• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.163-168
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• 2011

In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.229-232
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• 2000

Orthogonal frequency division multiplexing(OFDM) has meanwhile become part of several telecommunicati ons standards, such as satellite and terrestrial digital audio broadcasting(DAB), digital terrestrial TV broad casting(DVB), asymmetric digital subscriber line(ADSL) for high-bit-rate digital subscriber services on twisted-pair channels, and broadband indoor wireless systems. In his paper, we show that OFDM signals contain sufficient structure to accomplish blind channel estimation using second order statistics only. This method doesn't require redundancy as cp in transmitter. And the result is compared with PSAM channel estimation as least square, linear minimum mean square, singular value decomposition.

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

• ETRI Journal
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• v.28 no.5
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• pp.688-691
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• 2006

This letter addresses the superimposed pilot aided multiuser channel estimation for the uplinks of multi-input multi-output orthogonal frequency-division multiplexing systems. To mitigate the embedded-data effects on the performance of channel estimation, a novel combining algorithm is proposed. Optimal pilot symbols are developed with respect to the least square channel estimate's mean square error. The averaged sum-capacity lower bound is derived and simulated. Simulation results show that on a low signal-to-noise ratio regime, our proposed scheme achieves better performance and higher capacity than the conventional pilot aided approach.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.135-141
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• 2014

The inherent feature of the highly efficient spectrum usage has made Orthogonal Frequency Division Multiplexing (OFDM) preferable for Communication Standards. This study evaluated the performance of a Least Square (LS) estimator for a comb-type pilot insertion scheme over a fast fading Rayleigh channel. A High Peak-to-Average Power Ratio (PAPR) is one of the major downsides of the OFDM. The effects of an increase in the number of subcarriers on PAPR and the performance of the LS Estimator were studied. Increasing the number of subcarriers while keeping the pilots overhead constant resulted in improved performance of the LS estimator but the PAPR increased with increasing number of subcarriers. Therefore some trade-off between the number of subcarriers and the performance of the OFDM system is needed. The Mean Square Error (MSE) expression was also derived for the LS estimator in the case of a comb-type pilot arrangement. The MSE expression clearly explains the effects of the number of subcarriers on the performance of the LS estimator.

• Journal of Environmental Science International
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• v.6 no.5
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• pp.541-550
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• 1997

A least-square regression analysis is applied for the estimation of velocity streamfunction field based on discretely sampled current meter data. The coefficients of a streamfuunction that is expanded in terms of trigonometric basis function are obtained by enforcing the horizontal non-divergence of two-dimensional flow field. This method avoids Interpolation and gives a root-mean-square (rms) residual of fit which Includes the divergent part and noisiness of oceanic data. The Implementation of the method Is done by employing a boundary-fitted, curvilinear orthogonal coordinate which facilitates the specification of boundary conditions. An application is successfully made to the Texas-Louisiana shelf using the 32 months current meter data (31 moorings) observed as a part of the Texas-Louisiana Shelf and Transport Processes Study (LATEX). The rms residual of the fitting is relatively small for the shelf, which indicates the field Is Ivell represented by the streamnfunction.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1455-1461
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• 2012

MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.32-38
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• 2000

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the adaptation speed and the convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by the gradient of error square. The proposed algorithm is performed in the Walsh-Hadamard domain in real-valued orthogonal transform because of fast convergence. The simulation results using the new algorithm for noise canceller system is described. They are compared to the results obtained by other algorithms. It is shown that the proposed algorithm produces good results compared with conventional algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.93-98
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• 2009

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.