• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.405-409
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• 2009

In this paper, the effects of LLR (Log-Likelihood Ratio) approximation on LDPC (Low-Density Parity-Check) decoder performance are analyzed, and optimal design conditions of LDPC decoder are derived. The min-sum LDPC decoding algorithm which is based on an approximation of LLR sum-product algorithm is modeled and simulated by MATLAB, and it is analyzed that the effects of LLR approximation bit-width and maximum iteration cycles on the bit error rate (BER) performance of LDCP decoder. The parity check matrix for IEEE 802.11n standard which has block length of 1,944 bits and code rate of 1/2 is used, and AWGN channel with QPSK modulation is assumed. The simulation results show that optimal BER performance is achieved for 7 iteration cycles and LLR bit-width of (7,5).

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.221-222
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• 2008

We propose a LLR (log-likelihood ratio) selection combining technique that reduces much of complexity. This technique chooses the most reliable branch based on the magnitude of the LLR of each branch. We show that the proposed selection combining achieves significant power gains over conventional selection combining and nearly matches the performance provided by MRC.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.771-774
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• 2010

In this paper, BER performance of LDPC(Low-Density Parity-Check) decoder for WiMAX is analyzed, and optimal design conditions of LDPC decoder are derived. The min-sum LDPC decoding algorithm which is based on an approximation of LLR sum-product algorithm is modeled and simulated by Matlab, and it is analyzed that the effects of LLR approximation bit-width and maximum iteration cycles on the bit error rate(BER) performance of LDCP decoder. The parity check matrix for IEEE 802.16e standard which has block length of 2304 and code rate of 1/2 is used, and AWGN channel with QPSK modulation is assumed. The simulation results show that optimal BER performance is achieved for 7 iteration cycles and LLR bit-width of (8,6).

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.276-284
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• 2012

Classification algorithms generally assume that the data is complete. However, missing values are common in real data sets due to various reasons. In this paper, we propose to use locally linear reconstruction (LLR) for missing value imputation to improve the classification performance when missing values exist. We first investigate how much missing values degenerate the classification performance with regard to various missing ratios. Then, we compare the proposed missing value imputation (LLR) with three well-known single imputation methods over three different classifiers using eight data sets. The experimental results showed that (1) any imputation methods, although some of them are very simple, helped to improve the classification accuracy; (2) among the imputation methods, the proposed LLR imputation was the most effective over all missing ratios, and (3) when the missing ratio is relatively high, LLR was outstanding and its classification accuracy was as high as the classification accuracy derived from the compete data set.

• ETRI Journal
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• v.28 no.3
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• pp.291-300
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• 2006

A simple and general bit log-likelihood ratio (LLR) expression is provided for Gray-coded rectangular quadrature amplitude modulation (R-QAM) signals. The characteristics of Gray code mapping such as symmetries and repeated formats of the bit assignment in a symbol among bit groups are applied effectively for the simplification of the LLR expression. In order to reduce the complexity of the max-log-MAP algorithm for LLR calculation, we replace the mathematical max or min function of the conventional LLR expression with simple arithmetic functions. In addition, we propose an implementation algorithm of this expression. Because the proposed expression is very simple and constructive with some parameters reflecting the characteristic of the Gray code mapping result, it can easily be implemented, providing an efficient symbol de-mapping structure for various wireless applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2227-2234
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• 2009

DVB-SSP is a new broadcasting system for hybrid satellite communications, which supports mobile handheld systems and fixed terrestrial systems. An upper layer, including erasure Reed-Solomon error correction combined with cyclic redundancy check. However, a critical factor must be considered in upper layer decoding. If there is only one bit error in an IP packet, the entire IP packet is considered as unreliable bytes, even if it contains correct bytes. If, for example, there is one real byte error, in an IP packet of 512 bytes, 511 correct bytes are erased from the frame. Therefore, this paper proposed upper layer decoding methods; LLR-based decoding. By means of simulation we show that the performance of the proposed decoding algorithm is superior to that of the conventional one.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.939-947
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• 2010

The LDPC(Low-Density Parity-Check) code, which is one of the channel encoding methods in IEEE 802.11n wireless LAN standard, has superior error-correcting capabilities. Since the hardware complexity of LDPC decoder is high, it is very important to take into account the trade-offs between hardware complexity and decoding performance. In this paper, the effects of LLR(Log-Likelihood Ratio) approximation on the performance of MSA(Min-Sum Algorithm)-based LDPC decoder are analyzed, and some optimal design conditions are derived. The parity check matrix with block length of 1,944 bits and code rate of 1/2 in IEEE 802.11n WLAN standard is used. In the case of $BER=10^{-3}$, the $E_b/N_o$ difference between LLR bit-widths (6,4) and (7,5) is 0.62 dB, and $E_b/N_o$ difference for iteration cycles 6 and 7 is 0.3 dB. The simulation results show that optimal BER performance can be achieved by LLR bit-width of (7,5) and iteration cycle of 7.

• 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).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1020-1023
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• 2011

In this paper, we present a symbol remapping method of BRGC M-ary QAM signal by using LLR soft bit decision information which is obtained after iterative decoding process. In order to reconstruct estimated transmitted signal constellation, we have to use exponential or hyperbolic tangent(tanh) function resulting in high implementation complexity. The BRGC mapping rule enables us to use a recursive operation. In addtion, we reduce the implementing complexity by using a curve fitting algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2207-2214
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• 2010

Underwater acoustic(UWA) communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of UWA channel causes signal distortion and error floor. In this paper, we proposed split input bits of channel decoder using method of maximum value, average value, LLR value for optimal estimation. Channel coding method is LDPC(N size=16000) standard in DVB-S2. As shown in simulation results, the performance of LLR value method is better than other methods.