Parallel Channel Estimator and Equalizer for Mobile OFDM Systems

Guan, Yongfeng; Xu, Tao; Leuken, René van; Qian, Manyi

doi:10.1007/s00034-013-9664-6

Cited by 5 publications

(8 citation statements)

References 20 publications

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“…1. The  value at the lowest point of the curve (17) is very close to the ones of the curves (12) and (16), which indicates that it is feasible to replace (16) with (17) to determine the proper  value. It is discovered in our simulation that, the value of the second item in (16) will reduce rapidly and dominate the curve as  slowly increases from 0.…”

Section: A Time-invariant Channel Simulationmentioning

confidence: 56%

“…where, h li is the ideal channel impulse response on the lth OFDM symbol. Substitute (4) and (11) into (12)…”

Section: Methods To Overcome the Nearly Singular Problem Of Matrimentioning

confidence: 99%

“…Such a 'perfect" channel frequency response is taken as the best boundary curve, and is compared with the method proposed in this study. The exponential decay channel model is shown, as follows: by the time average with these 100 channels, and the estimated channel impulse response will be substituted into (12) to estimate E l with time-averaging. Fig.…”

Section: A Time-invariant Channel Simulationmentioning

confidence: 99%

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The Research of Frequency Domain Least Squares Channel Estimation in OFDM Systems

Kao¹,

Wu²

2016

jcm

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-This paper focuses on comb-type or scattered pilot arrangement in OFDM systems with a frequency guard band under the time-variant channel. If the maximum channel delay is large, there is a nearly singular matrix problem when a receiver adopts the Frequency Domain LS (FDLS) method to estimate the data subcarrier channel frequency response. This problem renders FDLS channel estimation more sensitive to noise. M. Yu and P. Sadeghi proposed a simply method to avoid the nearly singular matrix problem; however, they did not describe in detail how to select the important regularization parameter. Therefore, this study will discuss and analyze the regularization parameter, and propose a flow to select a suitable regularization parameter. From BER simulations, the proposed flow shows good performance.

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Section: A Time-invariant Channel Simulationmentioning

confidence: 56%

“…where, h li is the ideal channel impulse response on the lth OFDM symbol. Substitute (4) and (11) into (12)…”

Section: Methods To Overcome the Nearly Singular Problem Of Matrimentioning

confidence: 99%

Section: A Time-invariant Channel Simulationmentioning

confidence: 99%

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The Research of Frequency Domain Least Squares Channel Estimation in OFDM Systems

Kao¹,

Wu²

2016

jcm

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“…For example, He et al [13] proposed from compressed sensing theory optimal pilot pattern designs for a sparse channel estimation in OFDM systems. However, extra bandwidth is required to accommodate periodic training symbols, and thus is reducing the spectrum efficiency [8,12,21]. The blind method utilizes the second-order or higher statistics of received signals to perform channel estimation [1,3,11].…”

Section: Introductionmentioning

confidence: 99%

Fast Convergence on Blind and Semi-Blind Channel Estimation for MIMO–OFDM Systems

Zhang

Kuo

2014

Circuits Syst Signal Process

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In this paper, blind and semi-blind subspace channel estimations with fast convergence rate are proposed for multiple-input multiple-output orthogonal frequency division multiplexing (OFDM) systems in the presence of virtual carriers. The subspace method has a main drawback of slow convergence rate when deriving the noise subspaces from the second-order statistics of received signals. This phenomenon is especially evident when the size of received signals is large. Inspired by this fact, we present a block matrix scheme (BMS) to generate a group of sub-vectors from each OFDM symbol when virtual carriers are used. The number of equivalent signals is increased and therefore, the convergence rate of channel estimation is enhanced. The semi-blind method is also investigated by incorporating subspace technology with least square scheme. The identifiability of the BMS-based channel estimation is analyzed to derive the applicable range of the BMS size. The computational complexity of the proposed channel estimation is calculated at the end. Computer simulations show that the proposed blind and semi-blind methods converge very well in channel estimation and equalization.

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“…However, the current study synchronization algorithm based on cyclic prefix, requirements of cyclic prefix length cannot be greater than OFDM the 1/4 of the symbol timing synchronization , otherwise, the system timing synchronization error will be significant. Aiming at this problem, this paper again by changing the training sequence structure, and puts forward the improved synchronization algorith m [3]. Solve the problem in improving system performance basis.…”

mentioning

confidence: 99%

OFDM Synchronization Improved Algorithm Based on Cyclic Prefix

Zhang¹,

Chen²,

Zhang³

2015

Proceedings of the International Conference on Computer Information Systems and Industrial Applications

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The current study synchronization algorithm based on cyclic prefix, requirements of cyclic prefix length cannot be greater than OFDM the 1/4 of the symbol timing synchronization, otherwise, the system timing synchronization error will be significant. Aiming at this problem, this paper again by changing the training sequence structure, puts forward the improved synchronization algorithm, consider the impact of the correlation coefficient on timing synchronous, by an estimate of the correlation coefficient, reducing the factors that affect the performance of the ML timing synchronization algorithm; in the frequency offset estimation, using the set of related ideas to eliminate the drawbacks of ML algorithm performance in multipath channel low, through the simulation verified the effectiveness of the algorithm.

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Parallel Channel Estimator and Equalizer for Mobile OFDM Systems

Cited by 5 publications

References 20 publications

The Research of Frequency Domain Least Squares Channel Estimation in OFDM Systems

The Research of Frequency Domain Least Squares Channel Estimation in OFDM Systems

Fast Convergence on Blind and Semi-Blind Channel Estimation for MIMO–OFDM Systems

OFDM Synchronization Improved Algorithm Based on Cyclic Prefix

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