• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.939-946
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• 1999

A new blind multi-user channel estimation algorithm for the mobile communication systems is proposed. The proposed algorithm exploits the second-order statistics of a received signal and the subspace concept, and requires much less computational complexity than the existing algorithms. The algorithm can reduce the comptational load by estimating the physical channels excluding the spreading codes. We formulate the algorithm using the multi-channel model for asynchronous DS-CDMA systems and perform numerical experiments to evaluate the performance of the proposed algorithm.

• ETRI Journal
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• v.41 no.5
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• pp.658-669
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• 2019

For dual-channel time-frequency (TF) overlapped signals with low sparsity in underdetermined blind source separation (UBSS), this paper proposes an effective method based on interval probability to estimate and expand the types of mixing matrices. First, the detection of TF single-source points (TF-SSP) is used to improve the TF sparsity of each source. For more distinguishability, as the ratios of the coefficients from different columns of the mixing matrix are close, a local peak-detection mechanism based on interval probability (LPIP) is proposed. LPIP utilizes uniform subintervals to optimize and classify the TF coefficient ratios of the detected TF-SSP effectively in the case of a high level of TF overlap among sources and reduces the TF interference points and redundant signal features greatly to enhance the estimation accuracy. The simulation results show that under both noiseless and noisy cases, the proposed method performs better than the selected mainstream traditional methods, has good robustness, and has low algorithm complexity.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.254-261
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• 2007

In this paper, we propose a blind equalization method for advanced terrestrial digital multimedia broadcasting (AT-DMB) systems which use hierarchical modulation. The AT-DMB system adopts hierarchical 16-ary quadrature amplitude modulation (16-QAM) to ensure backward-compatibly with the differential quadrature phase shift keying (DQPSK) signal of the legacy terrestrial digital multimedia broadcasting (T-DMB) systems and to support higher transmission rate. Due to the hierarchical modulation, the conventional T-DMB signal and the additional signal have different error rate at same signal to noise ratio (SNR). By weighting the decided symbols differently according to the reliability of the symbols, i.e., high priority symbol with low error rate and low priority symbol with high error rate, we can improve the channel estimation accuracy. In this paper, we analyze SNR loss by hierarchical modulation and confirm it through simulations. Moreover, through simulations, we verify that the proposed weighting method improve BER compared to the no-weighting method.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.481-486
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• 2012

Accurate and efficient estimation of the number of sources is critical for providing the parameter of targets in problems of array signal processing and blind source separation among other such problems. When conventional estimators work in unfavorable scenarios, e.g., at low signal-to-noise ratio (SNR), with a small number of snapshots, or for sources with a different strength, it is challenging to maintain good performance. In this paper, the detection limit of the minimum description length (MDL) estimator and the signal strength required for reliable detection are first discussed. Though a comparison, we analyze the reason that performances of classical estimators deteriorate completely in unfavorable scenarios. After discussing the limiting distribution of eigenvalues of the sample covariance matrix, we propose a new approach for estimating the number of sources which is based on a sequential hypothesis test. The new estimator performs better in unfavorable scenarios and is consistent in the traditional asymptotic sense. Finally, numerical evaluations indicate that the proposed estimator performs well when compared with other traditional estimators at low SNR and in the finite sample size case, especially when weak signals are superimposed on the strong signals.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.215-221
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• 2010

This paper introduces development of location estimation and navigation system of mobile robots using USN and LEGO Mindstorms NXT. Developed system includes location estimation, location and navigation information display and navigation control parts. It used ZigBee based USN which was built with CC2431 chip to locate blind node and implemented fuzzy model to improve ability of calculation of distances from reference nodes and location of mobile robots. This paper proposed combination method of location estimation using USN and encoder which is built in motors of mobile robots. Experimental results showed proposed method is superior to the method which used USN only in location estimation and navigating robots. Developed system can locate current position of mobile robots and monitor information from sensor nodes like temperature, humidity and send control signal to mobile robot to move.

• Journal of Sensor Science and Technology
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• v.23 no.3
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• pp.158-164
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• 2014

In indoor sensor networks equalization algorithms based on the minimization of Euclidean distance (MED) for the distributions of constant modulus error (CME) have yielded superior performance in compensating for signal distortions induced from optical fiber links, wireless-links and for impulsive noise problems. One main drawback of MED-CME algorithms is a heavy computational burden hindering its implementation. In this paper, a recursive gradient estimation for weight updates of the MED-CME algorithm is proposed for reducing the operations $O(N^2)$ of the conventional MED-CME to O(N) at each iteration time for N data-block size. From the simulation results of the proposed recursive method producing exactly the same results as the conventional method, the proposed estimation method can be considered to be a reliable candidate for implementation of efficient receivers in indoor sensor networks.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1780-1783
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• 2002

A problem of signal transmitted and received in OFDM systems is considered. In particular, an efficient solution to the problem of blind channel estimation based on Maximum Likelihood (ML) principle has been investigated. The paper proposes a new upper-bound cost, used in conjunction with a standard branch and bound integer programming technique for solving the ML problem. The tighter upper-bound cost exploits a finite-alphabet property of the transmitted signal. The proposed upper-bound cost was found to greatly speed up the ML algorithm, thus reducing computational complexity. Experimental results and discussion are included.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.210-217
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• 2022

Passive source depth estimation has been studied for decades since the source depth can be used for target classification, target tracking, etc. The purpose of this paper is to solve the problem of ambiguity in the previous paper [S.-il. Cho et al. (in Korean), J. Acoust. Soc. Kr. 38, 120-127 (2019)] that source depth is estimated in two points. The patterns of phase shift of Channel Impulse Response(CIR) reflected in ocean surface and bottom is used for removing ambiguity of the source depth estimation, and after removing ambiguity, source depth is estimated at one point through the intersection of CIR. In order to extract CIR in case of unknown source signal and continuous signal or noise, Ray-based blind deconvolution is used. The proposed algorithm is demonstrated through numerical simulation in ocean waveguide.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.378-386
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• 2017

Accurate distance measurement between maneuver target in underwater and measuring devices is required to perform quantitative test evaluation in marine weapons system R&D process. In general, the target distance is measured using a one-way ToA (Time of Arrival) method that calculates the time difference between transmitted and received signals from the two accurately synchronized devices. However, the distance estimation performance is degraded because of the multi-path environments. In this paper, the time-variant transfer function of complex underwater environment is estimated from each received data frame using RBD (Ray-based Blind Deconvolution), and the estimated time-variant transfer function is then used to get rid of the effect about complex underwater environment and to recover the data signal using PTRM (Passive Time Reversal Mirror). The result from the simulation and experimental data show that the suggested method improve the distance estimation performance when comparing with the conventional ToA method.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.328-335
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• 2005

This paper proposes a frequency domain independent component analysis (ICA) algorithm to separate the mixed speech signals using a multiple microphone array By estimating the delay timings using a input cross-correlation, even in the delayed mixture case, we propose a good initial value setting method which leads to optimal convergence. To reduce the calculation, separation process is performed at frequency domain. The results of simulations confirms the better performances of the proposed algorithm.