• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.949-961
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• 2009

This paper analyses BER (Bit Error Rate) performance of 2-hop wireless communications networks with hybrid decode-and-forward (HDF) relays. The conventional HDF method is usually based on the receive signal-to-noise ratio (SNR) for the relay to decide whether to forward the decoded data in order to obviate the erroneous detection at the relay. In contrast, we propose a new solution of using log-likelihood ratio (LLR) as an efficient alternative to SNR. The approximate BER expressions of different HDF schemes are also derived and verified by Monte-Carlo simulations. In addition, we compute the optimum thresholds for HDF schemes. A variety of numerical results demonstrate that the new LLR-based HDF significantly outperforms the SNR-based HDF for any threshold level and relay location under flat Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).

• Journal of Communications and Networks
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• v.14 no.5
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.310-319
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• 1995

We represent graphically the relationship of hierachical log linear models by regarding the values of the likelihood ratio statistics as the squared norm of the corresponding vectors. Right angled triangles, tetrahedrons, and modified polyhedrons are used for graphical description. We find that the angle between the two vectors depends on the coefficient of determination and the partial coefficent of determination. Thess graphical descriptions could be applied to the model selection method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.303-309
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• 2006

By combining the space-time diversity technique and iterative turbo codes, space-time turbo codes(STTCS) are able to provide powerful error correction capability. However, the multi-path transmission and iterative decoding structure of STTCS make the decoder very complex. In this paper, we propose a low complexity decoder, which can be used to decode STTCS as well as general iterative codes such as turbo codes. The efficient implementation of the backward recursion and the log-likelihood ratio(LLR) update in the proposed algorithm improves the computational efficiency. In addition, if we approximate the calculation of the joint LLR by using the approximate ratio(AR) algorithm, the computational complexity can be reduced even further. A complexity analysis and computer simulations over the Rayleigh fading channel show that the proposed algorithm necessitates less than 40% of the additions required by the conventional Max-Log-MAP algorithm, while providing the same overall performance.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.82-85
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• 1987

Preliminary results of using the LPC parameter for text-independent speaker identification problem are presented. The idetification process includes log likelihood ratio for distance measure and dynamic programming for time normalization. To generate the data base for experiments, ten times. Experimental results show 99.4% of identification accuracy, incorrect identification were made when the speaker uses a dialect.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.47-53
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• 2004

We propose a new speech enhancement algorithm based on left-right Hidden Markov Model (HMM) with state decision using Log-likelihood Ratio Test (LRT). Since the conventional HMM-based speech enhancement methods try to improve speech quality for all states, they introduce huge computational loads inappropriate to real-time implementation. In the left-right HMM, only the current and the next state are considered for a possible state transition so to reduce the computational complexity. In this paper, we propose a method to decide the current state by using the LRT on the previous state. Experimental results show that the proposed method improves the speed up to 60% with 0.2∼0.4 dB degradation of speech quality compared to the conventional method.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.111-117
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• 2011

In this paper, the BER(Bit Error Rate) performance of a DVB-T2(Second Generation Digital Terrestrial Television Broadcasting System) in MISO(Multiple Input Single Output) transmission mode is evaluated by the computer simulation. In the DVB-T2 receiver, an IDD(Iterative Demapping and Decoder) technique is employed that exchanges extrinsic information between the demapper and the LDPC decoder. Simulation results show that the IDD-based DVB-T2 receiver in MISO transmission mode provides 2dB gain at BER of $10^{-4}$ but suffer from the frequency offsets between transmit antennas.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.17-21
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• 2017

Since holographic data storage has the advantage of high recording density and data transfer rate, it is a candidate for the next generation storage systems. However, Holographic data storage system is affected by interpage interference and two dimensional intersymbol interference. Also, burst error occurs by physical impact. In this paper, we propose an LDPC product code using modified log-likelihood ratio and extrinsic information to correct burst error and improve performance of holographic data storage. The performance of proposed LDPC product code is 0.5dB better than that of the conventional LDPC code.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.563-572
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• 2011

Reliability is an essential factor in a navigation system. Therefore, an integrity monitoring system is considered one of the most important parts in an avionic navigation system. A fault due to systematic malfunctioning definitely requires integrity reinforcement through systematic analysis. In this paper, we propose a method to detect faults of the GPS signal by using a distributed nonlinear filter based probability test. In order to detect faults, consistency is examined through a likelihood ratio between the main and auxiliary particle filters (PFs). Specifically, the main PF which includes all the measurements and the auxiliary PFs which only do partial measurements are used in the process of consistency testing. Through GPS measurement and the application of the autonomous integrity monitoring system, the current study illustrates the performance of the proposed fault detection algorithm.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.552-562
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• 2018

With the advent of the information society, image restoration technology has aroused considerable interest. Guided image filtering is more effective in suppressing noise in homogeneous regions, but its edge-preserving property is poor. As such, the critical part of guided filtering lies in the selection of the guided image. The result of the Expected Patch Log Likelihood (EPLL) method maintains a good structure, but it is easy to produce the ladder effect in homogeneous areas. According to the complementarity of EPLL with guided filtering, we propose a method of coupling EPLL and guided filtering for image de-noising. The EPLL model is adopted to construct the guided image for the guided filtering, which can provide better structural information for the guided filtering. Meanwhile, with the secondary smoothing of guided image filtering in image homogenization areas, we can improve the noise suppression effect in those areas while reducing the ladder effect brought about by the EPLL. The experimental results show that it not only retains the excellent performance of EPLL, but also produces better visual effects and a higher peak signal-to-noise ratio by adopting the proposed method.