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Channel Estimation for Fast Fading MIMO OFDM Systems in High Mobility Communications

Author: ZhouXiaoPing
Tutor: FangYong
School: Shanghai University
Course: Communication and Information System
Keywords: Compressed sensing Channel estimation Fast fading Sparse channel Distributed
CLC: TN919.3
Type: PhD thesis
Year: 2011
Downloads: 473
Quote: 1
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Abstract


Papers fast fading channel estimation method for high-speed mobile MIMO-OFDM system. First, we discuss the basic theory and channel estimation methods commonly used method. Second, wireless communication fading channel characteristics, and high-speed mobile fast fading channel's characteristics carried out the analysis, the high-speed mobile environment, fast fading channel will be in the time, frequency and space to form selective fading, therefore, needs from a multi- Pul extended delay spread and angular spread of the three angles to consider the radio channel. Further study shows that the different delays of the multipath signals would make the OFDM system to produce different degrees of inter-code interference (Inter-symbol interference, the ISI); speed mobile OFDM systems caused by the Doppler frequency shift, will produce the inter-carrier interference (Inter -carrier Interference, ICI), the orthogonality between the sub-carriers have been destroyed, the interference will be generated between the different sub-carriers; form a mutual interference between the antennas in a MIMO system, each of the antenna in the spatial domain. Again, this paper presents a compression perception theory definition, nature and algorithms, compressed sensing theory including signal sparse transform coding measurement reconstruction algorithm and distributed compression perception. Analyzes the the estimated feasibility analysis based on compressed sensing channel. Finally, in-depth study of based on compressed sensing OFDM system fast fading channel estimation algorithm based on compressed sensing MIMO-OFDM system is fast fading channel estimation algorithm based on compressed sensing distributed MIMO-OFDM system is fast fading channel estimation algorithm to obtain the corresponding research results. This thesis is fast fading channel estimation method applied research on high-speed mobile MIMO-OFDM system has great practical significance. I completed work and innovation: analysis of existing sparse channel model derivation does not cause the power-aliasing and leakage, low complexity sparse stronger and calculated based on the parameterized fast fading channel model. For OFDM systems, a the delay Doppler sparse channel model for MIMO-OFDM systems, an angle delay Doppler sparse MIMO-OFDM channel model. Through a random turn-frequency the perception matrix channel measurement, reconstructed with high probability for fast fading channels, improve system spectrum efficiency. Derivation of the frequency groups based on OFDM system sparse compressed sensing channel estimation algorithm to. With the correlation of the time domain so that the energy concentrated in only a few sample points. The use of a frequency domain correlation, energy concentrated in only a few Doppler frequency shift point. Therefore, while taking advantage of the time domain and the frequency domain correlation is lower than existing based on time-frequency two-dimensional complexity of the algorithm, the system performance is higher, to reduce the estimated delay. Is derived based on the MIMO-OFDM system empty frequency group sparse compression perceptual channel estimated algorithm, analysis between different empty within the antenna channel sparse coefficient and the same empty within the antenna letter Road sparse coefficient related to sex, in addition to the use of time-domain and frequency the correlation of the domain, and also makes use of the correlation between this airspace the sparse coefficient its neighborhood of the antenna channel sparse coefficient. The use of the airspace, the time domain and frequency domain correlation to improve system performance. A fast fading environment group sparse adaptive channel estimation methods, and take full advantage of the use of multi-antenna and group variable OFDM symbol potentially overcome the sparsity of the channel based on compressed sensing principle channel estimation methods need to know in advance the sparsity of the channel to the reconstruction of the lack of channel parameters, in the case of fast time-varying environment OFDM system channel sparsity not know, adaptive to estimate the channel parameters. Through simulation, test estimation algorithm mentioned change in a fast, high Doppler shift of the effectiveness and superiority of environment. Drawbacks of traditional fast fading distributed MIMO-OFDM system pilot excessive lead to low data transmission efficiency, to estimate the need for a received signal of each transmission antenna, respectively, the strong interference between the antennas can not be avoided, consider distributed MIMO-OFDM aware data space fast fading channel delay and Doppler shift correlation and joint a sparse model proposed joint estimation algorithm based on distributed compressed sensing theory the fast fading sparse channel. The simulation results show that the proposed estimation algorithm has higher spectrum utilization and estimated performance.

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