme. In addition, the code ambiguity and sign ambiguity, which require extra pilot symbols in existing literatures, can be simultaneously solved by our proposed asymmetric modulation without sacrificing any bandwidth efficiency.

論文審定書 i
誌謝 ii
中文摘要 iii
Abstract iv
目錄 v
圖次 vii
第一章 導論 1
1.1 研究動機 1
1.2 論文架構 3
第二章 系統介紹 4
2.1 正交分頻多工系統架構 4
2.2 空時區塊編碼介紹 5
2.3 空頻區塊編碼之正交分頻多工系統介紹 6
第三章 傳統盲式估測架構 10
3.1 GLRT資料偵測器 10
3.2 降低搜尋空間GLRT Data Detector分組 11
3.3 盲估測的相位模糊 12
3.4 SFBC編碼使用盲估測器的模糊性問題 12
第四章 子載波連續切割分組方案 15
第五章 提出的在SFBC解決模糊性的方案 19
5.1 提出的SFBC-OFDM盲估測架構 19
5.2 提出的模糊性問題解決方案 22
第六章 模擬分析與討論 27
第七章 結論 33
參考文獻 34
中英對照表 43
縮寫對照表 46

[1] W.-C. Huang, Y.-S. Yang, C.-P. Li, and H.-J. Li, “A new pilot architecture for sub-band uplink OFDMA systems,” IEEE Trans. Broadcast., vol. 59, no. 3, pp. 461-470, June 2013.
[2] W.-W. Hu, C.-P. Li, and J.-C. Chen, “Peak power reduction for pilot-aided OFDM systems with semi-blind detection,” IEEE Commun. Lett., vol. 16, no. 7, pp. 1056-1059, July 2012.
[3] S.-H. Wang, J.-C. Xie, C.-P. Li, and Y.-F. Chen, “A low-complexity PAPR reduction scheme for OFDMA uplink systems,” IEEE Trans. Wireless Commun., vol. 10, no. 4, pp. 1242-1251, Apr. 2011.
[4] C.-P. Li, S.-H. Wang, and K.-C. Chan, “Low complexity transmitter architectures for SFBC MIMO-OFDM systems,” IEEE Trans. Commun., vol. 60, issue 6, pp. 1712-1718, June 2012.
[5] W.-C. Huang, C.-P. Li, and H.-J. Li, “Optimal pilot sequence design for channel estimation in CDD-OFDM systems,” IEEE Trans. Wireless Commun., vol. 11, no. 11, pp. 4006-4016, Nov. 2012.
[6] J.-C. Chen, M.-H. Chiu, Y.-S. Yang, and C.-P. Li, “A suboptimal tone reservation algorithm based on cross-entropy method for PAPR reduction in OFDM systems,” IEEE Trans. Broadcast., vol. 57, no. 3, pp. 752-756, Sept. 2011.
[7] J.-C. Chen and C.-P. Li, “Tone reservation using near-optimal peak reduction tone set selection algorithm for PAPR reduction in OFDM systems,” IEEE Signal Process. Lett., vol. 17, no. 11, pp. 933-936, Nov. 2010.
[8] C.-P. Li and W.-W. Hu, “Super-imposed training scheme for timing and frequency synchronization in OFDM systems,” IEEE Trans. Broadcast., vol. 53, issue 2, pp. 574-583, June 2007.
[9] 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. Veh. Technol., vol. 58, no. 4, pp. 1731-1740, May 2009.
[10]W.-C. Huang, C.-P. Li, and H.-J. Li, “An investigation into the noise variance and the SNR estimators in imperfectly-synchronized OFDM systems,” IEEE Trans. Wireless Commun., vol. 9, no. 3, pp. 1159-1167, Mar. 2010.
[11] C.-P. Li, S.-H. Wang, and C.-L. Wang, “Novel low-complexity SLM schemes for PAPR reduction in OFDM systems,” IEEE Trans. Signal Process., vol. 58, no. 5, pp. 2916-2921, May 2010.
[12] W.-C. Huang, C.-H. Pan, C.-P. Li, and H.-J. Li, “Subspace-based semi-blind channel estimation in uplink OFDMA systems,” IEEE Trans. Broadcast., vol. 56, no. 1, pp. 58-65, Mar. 2010.
[13]S.-H. Wang and C.-P. Li, “A low-complexity PAPR reduction scheme for SFBC MIMO-OFDM systems,” IEEE Signal Process. Lett., vol. 16, no. 11, pp. 941-944, Nov. 2009.
[14] W.-C. Huang, C.-P. Li, and H.-J. Li, “A computationally efficient DFT scheme for applications with a subset of non-zero inputs,” IEEE Signal Process. Lett., vol. 15, pp. 206-208, 2008.
