• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.527-539
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• 2009

In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.112-121
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• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.6-12
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.11
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• pp.21-27
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• 2002

When decision-directed channel estimation is used for QAM-OFDM systems, the optimal shape of the two-dimensional filter depends on the amplitudes of the modulated symbols as well as the channel characteristics such as delay spread, Doppler frequency, and signal-to-noise ratio. While most conventional channel estimation methods did not consider the amplitudes of the modulated symbols because of the large computational complexity, we propose a simple channel estimation method for multi-level-amplitude-modulated systems. The proposed method can effectively reduce the noise variance of the estimates with small-sized filtering and there is a possibility of reducing the implementation cost and producing better results by avoiding the bias due to large filter sizes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.89-97
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• 2012

In this paper, we propose a novel approach to noise power estimation for speech enhancement in noisy environments. The method based on IMCRA (improved minima controlled recursive averaging) which is widely used in speech enhancement utilizes a rough VAD (voice activity detection) algorithm which excludes speech components during speech periods in order to improves the performance of the noise power estimation by reducing the speech distortion caused by the conventional algorithm based on the minimum power spectrum derived from the noisy speech. However, since the VAD algorithm is not sufficient to distinguish speech from noise at non-stationary noise and low SNRs (signal-to-noise ratios), the speech distortion resulted from the minimum tracking during speech periods still remained. In the proposed method, minimum power estimate obtained by IMCRA is modified by SMT (spectral minima tracking) to reduce the speech distortion derived from the bias of the estimated minimum power. In addition, in order to effectively estimate minimum power by considering the distribution characteristic of the speech and noise spectrum, the presented method combines the minimum estimates provided by IMCRA and SMT depending on the weighting factor based on the subband. Performance of the proposed algorithm is evaluated by subjective and objective quality tests under various environments and better results compared with the conventional method are obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11B
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• pp.1522-1533
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• 2001

In this paper, we handle the estimation method of the received $E_{b}l1_{o}$ for forward closed-loop power control in cdma2000 systems. The estimation of MS-received $E_{b}l1_{o}$ utilizes the symbols related to the forward power control subchannel transmission. The estimation of the received bit energy and noise variance is analyzed for the frequency-selective Rayleigh fading channel. In order to improve SIR (signal-to-interference), the estimation of the received bit energy is made by the coherent combining of the rake-fingers and received I/Q symbols. And, in this paper, we evaluate the performance of forward closed-loop power control according to the mobile speed and the power adjustment step size in terms of the bit error rate (BER) and power control error. Simulation results present the optimal power adjustment step sizes according to the mobile speeds.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.689-695
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• 2006

This paper focuses on the accurate performance evaluation of cooperative diversity technique with imperfect channel estimates. The channel environment for simulations and performance evaluation is supposed to be the slowly time-varying Rayleigh fading channel. The framework of the performance evaluation is based on the Moment Generating Function(MGF) approach. To apply the effect of this channel estimation error into the performance evaluation, we import an useful Gaussian approximation in formulating the effective noise component and the additive noise. The average BER performance of cooperative diversity with M-PSK and M-QAM is computed as a function of the ratio of the signal to the effective noise based on the approximation. The verification of computed performance is provided with simulations. The evaluated performance matches up to simulation results even in a low SNR region.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.52-57
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• 2001

The passive ranging estimation techniques using a focused beamformer have been studied under the water. It is well known that the passive ranging estimation method using a focused beamformer is excellently evaluated. Among these, the passive ranging sonar is known to have a good performance under low signal-to-noise. ratio. However, its performance is degraded in multi-source environments. In this paper, we proposed the technique using dual focused beamformers to estimate the range. And when the sampling frequency is low, it is very difficult to steer the focused beam to the desired direction, as a result of this, the low performance occurs because of a distorted beam pattern. In this paper, we study the effect of sampling rate on passive ranging by using focused beamformer. And we verified the performance of the proposed method via computer simulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.67-76
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• 2019

Despite attractive advantages such as good time-frequency localization and improved spectral efficiency, filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) suffers from multipath fading. In highly frequency-selective channels, the effect of multipath interference can significantly distort the FBMC/OQAM signal due to the absence of cyclic prefix. To resolve the problem of the multipath interference in FBMC/OQAM, this paper proposes applying an antenna array that provides well shaped beam pattern for each multipath. To evaluate the performance of the proposed array system, various computer simulations have been conducted. The accuracy of direction of arrival estimation is demonstrated through spatial spectrum for a different number of antennas in a sub-array. The performance improvement is presented in terms of bit error rate. We found that the proposed array system mitigate the multipath interferences in Extended Typical Urban model with 12 antennas in a sub-array. Moreover, as the number of antennas in a sub-array increases, the system provides a signal-to-noise ratio gain.