• Journal of Communications and Networks
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• v.1 no.2
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• pp.118-133
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• 1999

In this paper we compare linear and non-linear inter-ference cancellation for systems employing code division multi-ple access (CDMA) techniques. Specifically, we examine linear and non-linear parallel interference cancellation(also called multi-stage cancellation) in relationship to other multiuser detection al-gorithms. We show the explicit relationship between parallel inter-ference cancellation and the decorrelator (or direct matrix inver-sion). This comparison gives insight into the performance of paral-lel interference cancellation (PIC) and leads to vetter approaches. We also show that non-linear PIC approaches with explicit chan-nel setimation can provide performance improvement over linear PIC, especially when using soft non-linear symbol estimates. The application of interference cancellation to non-linear modulation techniques is also presented along with a discussion on minimum mean-squared error(MMSE) symbol estimation techniques. These are shown to further improve the performance of parallel cancella-tion.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.323-337
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• 2004

This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.887-894
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• 2009

The two-stage minimum risk point estimation of mean, the probability of success in a sequence of Bernoulli trials, is considered for the case where loss is taken to be symmetrized relative squared error of estimation, plus a fixed cost per observation. First order asymptotic expansions are obtained for large sample properties of two-stage procedure. Monte Carlo simulation is carried out to obtain the expected sample size that minimizes the risk and to examine its finite sample behavior.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.929-941
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• 1997

In this paper, we propose the minimum risk estimator (MRE) and the approximate maximum likelihood estimator (AMLE) of the location and the scale parameters of the two-parameter exponential distribution with Type-II censoring. The MRE's can be derived by minimizing the mean squared error among the class of estimators which include some estimators as special cases. We show that the MRE's are more efficient than the other estimators of the scale and the location parameter in the terms of the mean squared error.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.3-8
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• 2013

In CDMA-based systems, recently, researches on chip-level equalization have been studied in order to improve receiving performance when supporting high-rate data services. In this paper, we consider a chip-level LMMSE (linear minimum mean-squared error) receiver for D-TxAA (dual stream transmit antenna array) based single stream HSDPA MIMO systems using precoding weights. First, we will derive precoding weights for maximizing the total instantaneous received power. We will also analyze the effects of both transmit delay of precoding weights and mobile velocity on chip-level LMMSE receivers, which is verified through computer simulations in various mobile channel environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.896-902
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• 2016

In this paper, we investigate a minimum mean-squared error based nonlinear successive precoding method as a practical solution of dirty paper coding for multiuser downlink channels where each user has more than one antenna in the presence of other cell interference (OCI). Unlike conventional zero-forcing (ZF) based methods, the proposed scheme takes the OCI plus noise into account when suppressing the inter-cell multiuser interference, which results in improvement of the received signal-to-interference-plus-noise ratio. Simulation results show that the proposed scheme outperforms conventional methods in terms of sum rate for various OCI configurations.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.59-64
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• 2009

In this paper, a novel low complexity linear receiver is proposed that is used at the receiver of MIMO systems. Zero-forcing (ZF) and minimum mean squared error (MMSE) receivers are common linear receivers. ZF receiver is simpler than MMSE receiver from the hardware implementation perspective, howerver, MMSE shows better performance than ZF. In general, MCS level changes according to channel condition. This paper shows the benefit of choosing between MMSE and ZF according to the selected MCS level. We implement the MCS-adaptive linear receiver as hardware, and show that its complexity is comparable to the conventional MMSE receiver.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.660-666
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• 2004

Transmitted data may be compensated by using estimated channel values that are obtained with pilot symbols in OFDM-CDMA systems. Generally, a USE (Minimum Mean-Squared Error) estimator using correlations between pilot symbols gives good results, but its structure is so complicated. Starting with a modification of PA (Pilot-Aided) algorithm using pilot symbols and PADD (Pilot-Aided Decision-Directed) algorithm using both pilot and data symbols, a new channel estimation algorithm with more simpler structure is proposed. The performance of this algorithm is evaluated with varying mobile speed in a Ralyleigh multipath fading environment through computer simulations. The simulation results show that the proposed channel estimation algorithm outperforms a conventional PA algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7A
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• pp.743-750
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• 2008

Orthogonal frequency division multiplexing (OFDM) is a attractive modulation scheme for high data rate transmission in frequency-selective channels. However, the time selectivity of wireless channel introduces intercarrier interference (ICI), and consequently degrades system performance. In this paper, we first propose a novel recursive algorithm for minimum mean squared error (MMSE) with successive interference cancellation (SIC). The proposed algorithm can significantly reduce the complexity of the MMSE-SIC scheme and achieve the same performance when optimal ordering is known. Also, the further reduced scheme of the proposed algorithm can be developed based on ICI properties, while preserving performance.