[15]S.-H. Wang, J.-C. Xie, C.-P. Li, and Y.-F. Chen, “A low-complexity PAPR reduction scheme for OFDMA uplink systems,” IEEE Trans. Wireless Commun., vol. 10, no. 4, pp. 1242-1251, Apr. 2011.
[16]C.-P. Li, S.-H. Wang, and C.-L. Wang, “Novel low-complexity SLM schemes for PAPR reduction in OFDM systems,” IEEE Trans. Signal Process., vol. 58, no. 5, pp. 2916-2921, May 2010.
[17]S.-H. Wang and C.-P. Li, “A low-complexity PAPR reduction scheme for SFBC MIMO-OFDM systems,” IEEE Signal Process. Lett., vol. 16, no. 11, pp. 941-944, Nov. 2009.
[18]Q. Huang, M. Ghogho, J. Wei, and P. Ciblat, “Practical timing and frequency synchronization for OFDM based cooperative systems,” IEEE Trans. Signal Process., vol. 58, no. 7, pp. 3706–3716, July 2010.
[19]W.-C. Huang, C.-P. Li, and H.-J. Li, “An investigation into the noise variance and the SNR estimators in imperfectly-synchronized OFDM systems,” IEEE Trans. Wireless Commun., vol. 9, no. 3, pp. 1159-1167, Mar. 2010.
[20]W.-W. Hu and C.-P. Li, “An efficient inter-carrier inteference cancellation scheme for OFDM systems with frequency estimation errors,” IEICE Trans. Commun., vol.E93-B, no.12, pp. 3600-3605, Dec. 2010.
[21]M. Hsieh and C. Wei, “Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels,” IEEE Trans. Consumer Electron., vol. 44, no. 1, Feb. 1998.
[22]S. Coleri, M. Ergen, and A. Bahai, “Channel estimation techniques based on pilot arrangement in OFDM systems,” IEEE Trans. Broadcast., vol. 48, pp. 223–229, Sept. 2002.
[23]R. Negi and J. Cioffi, “Pilot tone selection for channel estimation in a mobile OFDM system,” IEEE Trans. Consumer Electron., vol. 44, pp. 1122–1128, Aug. 1998.
[24] F. Gao and A. Nallanathan, “Blind channel estimation for OFDM systems via a generalized precoding,” IEEE Trans. Veh. Technol., vol. 56, no. 3, pp. 1155–1164, May 2007.
[25]C. Shin, R. W. Heath, Jr., and E. J. Powers, “Blind channel estimation for MIMO-OFDM systems,” IEEE Trans. Veh. Technol., vol. 56, no. 2, pp. 670–685, Mar. 2007.
[26]L. Tong, G. Xu, B. Hassibi, and T. Kailath, “Blind channel identification based on second-order statistics: A frequency-domain approach,” IEEE Trans. Inform. Theory, vol. 41, no. 1, pp. 329–334, Jan. 1995.
[27]W.-K. Ma, “Blind ML detection of orthogonal space-time block codes: Identifiability and code construction,” IEEE Trans. Signal Process., vol. 55, no. 7, pp. 3312–3324, July 2007.
[28]E. G. Larsson, P. Stoica, and J. Li, “Orthogonal space-time block codes: Maximum likelihood detection for unknown channels and unstructured interferences,” IEEE Trans. Signal Process., vol. 51, no. 2, pp. 362–372, Feb. 2003.
[29]Y. Song, S. Roy, and L. A. Akers, “Joint blind estimation of channel and data symbols in OFDM,” in Proc. 51st IEEE Veh. Technol. Conf., Tokyo, Japan, May 2000, vol. 1, pp. 46–50.
[30]T.-H. Chang, C.-W. Hsin, W.-K. Ma, and C.-Y. Chi, “A linear fractional semidefinite relaxation approach to maximum-likelihood detection of higher-order QAM OSTBC in unknown channels,” IEEE Trans. Signal Process., vol. 58, no. 4, pp. 2315–2326, Apr. 2010.
[31]D. Warrier and U. Madhow, “Spectrally efficient noncoherent communication,” IEEE Trans. Inform. Theory, vol. 48, no. 3, pp. 651–668, Mar. 2002.
[32] T. Cui and C. Tellambura, “Joint data detection and channel estimation for OFDM systems,” IEEE Trans. Commun., vol. 54, no. 4, Apr. 2006.
[33] W.-K. Ma, T. N. Davidson, K. M. Wong, Z.-Q. Luo, and P. C. Ching, “Quasimaximum-likelihood multiuser detection using semi-definite relaxation with applications to synchronous CDMA,” IEEE Trans. Signal Process., vol. 50, no. 4, pp. 912–922, Apr. 2002.
