臺灣博碩士論文加值系統

在正交分頻多工系統(Orthogonal Frequency Division Multiplexing, OFDM)中，盲式估測可以獲得較高的頻譜使用效益。在盲式資料偵測系統中，因為傳送的訊號中沒有領航訊號加在其中，因此接收端做資料偵測時，有資料模糊性(Ambiguity)的問題，目前解決資料模糊性的方法大致可分為三種：加入領航訊號(Pilot Signal)、使用疊加序列(Superimposed Training)、或是利用通道編碼(Channel Coding)，而本論文為了能夠達到完全地盲式估測，在此我們將以通道編碼的方式來解決資料模糊性。在既有文獻中已有人針對低密度奇偶校驗編碼(Low-Density Parity-Check Codes, LDPC)，提出在BPSK調變下可避免模糊性的編碼方式。而在本篇論文中，我們考慮更為泛用的線性區塊編碼(Linear Block Code, LBC)，並將其推廣至其他常見的高階調變，包括QPSK，16QAM，以及64QAM，在調變技術符合格雷編碼的前提下，我們歸納出產生模糊性的內積變化量，並進一步推導產生不具模糊性之線性區塊編碼的充份條件，只要線性區塊編碼符合該條件，便可確保其碼字不具模糊性，以達到完全盲式估測的目的。最後，在模擬的章節中，我們將分別針對不具模糊性與具有模糊性的線性區塊編碼進行資料估測，為了公平起見，具有模糊性的編碼會再搭配領航訊號，以解決模糊性的問題，由模擬結果可以看出，兩種編碼方式在高訊號雜訊比(Signal to Noise Ratio, SNR)的情況下具有相當接近的效能，換言之，只要採用適當的通道編碼，其符合我們所提出來充份條件，便可在效能幾乎無損的情況下，更進一步地提高頻譜使用效率。

In orthogonal frequency division multiplexing (OFDM) system, blind estimator was proposed which can obtain high bandwidth efficiently. There is a serious ambiguity problem in blind data detector structure. Solution methods can divide into three cases: pilot signal, superimposed training, and channel coding. In order to achieve totally blind estimate, we use channel coding to solve ambiguity in this thesis. In previous study, it had been use low-density-parity-check code (LDPC) to solve ambiguity, and proposed an encoding method to avoid ambiguity for BPSK. However, we consider generic linear block code (LBC) and want to extend BPSK modulation to higher modulation scheme, including QPSK, 16QAM, and 64QAM. For any constellation follows grey coding, we induct a difference of inner product for ambiguity and derive some sufficient conditions for LBC. If LBC satisfy some conditions, then it could avoid ambiguity between valid code words and it can achieve totally blind estimate. In simulation section, for data estimate, we respectively use two LBC cases, which exist ambiguity or not. In order to be fair, we insert a pilot to solve ambiguity in LBC, which exist ambiguity. In simulation results, the performance of two cases is similar in high signal to noise ratio (SNR). In other words, if we use proper channel code which it satisfy sufficient conditions, then we can increase bandwidth efficiently.

致謝 I
論文鑑定書 II
中文摘要 IIII
Abstract IV
目錄 V
圖目錄 VII
第 一 章 導論 1
1.1 研究動機 1
1.2 論文架構 3
第 二 章 正交分頻多工系統 4
2.1 正交分頻多工系統架構 4
第 三 章 傳統盲式資料偵測架構 8
第 四 章 不具有資料模糊性的通道編碼 11
4.1 格雷碼的特性 11
4.2 符合格雷碼特性的調變機制與提出的定理 12
4.3 利用通道編碼解決資料模糊性 18
4.3.1 利用LDPC解決BPSK資料模糊性 18
4.3.2 利用LBC解決高階層調變資料模糊性 19
4.3.2.1 整數倍的調變位元向量定理 20
4.3.2.2 非整數倍的調變位元向量定理 21
4.3.2.3 如何設計出所有碼字都滿足各自內積取2的餘數皆為0或1 24
4.4 基於推導的理論而提出新的架構圖 25
第 五 章 模擬結果 28
第 六 章 結論 36
參考文獻 37
中英對照表 41
縮寫 45

[1]Y. Sun, “Bandwidth-efficient wireless OFDM,” IEEE J. Sel. Areas Commun., vol. 19, no. 11, pp. 2267-2278, Nov. 2001.
[2]M. Wang, L. Xiao, T. Brown, and M. Dong, “Optimal symbol timing for OFDM wireless communications,” IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 5328–5337, Oct. 2009.
[3]Y. Wu and W. Y. Zou, “Orthogonal frequency division multiplexing: A multi-carrier modulation scheme,” IEEE Trans. Consum. Electron., vol. 41, no. 3, pp. 392–399, Aug. 1995.
[4]L. J. Cimini, Jr., “Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing,” IEEE Trans. Commun., vol. COM-33, pp. 665–675, July 1985.
[5]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.
[6]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.
[7]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.
[8]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.
[9]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.
[10]W.-W. Hu and C.-P. Li, “An efficient inter-carrier inteference cancellation scheme for OFDM systems with frequency estimation errors,” IEICE Trans. on Commun., vol.E93-B, no.12, pp. 3600-3605, Dec. 2010.
[11]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.
[12]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.
[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]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.
[15]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.
[16]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.
[17]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.
[18]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.
[19]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.
[20]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.
[21]D. Warrier and U. Madhow, “Spectrally efficient noncoherent communication,” IEEE Trans. Inform. Theory, vol. 48, no. 3, pp. 651–668, Mar. 2002.
[22]T. Cui and C. Tellambura, “Joint data detection and channel estimation for OFDM systems,” IEEE Trans. Commun., vol. 54, no. 4, Apr. 2006.
[23]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.
[24]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.
[25]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.
[26]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.
[27]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.
[28]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.
[29]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.
[30]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.
[31]S. Ohno and G. B. Giannakis, “Optimal training and redundant precoding for block transmissions with application to wireless OFDM,” IEEE Trans. Commun., vol. 50, pp. 2113-2123, Dec. 2002.