• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.509-513
• /
• 2002

This paper presents a semi-blind Minimum Mean Square Error (MMSE) beamforming adaptive algorithm used far OFDM/CDMA combined system. The proposed algorithm exploits the transmitting pilot signal in the initial period of the transmission to update the weight vector. Then it applies the blind adaptive period to update the weight vector, in which the pilot signal is no longer used. The derivation of the algorithm based on the Mean Square Error (MSE) criterion is also presented. Computer simulation is carried out to verify the performance of the proposed approach.

• Proceedings of the IEEK Conference
• /
• 2002.06a
• /
• pp.69-72
• /
• 2002

In this paper, adaptive minimum mean-squared error (MMSE) multiuser detector combined with decision-feedback detector (DFD) is considered fur near-far resistant DS-CDMA system. To provide a reliable input to the adaptive MMSE detector, multiple-access interference (MAI) is regenerated using bit estimates from DFD and subtracted from the received signal. In the adaptive MMSE detector, the effect of the imperfect cancellation is compensated by a least mean square (LMS) algorithm. Through the numerical results, it is shown that, in a near-far situation, the proposed scheme provides superior performance to the matched filter (MF) receiver, adaptive MMSE detector, and DFD in terms of the bit error rate (BER).

• The Journal of the Acoustical Society of Korea
• /
• v.29 no.2E
• /
• pp.86-99
• /
• 2010

This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.5
• /
• pp.39-43
• /
• 2020

In this paper, we propose the multi-channel interference cancellation algorithm for visible light communication (VLC) in smart building. The VLC system is communication technology using visible rays that come out in Light Emitting Diode (LED) device. It has energy curtailment effect and possible to use in ubiquitous network service applications. When a large number of users communicate indoors, the performance can be reduced due to channel interference. To remove interference, at the first, the minimum mean square error (MMSE) scheme as interference cancellation methods used, and then the successive interference cancellation (SIC) is applied to obtain additional diversity gain and improve interference cancellation performance. Indoor VLC channel model is employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the previous systems. As a result, the proposed interference cancellation improves the signal quality of VLC systems by effectively removing the channel noise. The results of the paper can be applied to VLC for smart building and general communication systems.

• The Journal of the Acoustical Society of Korea
• /
• v.15 no.4
• /
• pp.70-76
• /
• 1996

In the case of an image corrupted with mixed noise, conventional MMSE filter can not remove such a mixed noise properly, because the impulse moise cause a certain bias of the minimum mean-square error estimate at regions close to outliers. In this paper, we proposed the new method or removal of mixed noise by combining MMSE filtering structure with local multi-windowing method according to directions and with ranked-order method. As a result, the improvement of the image quality with the proposed was obtained between about 9.7 and 35.2 times in the sense of NMSE(normalized mean square errors) evaluation than that of MMSE filter. Also, we could obtain the enhanced image in the mixed noisy image from visual and quantitative aspect.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.18 no.12
• /
• pp.1408-1418
• /
• 2007

In this paper, we analyze the performance of pilot symbol assisted channel estimation and equalization schemes for OFDM systems over frequency-selective time-varying channels and propose methods to improve the system performance. In the least square(LS) and linear minimum mean square error(MMSE) channel estimation, time domain windowing is introduced for banding the frequency domain channel matrix. The linear MMSE and decision feedback equalization schemes are employed with the pilot symbols for channel estimation taken into account in the equalization process. To reduce computational complexity, the band LU matrix factorization algorithm is introduced in solving the linear systems involved in the equalization, and the performances are compared with the known previous results by computer simulations. When time domain windowing is employed in the decision feedback equalization, the matrix related with the decision feedback process is shown to be unhanded and the resultant performance degradation is analyzed.

• Journal of Communications and Networks
• /
• v.10 no.2
• /
• pp.118-126
• /
• 2008

The use of beamforming is effective for users in limited power environments. However, when it is applied to the downlink of a cellular system with universal frequency reuse, users near the sector boundary may experience significant interference from more than one sector. The use of a minimum mean square error (MMSE)-type receiver may not sufficiently cancel out the interference unless a sufficient number of receive antennas are used. In this paper, we consider the use of inter-sector beamforming that cooperates with a neighboring sector in the same cell to mitigate this interference problem in time-division duplex (TDD) environments. The proposed scheme can avoid interference from an adjacent sector in the same cell, while enhancing the transmit array gain by using the TDD reciprocity. The performance of the proposed scheme is analyzed in terms of the output signal-to-interference-plus-noise power ratio (SINR) and the output capacity when applied to an MMSE-type receiver. The beamforming mode can be analytically switched between the inter-sector and the single-sector mode based on the long-term channel information. Finally, the effectiveness of the proposed scheme is verified by computer simulation.

• Journal of information and communication convergence engineering
• /
• v.9 no.5
• /
• pp.500-504
• /
• 2011

In this paper, we propose an equivalent Wiener-Hopf equation. The proposed algorithm can obtain the weight vector of a TDL(tapped-delay-line) filter and the error simultaneously if the inputs are orthogonal to each other. The equivalent Wiener-Hopf equation was analyzed theoretically based on the MMSE(minimum mean square error) method. The results present that the proposed algorithm is equivalent to original Wiener-Hopf equation. The new algorithm was applied into the identification of an unknown system for evaluating the performance of the proposed method. We compared the Wiener-Hopf solution with the equivalent Wiener-Hopf solution. The simulation results were similar to those obtained in the theoretical analysis. In conclusion, our method can find the coefficient of the TDL (tapped-delay-line) filter where a lattice filter is used, and also when the process of Gram-Schmidt orthogonalization is used. Furthermore, a new cost function is suggested which may facilitate research in the adaptive signal processing area.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.1
• /
• pp.35-39
• /
• 2014

This paper proposes a Modified Minimum Mean Square Error (M-MMSE) estimator for an Orthogonal Frequency Division Multiplexing (OFDM) System over fast fading Rayleigh channel. The proposed M-MMSE estimator considered the effects of the efficient placement of pilots based on the channel energy distribution. The pilot symbols were placed in a non-linear manner according to the density of the channel energy. Comparative analysis of the MMSE estimator for a comb-type pilot arrangement and M-MMSE estimator for the proposed pilot insertion scheme revealed significant performance improvement of the M-MMSE estimator over the MMSE estimator.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1504-1526
• /
• 2018

For uplink multi-user massive MIMO systems, conventional minimum mean square error (MMSE) linear detection method achieves near-optimal performance when the number of antennas at base station is much larger than that of the single-antenna users. However, MMSE detection involves complicated matrix inversion, thus making it cumbersome to be implemented cost-effectively and rapidly. In this paper, we first summarize in detail the state-of-the-art simplified MMSE detection algorithms that circumvent the complicated matrix inversion and hence reduce the computation complexity from ${\mathcal{O}}(K^3)$ to ${\mathcal{O}}(K^2)$ or ${\mathcal{O}}(NK)$ with some certain performance sacrifice. Meanwhile, we divide the simplified algorithms into two categories, namely the matrix inversion approximation and the classical iterative linear equation solving methods, and make comparisons between them in terms of detection performance and computation complexity. In order to further optimize the detection performance of the existing detection algorithms, we propose more proper solutions to set the initial values and relaxation parameters, and present a new way of reconstructing the exact effective noise variance to accelerate the convergence speed. Analysis and simulation results verify that with the help of proper initial values and parameters, the simplified matrix inversion based detection algorithms can achieve detection performance quite close to that of the ideal matrix inversion based MMSE algorithm with only a small number of series expansions or iterations.