Robust Channel Estimation in LTE Uplink Transmission

碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 103 === Wireless communication will play an important role in the evolution of communication in the future, especially basing on WiMAX (IEEE) and LTE (3GPP) to develop individually. The major difference between the two systems is that LTE using single carrier frequ...

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Bibliographic Details
Main Authors: Yin, Wei-Cheng, 尹唯丞
Other Authors: Lin, David W.
Format: Others
Language:en_US
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/59183133871554119116
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Summary:碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 103 === Wireless communication will play an important role in the evolution of communication in the future, especially basing on WiMAX (IEEE) and LTE (3GPP) to develop individually. The major difference between the two systems is that LTE using single carrier frequency division multiple access(SC-FDMA)technique in uplink transmission, while WiMAX using orthogonal frequency division multiple access(OFDMA).The advantage of using SC-FDMA is to reduce the peak-to-average power ratio (PAPR) which saves the power consumption of user equipment (UEs). This thesis will introduce the subjects of channel estimation problems, algorithms, analysis of multi-path transmission in SC-FDMA. In channel estimation, we first use the least square estimator, then use two different methods to estimate the channel frequency response. The first method is to estimate the correlation matrix of channel by the frequency response of reference signals estimated by least square estimator. Then smooth the channel response of reference signals by linear minimum-mean square error (LMMSE) matrix derived by correlation matrix. The second method is using Gaussian distribution window (GWD) to make reference signal smoother. After estimating frequency response of reference signals, we use linear interpolation to get frequency response of data subcarriers. In simulation, we test and verify the simulate model which we proposed in additive white Gaussian noise(AWGN) channel. Then we simulate in multi-path channel. We find that LMMSE has similar performance as Gaussian distribution window in low SNR, but Gaussian distribution window has lower complexity than LMMSE.