• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.9-14
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• 2009

Recently, a rate-2, $2{\times}2$ space-time code with simple ML decoding has been designed. Though the simple ML decoding algorithm does reduce the ML decoding complexity, there is still need for improvement. In this paper, we propose an efficient decoding algorithm for the rate-2, $2{\times}2$ space-time code using interference cancellation techniques with performance virtually identical to that of ML decoding. Also, the decoding complexity of the proposed algorithm is significantly reduced compared to the conventional simple ML decoding, especially for large modulation orders.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11C
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• pp.1025-1028
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• 2009

This paper presents upper bounds of Maximum Likelihood (ML) decoding performance of a few irregular LDPC codes using the simple bound and ML input output weight distributions and it is shown that contrary to general opinion that as block length becomes longer, BP decoding performance becomes simply closer to ML decoding performance, before peak degradation, as block length becomes longer, BP decoding performance falls behind ML decoding performance more and after peak degradation, general opinion holds.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.9-12
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• 2001

In this paper, the natural space-time coding is applied for a DS-CDMA system with multiple transmit/receive antennas in a Rayleigh fading channel. With difference of arrival times from transmit antennas a modified maximum likelihood (ML) decoding algorithm is proposed for the space-time coded DS-CDMA system. The proposed decoding algorithm performs ML decoding over the transition of two consecutive branches by using a modified branch metric with the partial autocorrelation. By simulation, it is shown that the proposed decoding algorithm achieves significant performance improvement over the ML decoding algorithm without the modified branch metric.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.594-597
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• 2010

This paper estimates belief-propagation (BP) decoding performance of moderate-length irregular low-density parity-check (LDPC) codes with sphere bounds. We note that for moderate-length($10^3{\leq}N{\leq}4\times10^3$) irregular LDPC codes, BP decoding performance, which is much worse than maximum likelihood (ML) decoding performance, is well matched with one of loose upper bounds, i.e., sphere bounds. We introduce the sphere bounding technique for particular codes, not average bounds. The sphere bounding estimation technique is validated by simulation results. It is also shown that sphere bounds and BP decoding performance of irregular LDPC codes are very close at bit-error-rates (BERs) $P_b$ of practical importance($10^{-5}{\leq}P_b{\leq}10^{-4}$).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.34-42
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• 2007

The sphere decoder (SD) has recently been proposed to perform maximum likelihood (ML) decoding for multi-input multi-output systems. Employing a 'breadth-first' searching algorithm for closet points in a lattice, we propose a novel ML decoding scheme for multi-input multi-output systems. Simulation results show that the proposed scheme has the same bit error rate performance as the conventional ML decoders while allowing significantly lower computational burden than the SD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2197-2204
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• 2009

In this paper, we analyze the performance of the sphere decoding algorithm at MIMO system. The BER performance of this algorithm is the same as that of ML receiver, but computational complexity of SD algorithm is much less than that of ML receiver. The independent signals from each transmit antennas are modulated by using the QPSK and 16QAM modulation in the richly scattered Rayleigh flat-fading channel. The received signals from each receivers is independently detected by the receiver using Fincke & Pohst SD algorithm, and the BER output of the algorithm is compared with those of ZF, MMSE, SIC, and ML receivers. We also investigate the Viterbo & Boutros SD algorithm which is the modified SD algorithm, and the BER performance and the floting point operations of the algorithms are comparatively studied.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.1-5
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• 2008

In this paper, we propose and analyze the AMC (Adaptive Modulation and Coding) system with efficient turbo coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique. The proposed algorithm adopts extrinsic information from a MAP (Maximum A Posteriori) decoder with iterative decoding as a priori probability in two decoding procedures of V-BLAST scheme; the ordering and the slicing. Also, we consider the AMC system using the conventional turbo coded V-BLAST technique that simply combines the V-BLAST scheme with the turbo coding scheme. And we compare the proposed decoding algorithm to a conventional V-BLAST decoding algorithm and a ML (Maximum Likelihood) decoding algorithm. In addition, we apply a STD (Selection Transmit Diversity) scheme to the systems for better performance improvement. Results indicate that the proposed systems achieve better throughput performance than the conventional systems over the entire SNR range. In terms of transmission rate performance, the suggested system is close in proximity to the conventional system using the ML decoding algorithm.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.5-9
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• 2008

Researchers have investigated many upper bound techniques applicable to error probabilities on the maximum likelihood (ML) decoding performance of turbo-like codes and low density parity check (LDPC) codes in recent years for a long codeword block size. This is because it is trivial for a short codeword block size. Previous research efforts, such as the simple bound technique [20] recently proposed, developed upper bounds for LDPC codes and turbo-like codes using ensemble codes or the uniformly interleaved assumption. This assumption bounds the performance averaged over all ensemble codes or all interleavers. Another previous research effort [21] obtained the upper bound of turbo-like code with a particular interleaver using a truncated union bound which requires information of the minimum Hamming distance and the number of codewords with the minimum Hamming distance. However, it gives the reliable bound only in the region of the error floor where the minimum Hamming distance is dominant, i.e., in the region of high signal-to-noise ratios. Therefore, currently an upper bound on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix cannot be calculated because of heavy complexity so that only average bounds for ensemble codes can be obtained using a uniform interleaver assumption. In this paper, we propose a new bound technique on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix using ML estimated weight distributions and we also show that the practical iterative decoding performance is approximately suboptimal in ML sense because the simulation performance of iterative decoding is worse than the proposed upper bound and no wonder, even worse than ML decoding performance. In order to show this point, we compare the simulation results with the proposed upper bound and previous bounds. The proposed bound technique is based on the simple bound with an approximate weight distribution including several exact smallest distance terms, not with the ensemble distribution or the uniform interleaver assumption. This technique also shows a tighter upper bound than any other previous bound techniques for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.907-910
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• 2010

This paper presents the design of block lengths for irregular low-density parity-check (LDPC) codes based on the maximum variable degree $d_{{\upsilon},max}$. To design a block length, the performance degradation of belief-propagation (BP) decoding performance from upper bounds on the maximum likelihood (ML) decoding performance is used as an important factor. Since for large block lengths, the performance of irregular LDPC codes is very close to the Shannon limit, we focus on moderate block lengths ($5{\times}10^2\;{\leq}\;N\;{\leq}\;4{\times}10^3$). Given degree distributions, the purpose of our paper is to find proper block lengths based on the maximum variable degree $d_{{\upsilon},max}$. We also present some simulation results which show how a block length can be optimized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.160-165
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• 2007

In this paper, we propose a novel signal detection method that achieves the maximum likelihood (ML) performance but requires much less computational complexity than the ML detection. When the well-known linear decoding method is used for space-time block coded (STBC) OFDM systems in fast-fading channels, co-channel interference (CCI) as well as inter-carrier interference (ICI) occurs. A maximum likelihood (ML) method can be employed to deal with the CCI; however, its computational complexity is very high. In this paper, we propose a signal detection method for orthogonal space-time coded OFDM systems that achieves the similar error performance as the ML method, but requires much less computational complexity.