[34] L. Zhou, J.-K. Zhang, and K.-M. Wong, “A novel signaling scheme for blind unique identification of Alamouti space-time block-coded channel,” IEEE Trans. Signal Process., vol. 55, no. 6, pp. 2570–2582, June 2007.
[35]B. Hassibi and H. Vikalo, “On the sphere decoding algorithm—Part I: The expected complexity,” IEEE Trans. Signal Process., vol. 53, no. 8, pp. 2806–2810, Aug. 2005.
[36] E. Viterbo and J. Bouros, “A universal lattice code decoder for fading channels,” IEEE Trans. Inf. Theory, vol. 45, no. 5, pp. 1639–1642, July 1999.
[37] W.-K. Ma, B.-N. Vo, T. N. Davidson, and P.-C. Ching, “Blind ML detection of orthogonal space-time block codes: efficient high-performance implementations,” IEEE Trans. Signal Process., vol. 54, no. 2, pp. 738–751, Feb. 2006.
[38] L. Azzam and E. Ayanoglu “Reduced complexity sphere decoding via a reordered lattice representation” IEEE Trans. Commun. vol. 57, no. 9, pp. 2564-2569, Sept. 2009.
[39] T.-H. Chang, W.-K. Ma, and C.-Y. Chi, “Maximum-likelihood detection of orthogonal space-time block coded OFDM in unknown block fading channels,” IEEE Trans. Signal Process., vol. 56, no. 4, pp. 1637–1649, Apr. 2008.
[40] Y.-S. Yang, W.-C. Huang, C.-P. Li, and H.-J. Li, “A low complexity blind data detector for OFDM Systems,” in Proc. 76th IEEE Veh. Technol. Conf., Quebec, Canada, Sep. 2012, vol. 1, pp. 1–5.
[41] A. Scherb, V. Kuhn, and K.-D. Kammeyer, “On phase correct blind deconvolution of flat MIMO channels exploiting channel encoding,“ in IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, PA, USA, March18-23, 2005.
[42] M. C. Necker and G. L. Stuber. “Totally blind channel estimation for OFDM over fast varying mobile channels” in Proc. IEEE. ICC ’02, Apr. 2002, pp. 421–425.
[43] M. Torabi, S. Aissa, and M.-R. Soleymani, “On the BER performance of space-frequency block coded OFDM systems in fading MIMO channels,” IEEE Trans. Wireless Commun., Aug. 2007, vol. 6, no. 8, pp. 3090-3101.
[44] J. H. Jang, H. C. Won, and G. H. Im, “Cyclic prefixed single carrier transmission with SFBC over mobile wireless channels, ” IEEE Signal Process. Lett., vol. 13, no. 5, pp. 261 -264, May 2006.
[45] R. F. H. Fischer and M. Hoch, “Directed selected mapping for peak-to-average power ratio reduction in MIMO OFDM,” Electron. Lett., vol. 42, no. 22, pp. 1289-1290, Oct. 2006.
[46] R. F. H. Fischer and M. Hoch, “Peak-to-average power ratio reduction in MIMO OFDM,” in Proc. IEEE. ICC ‘07, Glasgow, Scotland, June 2007, pp. 762-767.
[47] Z. Latinovic and Y. Bar-Ness, “SFBC MIMO-OFDM peak-to-average power ratio reduction by polyphase interleaving and inversion,” IEEE Commun. Lett., vol. 10, no. 4, pp. 266-268, Apr. 2006.
[48] Z. Wang and Y. Bar-Ness, ”Peak-to-average power ratio reduction by polyphase interleaving and inversion for SFBC MIMO-OFDM with generalized complex orthogonal code,” in Proc. IEEE Conf. Inform. Sci. and Syst. (CISS 2006), Princeton, NY, USA, Mar. 2006, pp. 317-320.
[49] M. Tan, Z. Latinovic, and Y. Bar-Ness, “STBC MIMO-OFDM peak-to-average power ratio reduction by cross-antenna rotation and inversion,” IEEE Commun. Lett., vol. 9, no. 7, pp. 592-594, July 2005.
[50] M. Tan, Z. Latinovic, and Y. Bar-Ness, “STBC MIMO-OFDM peak-to-average power ratio reduction by cross-antenna rotation and inversion,” IEEE Commun. Lett., vol. 9, no. 7, pp. 592-594, July 2005.
[51] Z. Li and X.-G. Xia, “PAPR reduction for repetition space-time-frequency coded MIMO-OFDM systems using Chu sequences,” IEEE Trans. Wireless Commun., vol. 7, no. 4, pp. 1195-1202, Apr. 2008.