跳到主要內容

臺灣博碩士論文加值系統

(18.97.14.86) 您好!臺灣時間:2025/02/20 05:08
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:廖晟輝
研究生(外文):Cheng-Hui Liao
論文名稱:適用於索引調變MIMO-OFDM之聯合通道估測與渦輪等化
論文名稱(外文):Joint Channel Estimation and Turbo Equalization for MIMO-OFDM with Index Modulation
指導教授:翁芳標翁芳標引用關係
口試委員:王忠炫鄭立德
口試日期:2016-07-28
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:英文
論文頁數:52
中文關鍵詞:多輸入多輸出正交分頻多工之索引調變對數概似比值渦輪等化器卡門通道估測渦輪碼
外文關鍵詞:MIMOOFDM-IMLog-Likelihood RatioTurbo EqualizationKalman Channel EstimationTurbo codes
相關次數:
  • 被引用被引用:0
  • 點閱點閱:286
  • 評分評分:
  • 下載下載:25
  • 收藏至我的研究室書目清單書目收藏:0
在現今無線傳輸上,隨著服務資料量不斷的增加需求,多輸入多輸出 (Multiple Input Multiple Output, MIMO) 的技術在通過多種標準下,以提高資料傳輸速率和穩固鏈路。為了降低傳輸功率,結合採用正交分頻多工之索引調變 (Orthogonal Frequency Division Multiplexing With Index Modulation, OFDM-IM) 為其傳輸技術,能利用較少的載波,卻能達到與傳統正交分頻多工 (Orthogonal Frequency Division Multiplexing, OFDM) 一樣的傳輸量,達到對於資料傳輸速率與系統效能的需求,並且降低其峰值功率比 (Peak-to-Average Power Ratio, PAPR)。在接收器使用對數概似比值 (Log-Likelihood Ratio, LLR) 計算索引調變所選擇的載波。並且利用渦輪等化器 (Turbo Equalization) 疊代的特性,以及卡門演算法的通道估測 (Kalman Channel Estimation),使傳送訊號的估測經過疊代及通道消除後會越接近原始訊號。本篇論文主要是研究增加傳輸資料量的多輸入多輸出正交分頻多工之索引調變在頻率選擇衰減通道下情況下,在接收機架構上,使用對數概似比值,以降低其搜尋頻率複雜度,並結合渦輪碼 (Turbo Codes) 以及卡門演算法的通道估測疊代特性降低錯誤率。在不同調變方式下,模擬本論文提出之系統及演算法的錯誤率表現。

With the increasing demand of multimedia services in wireless transmission nowadays, Multiple-Input Multiple-Output (MIMO) technologies are adopted in many standards to enhance the data rate and the link robustness. In order to reduce transmission power, we use OFDM-IM (Orthogonal Frequency Division Multiplexing With Index Modulation) scheme for the transmission scheme, to approach the demand for data transmission rates and error performance. OFDM-IM can use less subcarrier, but have same data rate of OFDM (Orthogonal Frequency Division Multiplexing),and reduce PAPR. (Peak-to-Average Power Ratio) on transmission schemes. At receiver side, in order to reduce computational complexity ,we can use the Log-Likelihood Ratio (LLR) to search which subcarrier is active. Exploit Turbo Equalization and Kalman Channel Estimation send a closer estimation back to update the equalizer parameters and to recover the original transmitted symbols. In the thesis, we use MIMO OFDM-IM adopt fading- channel on the transmission side. At receiver side we use LLR combine Turbo codes and Kalman Channel Estimation to get better performance. Simulation results will show that the performance of system and algorithm.

Abstract ii
List of Figure iv
Chapter 1 Introduction 1
Chapter 2 Background 6
2.1 Multiple-Input Multiple-Out (MIMO) 6
2.2 Orthogonal Frequency Division Multiplexing (OFDM) 7
2.3 Turbo Code 10
2.3.1 Convolutional Code 11
2.3.2 Interleaver 12
2.4 Kalman 13
2.5 Major Prombles of OFDM 13
2.5.1 Peak to Average Power 13
2.5.2 Inter-carrier Interference 14
Chapter 3 Transmitter of MIMO OFDM-IM System 16
3.1 System Description 16
3.2 PAPR of OFDM 18
Chapter 4 Receiver of MIMO OFDM-IM with terbo equalization and Channel estimation 21
4.1 Receiver System Decription 21
4.2 Detection of MIMO OFDM-IM Scheme 22
4.3 Turbo Equalization 26
4.4 Kalman channel estimation 29
Chapter 5 Simulation Result 34
Chapter 6 Conclusion 49
Bibliography 50



