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Title: Low-complexity iterative channel estimation and detection techniques for OFDM systems
Other Titles: OFDM xi tong zhong de di fu za du die dai xin dao gu ji yu jian ce ji shu
OFDM 系統中的低複雜度迭代信道估計與檢測技術
Authors: Geng, Nian ( 耿念)
Department: Department of Electronic Engineering
Degree: Doctor of Philosophy
Issue Date: 2011
Publisher: City University of Hong Kong
Subjects: Orthogonal frequency division multiplexing.
Notes: CityU Call Number: TK5103.484 .G46 2011
xviii, 118 leaves : ill. 30 cm.
Thesis (Ph.D.)--City University of Hong Kong, 2011.
Includes bibliographical references (leaves 109-116)
Type: thesis
Abstract: The concept of "iterative" (or Turbo) has been widely used in a great variety of modern communication systems. An iterative receiver can achieve impressive performance gain by refining the estimates during the iteration between the elementary signal estimator (ESE) module and the decoder (DEC) module, two main modules of the typical iterative receiver. Recently, iterative joint channel estimation and signal detection involving message-passing among the ESE, DEC and the channel estimator (CE) have been investigated and significant performance improvement has been reported. In this thesis we focus on the design of channel estimation and symbol detection techniques for the iterative orthogonal frequency division multiplexing (OFDM) systems. Traditionally, channel estimation is commonly realized through the use of pilot signals in the OFDM systems. The accuracy of channel estimation can be improved if some channel statistical information, such as the channel power delay profile (PDP), is available at the receiver side. Further improvement is possible with the assistance of DEC feedbacks in the iterative systems. The linear-minimum-mean-square-error (LMMSE) estimation has been extensively studied for combining information from different sources, namely, the pilot signals, the PDP, and the DEC feedback. Significant performance improvement has been reported but with high computational complexity O(N3) per iteration with N being the number of OFDM subcarriers. In this thesis, we propose a novel dual-diagonal LMMSE (DD-LMMSE) channel estimation algorithm for the purpose of information combing. Two diagonal LMMSE (D-LMMSE) operations are involved, one in the frequency domain and the other in the time domain, hence the name. Fast Fourier transform (FFT) is used to convert and combine information between the time and frequency domains with the complexity O(NlogN). Simulation results show that, the DD-LMMSE approach performs closely to the LMMSE one and requires much lower complexity than the latter. A close form of the mean square error (MSE) analysis for the DD-LMMSE estimation algorithm is derived to predict the estimation performance. We show that this asymptotic bound provides a fast and good approximation for the MSE of DD-LMMSE estimator. Based on the derived asymptotic MSE bound, we further develop an evolution technique to predict the overall system performance. Different from all existing evolution analysis with full channel state information (CSI), the evolution technique proposed in this thesis handles the situation that CSI is not available at the receiver side. Similar to the signal to noise ratio (SNR)-variance evolution, the proposed evolution technique is also semi-analytic in the sense that the transfer characteristic of the MSE for the CE module can be calculated using the analytic way. Numerical results demonstrate that the proposed evolution technique can provide a reasonably accurate performance prediction by tracking only a few numbers of parameters. To avoid the transmission rate loss due to comb-type pilot placement, superimposed pilot is widely used for channel estimation in the communication systems, where the pilot layer is directly added to the data layer. The low-complexity DD-LMMSE algorithm is extended to the OFDM systems with superimposed pilot and the asymptotic MSE close form is derived to predict the accuracy of the DD-LMMSE channel estimators. Noticing that different energy allocation between the pilot layer and the data layer can affect the system performance, Monte Carlo simulation is widely used to obtain the optimal value. But it is quite costly and not universal for other system settings. Based on the asymptotic MSE bound and the system evolution analysis, we predict the system performance with different energy allocation so as to obtain the optimal value. Moreover, the diagonal channel estimation concept can be applied in the two dimensional (2D) channel estimation, which is applicable for the time-varying frequency-selective Rayleigh fading channels. For the 2D channel estimation, the neighboring OFDM blocks are correlated with the correlation being characterized by the Doppler spectrum. Messages, such as PDP, the channel observation, the pilot, the feedback from DEC, and the Doppler spectrum, are combined to improve the channel estimation accuracy. 2D Wiener (2D-W) filter is the optimal message combing strategy with high computational complexity. Following the concept of diagonal estimation, we propose a low-complexity adaptive 2D-diagonal (2D-D) LMMSE channel estimation algorithm. The simulation results are provided to show the efficiency of this method. Furthermore, we investigate the iterative system performance from an information-theoretic point of view. Recently, an interesting relationship between the channel input output mutual information and the minimum-mean-square-error (MMSE) (referred to as the MMSE-I relationship) in Gaussian channels is well developed. Some extension work of the area theorem for more general linear channels (including inter-symbol interference (ISI) and multiple input multiple output (MIMO) channels) using the transfer functions of MSE versus SNR has been done. In this thesis we are interested in the achievable rate of the considering system with channel estimation. The proper precoder is designed to make the output of ESE satisfy the constraints in the area theorem, so as to obtain the ESE transfer function of MSE versus SNR. Based on the area theorem and the transfer function, the corresponding system achievable rate can be asymptotically analyzed. In summary, this thesis presents a comprehensive study on the channel estimation and symbol detection techniques in the iterative OFDM systems. The simulation results are provided to show the efficiency of the proposed estimation algorithm. The analytical discussion can help us to analyze the iterative system performance and convince the simulation results.
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