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A DFT-based Low Complexity LMMSE Channel Estimation Technique for OFDM Systems

Patra Jyoti P., Pradhan Bibhuti Bhusan, Singh Poonam

Journal of Telecommunications and Information Technology

2022

nr 1

72--78

The linear minimum mean square error (LMMSE) channel estimation technique is often employed in orthogonal frequency division multiplexing (OFDM) systems because of its optimal performance in the mean square error (MSE) performance. However, the LMMSE method requires cubic complexity of order O(N 3 p ), where Np is the number of pilot subcarriers. To reduce the computational complexity, a discrete Fourier transform (DFT) based LMMSE method is proposed in this paper for OFDM systems in the frequency selective channel. To validate the proposed method, the closed form mean square error (MSE) expression is also derived. Finally, a computer simulation is carried out to compare the performance of the proposed LMMSE method with the classical LS and LMMSE methods in terms of bit error rate (BER) and computational complexity. Results of the simulation show that the proposed LMMSE method achieves exactly the same performance as the conventional LMMSE method, with much lower computational complexity.

Image Despeckling Based on LMMSE Wavelet Shrinkage

Cui Y., Zhang T., Yu W.

Przegląd Elektrotechniczny

2012

R. 88, nr 7b

269--272

A low complexity method for suppressing speckle in synthetic aperture radar (SAR) images is proposed. This method doesn’t require the logarithmic transform and is an extension of the linear minimum mean square error (LMMSE) filter to the image wavelet representation. A spatially adaptive shrinkage function is obtained and each modified coefficient is decided separately. Simulation results for the simulated SAR images demonstrate the proposed method outperforms some representative SAR despeckling methods.

Zaproponowano metodę poprawy jakości obrazu w radarach typu SAR. Bazuje ona na liniowym minimum średniej kwadratu błędu LMMSE filtru. Wykorzystano adaptacyjną funkcję zbieżną w przestrzeni i wszystkie współczynniki modyfikowane są niezależnie.