• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.175-180
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• 2012

This paper presents a blind watermark detection scheme for an additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind source separation (BSS) based on independent component analysis (ICA) is used. Low watermark-to-signal ratio (WSR) is one of the limitations of blind detection with the additive embedding model. The proposed detector uses two-stage processing to improve the WSR at the blind detector; the first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses the resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on ICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlationbased detection schemes.

• ETRI Journal
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• v.42 no.3
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• pp.324-332
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• 2020

In this paper, a blind symbol timing offset (STO) estimation method is proposed for offset quadrature phase-shift keying (OQPSK) modulated signals, which also works for other linearly modulated signals (LMS) such as binary-PSK, QPSK, 𝜋/4-QPSK, and minimum-shift keying. There are various methods available for blind STO estimation of LMS; however, none work in the case of OQPSK modulated signals. The popular cyclic correlation method fails to estimate STO for OQPSK signals, as the offset present between the in-phase (I) and quadrature (Q) components causes the cyclic peak to disappear at the symbol rate frequency. In the proposed method, a set of close and approximate offsets is used to compensate the offset between the I and Q components of the received OQPSK signal. The STO in the time domain is represented as a phase in the cyclic frequency domain. The STO is therefore calculated by obtaining the phase of the cyclic peak at the symbol rate frequency. The method is validated through extensive theoretical study, simulation, and testbed implementation. The proposed estimation method exhibits robust performance in the presence of unknown carrier phase offset and frequency offset.

• 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.

• ETRI Journal
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• v.45 no.2
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• pp.226-239
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• 2023

Challenges in cognitive radio and tactical communications include recognizing anonymously received signals and estimating parameters in a blind or semi-blind manner. In this paper, we examine this issue for orthogonal frequency division multiplexing (OFDM) signaling. There are several parameters in OFDM signaling, and the blind receiver must extract and consider the synchronization issue. We assume that the blind receiver is aware of modulation type, OFDM, and not aware of chip duration and the length of cyclic prefix. First, we present new criteria based on kurtosis to estimate these parameters and compare their performance at different levels of additive white Gaussian noise with methods based on correlation, kurtosis, maximum likelihood, and matched filter. Then, we perform synchronization and estimate the start time based on these criteria and several new criteria in two steps: fine and coarse synchronization. Finally, in a more practical setup, we present the idea of jointly estimating the mentioned parameters and the signal start time as coarse synchronization. We compare different criteria and show that one of the proposed criteria has the highest efficiency.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.114-120
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• 2003

Blind channel estimation of communication channels is a problem of important current theoretical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. This paper proposes the blind adaptive channel estimation using multichannel linear prediction method. Computer simulations are presented to compare the proposed algorithm with the existing ones.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.416-418
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• 2006

In this paper, a new acoustic echo cancellation approach based on the DUET algorithm and scaling factor estimation is proposed to solve the scaling ambiguity in case of blind separation based acoustic echo cancellation in a noisy environment. In hands-free full-duplex communication system. acoustic noises picked up by the microphone are mixed with echo signal. For this reason, the echo cancellation system may provide poor performance. For that purpose, a degenerate unmixing estimation technique, adjusted in the time-frequency domain, is employed to separate undesired echo signals and noises. Also, since scaling and permutation ambiguities have not been solved in the blind source separation algorithm, kurtosis for the desired signal selection and a scaling factor estimation algorithm are utilized in this rarer for the separation of an echo signal. Simulation results demonstrate that the proposed approach yields better echo cancellation and noise reduction performances, compared with conventional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.9
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• pp.863-871
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• 2004

In this paper, we propose a subspace channel estimation technique for DS/CDMA DMB down link system, which can obtain reduction in numerical complexity by using of matched filtering outputs. The complexity reduction is considerable when the channel length is small and the system is moderately loaded. Previously proposed subspace-based blind channel estimation algorithm suffer from high numerical complexity for systems with large spreading gains. Although the proposed algerian suffers a slight performance loss, it becomes negligible for large observation length. Performance is evaluated through simulations and the derivation of the analytical MSE.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.891-897
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• 2018

In this paper, we propose a blind estimation scheme for the antenna spacing of nonuniform linear array MIMO radar using distributed electronic sensors based on ESPRIT. We present a blind method to separate orthogonal waveforms of a MIMO radar based on the antenna spacing estimation. The estimated orthogonal waveforms of a MIMO radar can be used for disabling opponent MIMO radars.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.91-100
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• 2023

Reverberation time (T60) is a typical acoustic parameter that provides information about reverberation. Since the impacts of reverberation vary depending on the frequency bands even in the same space, frequency-dependent (FD) T60, which offers detailed insights into the acoustic environments, can be useful. However, most conventional blind T60 estimation methods, which estimate the T60 from speech signals, focus on fullband T60 estimation, and a few blind FDT60 estimation methods commonly show poor performance in the low-frequency bands. This paper introduces a modified approach based on Attentive pooling based Weighted Sum of Spectral Decay Rates (AWSSDR), previously proposed for blind T60 estimation, by extending its target from fullband T60 to FDT60. The experimental results show that the proposed method outperforms conventional blind FDT60 estimation methods on the acoustic characterization of environments (ACE) challenge evaluation dataset. Notably, it consistently exhibits excellent estimation performance in all frequency bands. This demonstrates that the mechanism of the AWSSDR method is valuable for blind FDT60 estimation because it reflects the FD variations in the impact of reverberation, aggregating information about FDT60 from the speech signal by processing the spectral decay rates associated with the physical properties of reverberation in each frequency band.

• ETRI Journal
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• v.41 no.4
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• pp.426-436
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• 2019

In time division duplex (TDD)-based multiuser massive multiple input multiple output (MIMO) systems, the uplink channel is estimated and the results are used in downlink for signal detection. Owing to noisy uplink channel estimation, the downlink channel should also be estimated for accurate signal detection. Therefore, recently, a blind method was developed, which assumes the use of a linear high-power amplifier (HPA) in the base station (BS). In this study, we extend this method to a scenario with a nonlinear HPA in the BS, where the Bussgang decomposition is used for HPA modeling. In the proposed method, the average power of the received signal for each user is a function of channel gain, large-scale fading, and nonlinear distortion variance. Therefore, the channel gain is estimated, which is required for signal detection. The performance of the proposed method is analyzed theoretically. The simulation results show superior performance of the proposed method compared to that of the other methods in the literature.