• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.162-164
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• 2010

Terrestrial trunked radio (TETRA) standard specifies shortened Reed-Muller (RM) codes as forward error correction means for control signals. In this paper, we compare decoding algorithms for RM codes in TETRA, in terms of performance and complexity trade-off. Belief propagation and majority logic decoding algorithms are selected for comparison.

• ETRI Journal
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• v.36 no.4
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• pp.591-598
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• 2014

This paper proposes a new min-sum algorithm for low-density parity-check decoding. In this paper, we first define the negative and positive effects of the received signal-to-noise ratio (SNR) in the min-sum decoding algorithm. To improve the performance of error correction by considering the negative and positive effects of the received SNR, the proposed algorithm applies adaptive scaling factors not only to extrinsic information but also to a received log-likelihood ratio. We also propose a combined variable and check node architecture to realize the proposed algorithm with low complexity. The simulation results show that the proposed algorithm achieves up to 0.4 dB coding gain with low complexity compared to existing min-sum-based algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.95-102
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• 2006

This paper proposes the KB-Fano algorithm which has lower decoding complexity by applying modified Fano-like metric bias to the conventional K-best algorithm. Additionally, an efficient K-best decoding algorithm, named the KR-Fano scheme, is proposed by jointly combining the K-reduction and the KB-Fano schemes. Simulations show that the proposed algerian provides the remarkable improvement from the viewpoints of the BER performance and the decoding complexity as compared to the conventional K-best scheme.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.146-149
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• 2022

In this letter, we propose low-complexity Hybrid-Partial-Gaussian-Approximation (HPGA) decoding methods for core-layer signal of Layered-Division-Multiplexing Multiple-Inputs-Multiple- Outputs ATSC 3.0 broadcasting systems. The proposed HPGA decoding methods have an advantage of being able to greatly reduce decoding complexity without significant performance degradation compared to a conventional PGA method, by selectively using existing GA and PGA methods according to a received injection-level at an each receive antenna.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1987-2001
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• 2017

Low-density parity-check (LDPC) codes have attracted a great attention because of their excellent error correction capability with reasonably low decoding complexity. Among decoding algorithms for LDPC codes, the min-sum (MS) algorithm and its modified versions have been widely adopted due to their high efficiency in hardware implementation. In this paper, a self-adaptive MS algorithm using the difference of the first two minima is proposed for faster decoding speed and lower power consumption. Finding the first two minima is an important operation when MS-based LDPC decoders are implemented in hardware, and the found minima are often compressed using the difference of the two values to reduce interconnection complexity and memory usage. It is found that, when these difference values are bounded, decoding is not successfully terminated. Thus, the proposed method dynamically decides whether the termination-checking step will be carried out based on the difference in the two found minima. The simulation results show that the decoding speed is improved by 7%, and the power consumption is reduced by 16.34% by skipping unnecessary steps in the unsuccessful iteration without any loss in error correction performance. In addition, the synthesis results show that the hardware overhead for the proposed method is negligible.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.13-18
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• 2011

Sphere Decoding (SD) is a decoding technique able to achieve the Maximum Likelihood (ML) performance in fading environments; nevertheless, the main disadvantage of this technique is its high complexity, especially in poor channel conditions. In this paper, we present an adaptive hybrid algorithm which reduces the conventional Sphere Decoder's complexity and keeps the ML performance. The system called Adaptive OSIC-SD modifies its operation based on Signal to Noise Ratio (SNR) information and achieves an optimal performance in terms of Bit Error Rate (BER) and complexity. Through simulations, we probe that the proposed system maintains almost the same bit error rate performance of the conventional SD, and exhibits a lower, quasi-constant complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.522-528
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• 2011

The iterative detection and decoding (IDD) has been shown to dramatically improve the bit error rate (BER) performance of the multiple-input multiple-output (MIMO) communication systems. However, these techniques require a high computational complexity since it is required to compute the soft decisions for each bit. In this paper, we show IDD comprised of sphere decoder with low-density parity check (LDPC) codes and present the tree search strategy, called a layer symbol search (LSS), to obtain soft decisions with a low computational complexity. In addition, an adaptive early termination is proposed to reduce the computational complexity during an iteration between an inner sphere decoder and an outer LDPC decoder. It is shown that the proposed approach can achieve the performance similar to an existing algorithm with 70% lower computational complexity compared to the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.11
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• pp.1051-1059
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• 2013

This paper proposes a complexity reduced list sphere decoding (LSD) scheme for joint iterative soft detection scheme for coded MIMO system. The conventional LSD scheme is based on searching the candidates with a fixed radius. However, once the candidate list is full, it is highly probable that the radius can be reduced. By reducing the radius, the complexity can be also reduced. We propose a simple and efficient radius update method for complexity reduction of list version sphere decoding and its application to iterative soft MIMO detection. We evaluate the performance of the proposed scheme with a joint soft-input-soft-ouput iterative MIMO detection in combination with turbo codes. Simulation results show that the proposed methods provide substantial complexity reduction while achieving similar bit error rate (BER) performance as the conventional LSD scheme.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.965-972
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• 2005

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen for second generation digital video broadcasting standard, are required a large number of computation due to large size of coded block and iteration. Therefore, we presented two kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algerian. Secondly, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and computational complexity of early detected method is about $50\%$ offs in case of check node update, $99\%$ offs in case of check node update compared to conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.10
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• pp.585-592
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• 2014

It is well known that serial belief propagation (BP) decoding for low-density parity-check (LDPC) codes achieves faster convergence without any increase of decoding complexity per iteration and bit error rate (BER) performance loss than standard parallel BP (PBP) decoding. Serial BP (SBP) decoding, such as horizontal SBP (H-SBP) decoding or vertical SBP (V-SBP) decoding, updates check nodes or variable nodes faster than standard PBP decoding within a single iteration. In this paper, we propose combined horizontal-vertical SBP (CHV-SBP) decoding. By the same reasoning, CHV-SBP decoding updates check nodes or variable nodes faster than SBP decoding within a serialized step in an iteration. CHV-SBP decoding achieves faster convergence than H-SBP or V-SBP decoding. We compare these decoding schemes in details. We also show in simulations that the convergence rate, in iterations, for CHV-SBP decoding is about $\frac{1}{6}$ of that for standard PBP decoding, while the convergence rate for SBP decoding is about $\frac{1}{2}$ of that for standard PBP decoding. In simulations, we use recently proposed generalized LDPC (GLDPC) codes with binary cyclic codes (BCC).