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Research On Time-Varying Channel Estimation In OFDM Systems

Posted on:2014-01-26Degree:DoctorType:Dissertation
Country:ChinaCandidate:Q L GuoFull Text:PDF
GTID:1228330401463136Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
With the development of diverse communication services, data and multimedia services have surpassed the traditional voice counterpart to be the major carrier of wireless communication. The huge network data and video to deliver induced by the information explosion pose great challenge on the high-data-rate reliable communication. However, the symbol period reduces with the increase of data rate for single-carrier modulation, causing server inter-symbol interference. In orthogonal frequency-division multiplexing (OFDM) systems, the entire channel is divided into a number of parallel independent sub-channels to increase the rate and channel capacity. Meanwhile, the OFDM symbol period is much longer than the multipath spread, which effectively avoid the inter-symbol interference. Therefore, OFDM with the merits of high data rate, inter-symbol interference robustness, band allocation flexibility, easy integrate with MIMO, is widely admitted by both academics and industries. Besides, OFDM has been adopted by several communication standards as one of the key physical-layer technologies.The high development of the high-speed railway puts forward more demand for the high-data-rate communications, which concern both the passengers’communication services and the security issues such as the train control and monitor. Nevertheless, in highly mobile environments, OFDM systems face many problems such as the oscillators asynchronous of the transmitting and receiving terminals, the boost of the channel gains to estimate, the destruction of the orthogonality of subcarriers. In addition, the performance of the traditional channel estimation technologies degrades significantly, making the unsatisfactory system performance for high-data-rate demands. Thus, from both the academical and practical perspectives, the research on the time-varying channel estimation in OFDM systems is crucial.The contents and the major contributions of this paper are listed as follows.To reduce the large model error of existing basis expiation models (BEM), this paper derivates the formula of the minimum model error in least square estimation with the BEMs to find that the model error is related with both the model type and the characteristic of the object. Recently the researchers all over the world focus on the optimal model for better fitting effect, however, existing achievements prove that no uniform perfect model exists for any channel gains. Based on existing model, this paper proposes the channel estimation iterative algorithm with the channel decomposition to reduce the modeling error of BEMs. This algorithm adopts the idea of "divide and conquer" to decompose the channel gains to optimize the channel gains to estimate in iterations by updating the optimal slopes or the end slopes. Then, the non-linear parts are estimated in BEMs with less modeling error. At last, the results from both BEM and linear model are combined to get the final channel gains. A lot of simulations in the COST207rural channel model demonstrate that the performance can be promoted by2to4iterations, and the proposed algorithm outperforms the traditional linear model and generalized complex-exponential BEM in terms of estimation accuracy. Moreover, the superiority is more obvious with increased mobility.To eliminate the sub-carriers interference for the channel estimation, the simplified formula of the interference power is derived first, then the upper and lower bounds of the interference power are gained to get insight into the relations with the normalized Doppler frequency shift. Simulations with three different channel models validate the upper and low bounds of sub-carrier interference power and conclude that the power is roughly proportional to the square of normalized Doppler frequency shift with different coefficients depending on the Doppler power profile. Then, this paper proposed the joint channel estimation algorithm with dual-ICI cancellation, which employs both BEM and linear model. Pre-ICI cancellation makes the estimation in BEM more sensitive to the variation of the channel gains, while the result of BEM is fed back to linear model for post-ICI cancellation to maintain the performance of linear model in highly mobile environments. Dual-ICI cancellation makes the proposed algorithm better in performance than the conventional BEM and linear model with high or low mobility.To deal with the random appearance and disappearance of the tap in sparse time-varying channels, this paper proposes a novel pilot cluster pattern to avoid the undesirable spectrum efficiency of traditional BEM. On basis of this pattern, the time-varying channel estimation with main taps track is proposed. First, the interpolation in temporal domain makes many virtual pilots, and the multipath power is derived with both pilots and virtual pilots after the Fourier transformation. The main taps are detected in terms of tap power according to the accurate multipath delay profile. Then the marked main taps are estimated in BEMs, meanwhile, the other taps are set to be null to eliminate the noise affluence. The temporal gains are transformed into the channel frequency matrix. To alleviate the degradation of the performance of data detection due to sub-carrier interference, the QR decomposition is induced to detect the transmitted data from down to top for lower bit error rate. Simulations in COST207traditional urban model with six taps demonstrate that the proposed algorithm has the a little higher spectrum efficiency in sparse time-varying channel than the traditional least-square method in frequency domain, linear model and hybrid pilots’methods, in addition, obviously better than the traditional BEM algorithms. The proposed algorithm outperforms the traditional least-square method and linear model in high signal-to-noise condition with respect to mean square error and bit error rate.
Keywords/Search Tags:time-varying channel estimation, signal detection, orthogonal, frequency, division, multiplexing (OFDM), basis expansion model (BEM), linear model
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