• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.8
• /
• pp.25-32
• /
• 2012

In this paper, we propose a method for improving the performance of low complexity LS channel estimation for OFDM in fast time varying channels. The CE-BEM channel model used for the low complexity LS channel estimation has a problem on its own and deteriorates channel estimation performance. In this paper, we first use time domain windowing in order to remove the effect of ICI caused by data symbols. Then samples are taken from the results of the LS channel estimation and the effects of the windowing are removed from them. For resolving the defect of CE-BEM, the channel responses are recovered by interpolating the resultant samples with DPSS employed as basis functions the characteristics of which is well matched to the time variation of the channel. Computer simulations show that the proposed channel estimation method gives rise to performance improvement over conventional methods especially when channel variation is very fast and confirm that not only which type of functions is selected for the basis but how many functions are used for the basis is another key factor to performance improvement.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.48 no.11
• /
• pp.17-21
• /
• 2011

In this paper, we propose a pilot symbol assisted low complexity LS channel estimation method for OFDM in fast time varying channels. The proposed method shows low complexity characteristics in terms of memory space and processing time compared with conventional BEM channel model LS estimation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2400-2413
• /
• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• Journal of electromagnetic engineering and science
• /
• v.7 no.4
• /
• pp.195-200
• /
• 2007

Doubly-selective channel estimator for orthogonal frequency division multiplexing(OFDM) systems is proposed in this paper. Based on the generalized complex exponential basis expansion model(GCE-BEM), we describe the time-variant channel with time-invariant coefficients over multiple OFDM blocks. The time variation of the channel destroys the orthogonality between subcarriers, and the resulting channel matrix in the frequency domain is no longer diagonal, but the main interference comes from the near subcarriers. Based on this, we propose a channel estimator with low pilot ratio. We first develop a least-square(LS) estimator under the assumption that only the maximum Doppler frequency and the channel order are known at the receiver, and then verify that the correlation matrix of inter-channel interference(ICI) is a scaled identity matrix based on which we derive an optimal pilot insertion scheme for the LS estimator in the sense of minimum mean square error. The proposed estimator has the advantages of low pilot ratio and robustness against inter-carrier interference.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.11
• /
• pp.5394-5409
• /
• 2019

The paper investigates a novel detector receiver with Kalman channel information estimator and iterative channel response equalization for MIMO (multi-input multi-output) OFDM (orthogonal frequency division multiplexing) communication systems in fast multipath fading environments. The performances of the existing linear equalizers (LE) are not good enough over most fast fading multipath channels. The existing adaptive equalizer with decision feedback structure (ADFE) can improve the performance of LE. But error-propagation effect seriously degrades the system performance of the ADFE, especially when operated in fast multipath fading environments. By considering the Kalman channel impulse response estimation for the fast fading multipath channels based on CE-BEM (complex exponential basis expansion) model, the paper proposes the iterative receiver with soft decision feedback equalization (SDFE) structure in the fast multipath fading environments. The proposed SDFE detector receiver combats the error-propagation effect for fast multipath fading channels and outperform the existing LE and ADFE. We demonstrate several simulations to confirm the ability of the proposed iterative receiver over the existing receivers.