[1]J. Andrews, S. Buzzi, W. Choi, S. Hanly, A. Lozano, A. Soong, and J.Zhang, “What will 5G be?,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, Jun. 2014.
[2]V. Namboodiri, H. Liu, and P. Spasojevi`c, “Low complexity turbo equalization for mobile MIMO OFDM systems,” accepted in ICCSP 2011.
[3]D. Grieco, J.-L. Pan, R. Olesen, and N. Shah, “ Uplink Single-User MIMO for 3GPP LTE,” in Proc. PIMRC 2007, pp. 1 - 5, Sep. 2007
[4]T.C.W. Schenk, and Allart van Zelst, “Frequency synchronization for MIMO OFDM wireless LAN systems,?Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th , Volume: 2 , Page(s):781 – 785 , 6-9 Oct. 2003.
[5]Koetter, R.; Singer, A.C.; Tüchler, M., “Turbo equalization”, Signal Processing Magazine, VOL. 21, IEEE, Jan. 2004
[6]Baohao Chen; Qimei Cui; Fan Yang; Jin Xu “ A novel channel estimation method based on Kalman filter compressed sensing for time-varying OFDM system” IEEE Conference Publications,pp. Pages: 1 – 5,year:2014
[7]E. Başar, Ü. Aygölü, E. Panayırcı, and H. V. Poor, “Orthogonal frequency division multiplexing with index modulation,” IEEE Trans. Signal Process., vol. 61, no. 22, pp. 5536–5549, Nov. 2013
[8]R. Abu-alhiga and H. Haas, “Subcarrier-index modulation OFDM,” in Proc. IEEE Int. Sym. Personal, Indoor,Mobile Radio Commun., Tokyo Japan, Sep. 2009, pp. 177–181.
[9]Yue Xiao, Shunshun Wang, Lilin Dan, Xia Lei, Ping Yang, and Wei Xiang “OFDM With Interleaved Subcarrier-Index Modulation” IEEE Communictions Letters, vol.18, no. 8, pp.1447-1450 AUGUST 2014
[10]Shunshun Wang; Bin Xu; Huirong Bai; Yue Xiao; Lilin Dan“MIMO-OFDM with interleaved subcarrier-index modulation” IET Conference Publications,pp. 35 - 37, year: 2014
[11]D. Tsonev, S. Sinanovic, and H. Haas, “Enhanced subcarrier index modulation (SIM) OFDM,” in Proc. IEEE GLOBECOM Workshops, , pp. 728–732,yeae:2010
[12]R. Fan, Y. Yu, and Y. Guan, “Generalization of orthogonal frequency division multiplexing with index modulation,” IEEE Trans. Wireless Commun., no. 99, pp. 1–10, May 2015.
[13]Miaowen Wen; Xiang Cheng; Liuqing Yang. “ Optimizing the Energy Efficiency of OFDM with Index Modulation?,IEEE Conference Publications,pp.31-35,year:2014
[14]C. Berrou, A. Glavieux, and P. Thitimajshima, “Near Shannon limit error-correcting and decoding: turbo codes,” in Proc. IEEE Int. Conf. Commun., vol.2, May, 1993, pp.1064-1070.
[15]H. Lou and C. Xiao, “Soft decision feedback turbo equalization for multilevel modulations,” IEEE Trans. Signal Process, vol. 59, no. 1, pp. 186– 19 5, Jan. 2011.
[16]Koetter, R.; Singer, A.C.; Tüchler, M., “Turbo equalization”, Signal Processing Magazine, VOL. 21, IEEE, Jan. 2004
[17]Alireza Movahedian and Michael McGuire “Estimation of Fast-Fading Channels for Turbo Receivers With High-Order Modulation, Feb 2013”
[18]Huang Lou, Chengshan Xiao, “Soft-Decision Feedback Turbo Equalization for Multilevel Modulations,” IEEE Transactions On Signal Processing, Vol. 59, No. 1, pp.186-195, Jan. 2011
[19]M. Huang, X. Chen, L. Xiao, S. Zhou and J. Wang “Kalman-filter-based channel estimation for orthogonal frequency-division multiplexing systems in time-varying channels,” IEEE Trans. Commun., vol. 1, Is. 4, August 2007.
[20]Muralidhar, K.; Sreedhar, D. "Generalized vector state-scalar observation Kalman channel estimator for doubly-selective OFDM systems", Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, On pp. 4928 - 4932
[21]Kyeongyeon Kim, Kalantarova, N., Kozat, S.S., Singer, A.C., “Linear MMSE-Optimal Turbo Equalization Using Context Trees”, IEEE Transactions On Signal Processing, Vol. 61, No. 12, pp. 3041-3055, Jun. 15, 2013
[22]M. Tüchler, A. C. Singer, and R. Koetter, “Minimum mean square error equalization using a priori information,” IEEE Trans. Signal Process., vol. 50, no. 3, pp. 673–683, Mar. 2002.
[23]Y. S. Cho, J. Kim, W. Y. Yang and C.-G. Kang, MIMO-OFDM Wireless Communications with MATLAB, John Wiley & Sons (Asia), 2010
[24]Eric Pierre Simon and Mohammad Ali Khalighi, “Iterative Soft-Kalman Channel Estimation for Fast Time-Varying MIMO-OFDM Channels,” IEEE Trans. Commun., vol. 2, no. 6, Dec. 2013.
[25]Xin Li and Wong T.F. “Turbo equalization with nonlinear Kalman filtering for time-varying frequency-selective fading channels” Wireless Communications, IEEE Transactions pp. 691 - 700, on year 2007
[26]Die Hu, Xiaodong Wang, Lianghua He, " A New Sparse Channel Estimation and Tracking Method for Time-Varying OFDM Systems," IEEE Trans. Commun., vol. 62, pp. 4648-4653, 2013.
[27]J. Andrews, S. Buzzi, W. Choi, S. Hanly, A. Lozano, A. Soong, and J.Zhang, “What will 5G be?,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, Jun. 2014.
[28]S. M. Alamouti, "A simple transmit diversity technique for wireless communications," IEEE J. Select. Areas Commun., vol. 16, no. 8, pp. 1451-1458, 1998.
[29]C. Douillard et al.,“Iterative correction of intersymbol interference: Turbo-equalization”, ETT, Vol.6, No. 5, pp. 507–511, Sep.-Oct. 1995.
[30]S. Talakoub, L. Sabeti, B. Shahrrava, and M. Ahmadi, “An Improved Max-Log-MAP Algorithm for Turbo Decoding and Turbo Equalization,” IEEE Trans. VOL. 56, NO. 3, JUNE 2007


QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