• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.49-59
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• 2005

An adaptive hybrid beamformer is proposed to improve the reception performance of the advanced television system committee (ATSC) digital television (DTV) in a mobile environment. Dynamic multipaths and Doppler shifts severely degrade the reception performance of the ATSC DTV receiver. Accordingly, a hybrid beamformer, called a Capon and least mean square (CLMS) beamformer, is presented that uses direction of arrival (DOA) information and the least mean square (LMS) beamforming algorithm. The proposed CLMS algerian efficiently removes dynamic multipaths and compensates for the phase distortion caused by Doppler shifts in mobile receivers. After the CLMS beamformer is operated, the subsequent use of an equalizer removes any residual multipath effects, thereby significantly improving the performance of DTV receivers. The performances of the proposed CLMS, Capon, and LMS beamformersare compared based on computer simulations. In addition, the overall performance of the CLMS beamformer followed by an equalizer is also considered.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.19-25
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• 2004

In this paper, we present a trellis-based blind channel estimation and equalization technique coupling two kinds of adaptive Viterbi algorithms. First, the initial blind channel estimation is accomplished by incorporating the list parallel Viterbi algorithm with the least mean square (LMS) updating approach. In this operation, multiple trellis mappings are preserved simultaneously and ranked in terms of path metrics. Equivalently, multiple channel estimates are maintained and updated once a single symbol is received. Second, the best channel estimate from the above operation will be adopted to set up the whole trellis. The conventional adaptive Viterbi algorithm is then applied to detect the signal and further update the channel estimate alternately. A small delay is introduced for the symbol detection and the decision feedback to smooth the noise impact. An automatic switch between the above two operations is also proposed by exploiting the evolution of path metrics and the linear constraint inherent in the trellis mapping. Simulation has shown an overall excellent performance of the proposed scheme in terms of mean square error (MSE) for channel estimation, robustness to the initial channel guess, computational complexity, and channel equalization.

• 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 the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.1-8
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• 2006

In this paper, we propose carrier phase synchronization algorithm which are base on turbo coded system for DVB-RCS. There have been two categories of phase estimator, single estimator outside turbo code decoder and multiple estimators inside turbo code decoder. In single estimator, we use the estimation algorithm that ML(Maximum Likelihood) and LMS(Least Mean Square), also three different soft decision methods are proposed. Multiple estimator apply PSP(Per Survivor Processing) algorithm additionally. We compared performance between single estimator and Multiple estimator in AWGN channel. We presented the two methods of PSP algorithm for performance elevation. First is the Bi-directional channel estimation and second is binding method.

• Journal of Integrative Natural Science
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• v.15 no.3
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.288-295
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• 2013

In this paper, we compare the existing channel estimation technique for 4S (Ship to Ship, Ship to Shore) maritime communications under AWGN channel model, Rician fading channel model, and Rayleigh fading channel model respectively. In general, the received signal is corrupted by multipath and ISI (Inter Symbol Interference). The estimation of a time-varying multipath fading channel is a difficult task for the receiver. Its performance can be improved if an appropriate channel estimation filter is used. The simulation is performed in MATLAB. In this simulation, we use the popular estimation algorithms, LMS (Least Mean Square) and RLS (Recursive Least-Squares) are compared with respect to AWGN, Rician and Rayleigh channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1239-1247
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• 2015

In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) system, the computational complexity of downlink channel estimation is proportional to the number of antennas at a base station. Therefore, effective channel estimation techniques may have to be studied. In this paper, novel channel estimation algorithms using adaptive techniques such as Kalman and least mean square (LMS) filters are proposed in a channel model with temporal and spatial correlation.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.43-46
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• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.305-344
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• 2008

This paper presents the active control of flexible beam vibration. The beam was excited by a steady-state point force by mini shaker and the control was performed by mini shaker. To perform active control, least-mean-square (LMS) algorithm was used because it can easily obtain the complex transfer function in real-time. So an adaptive controller based on Filtered-X LMS algorithm was used and the controller was defined by minimizing the square of the response at a location of error sensor. In order to fine out performance tendency, input amplitude was changed in several cases and active vibration control was performed.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.