• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7A
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• pp.659-667
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• 2002

In this dissertation, in the Turbo Code used for error correction coding of the recent digital communication systems, we propose a new S-R interleaver that has the better performance than the existing block interleaver, and the Turbo Decoder that has the parallel concatenated New structure using the MAP algorithm. For real-time voice and video services over the third generation mobile communications, the performance of two proposed methods is analyzed by the reduced decoding delay using the variable decoding method by computer simulation over multipath channels of DS-CDMA system. Also, a Modified NCMA based on conventional NCMA is proposed to improve the channel efficiency in the mobile communication system, and is investigated over the multi-user environment of DS-CDMA system through computer simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.28-38
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• 2013

In this paper, we propose a improved turbo equalizer which generates a feedback signal through a simple calculation to improve performance in single carrier system with the LMS(least mean square) algorithm based equalizer and LDPC(low density parity check) codes. LDPC codes can approach the Shannon limit performance closely. However, computational complexity of LDPC codes is greatly increased by increasing the repetition of the LDPC codes and using a long parity check matrix in harsh environments. Turbo equalization based on LDPC code is used for improvement of system performance. In this system, there is a disadvantage of very large amount of computation due to the increase of the repetition number. To less down the amount of this complicated calculation, The proposed improved turbo equalizer adjusts the adoptive equalizer after the soft decision and the LDPC code. Through the simulation results, it's confirmed that performance of improved turbo equalizer is close to the SISO-MMSE(soft input soft output minimum mean square error) turbo equalizer based on LDPC code with the smaller amount of calculation.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.665-671
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• 2010

In this paper, a turbo equalizer is proposed for the digital video broadcasting for terrestrial - 2nd generation (DVB-T2) system. The proposed turbo equalizer is consisted with the maximum a posteriori (MAP) and low density parity check (LDPC) decoder. The channel information for the soft-input-soft-output (SISO) MAP equalizer is based on the least square (LS) channel estimator. The performance is analyzed through computer simulations in terms of the iteration number.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1290-1298
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• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics, and uses the information to the next decoding step Turbo Code shows excellent performance, approaching Shannon Limit at the view of BER, when the size of Interleaver is big and iterate decoding is run enough. But it has the problems which are increased complexity and delay and difficulty of real-time processing due to Interleaver and iterate decoding. In this paper, it is analyzed that MAP(maximum a posteriori) algorithm which is used as one of Turbo Code decoding, and the factor which determines its performance. MAP algorithm proceeds iterate decoding by determining soft decision value through the environment and transition probability between all adjacent bits and received symbols. Therefore, to improve the performance of MAP algorithm, the trust between adjacent received symbols must be ensured. However, MAP algorithm itself, can not do any action for ensuring so the conclusion is that it is needed more algorithm, so to decrease iterate decoding. Consequently, MAP algorithm and Turbo Code performance are analyzed in the nongaussian channel applying Robust equalization technique in order to input more trusted information into MAP algorithm for the received symbols.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1688-1695
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• 2016

Underwater communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of underwater channel causes signal distortion and error floor. The excessive multipath encountered in underwater communication channel creates inter symbol interference, which is a limiting factor to achieve a high data rate and bit error rate performance. Therefore, to increase throughput efficiency and improve performance, this paper consider FTN (Faster-than-Nyquist) signalling based on turbo equalization. FTN signalling is a technique of transmitting information at a rate higher than the allowed Nyquist limit. This paper presented efficient decoder structure of FTN transmission in the environment of multipath underwater channel and we compare the performance between FTN method and conventional punctured method in lake experimentation. As a results of lake experiment, we confirmed FTN method based on turbo equalization is applicable and efficiency in underwater communication.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.257-265
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• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics in each decoding step, and uses the information to the next decoding step. Viterbi decoder, which is for a convolutional code, runs continuous mode, while Turbo Code decoder runs by block unit. There are algorithms used in a decoder : which are MAP(maximum a posteriori) algorithm requiring very complicated calculation and SOVA(soft output Viterbi algorithm) using Viterbi algorithm suggested by Hagenauer, and it is known that the decoding performance of MAP is better. The result of this make experimentation shows that the performance of SOVA, which has half complex algorithm compare to MAP, is almost same as the performance of MAP when the SOVA decoding performance is supplemented with Robust equalization techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1323-1329
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• 2014

In this paper, we analyzed efficient decoding scheme with FTN (Faster than Nyquist) method that is transmission method faster than Nyquist theory and increase the throughput. we proposed viterbi equalizer model to minimize ISI (Inter-Symbol Interference) when FTN signal is transmitted. the proposed model utilized interference as branch information. In this paper, to decode FTN singal, we used turbo equalization algorithms that iteratively exchange probabilistic information between soft Viterbi equalizer (BCJR method) and LDPC decoder. By changing the trellis diagram in order to maximize Euclidean distance, we confirmed that performance was improved compared to conventional methods as increasing throughput of FTN signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1531-1538
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• 2015

In this paper, we proposed receiver structure based on an iterative turbo equalization to cope with phase difference between two sensors in MIMO underwater communication channel. In a space-time coded system, it is often assumed that there are no phase errors among the multiple transmitter and receiver chains. In this paper, we have studied the effect of the phase errors between different transmit sensors and different propagation paths in the environment of MIMO underwater communication system, and have shown through BER performance by computer simulations that the bit-error-rate performance can be severely degraded. A decision-directed estimation and compensation algorithm has been proposed to minimize their effects on the system performance. In this paper, we investigate the phase differences and their effects on multiple-input and multiple-output systems, and propose a compensation algorithm for underwater channel model to minimize their effects.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.344-352
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• 2020

Covertness and performance are very important design goals in the underwater communications. To satisfy both of them, we proposed efficient underwater communication model which combined multiband and direct sequence spread spectrum method in order to improve performance and covertness simultaneously. Turbo coding method with 1/3 coding rates is used for channel coding algorithm, and turbo equalization method which iterately exchange probabilistic information between equalizer and decoder is used for receiver side. After optimal threshold value was set in Rake processing, this paper analyzed the performance by varying the number of chips were 8, 16, 32 and the number of bands were from 1 to 4. Through the simulation results, we confirmed that the performance improvement was obtained by increasing the number of bands and chips. 2~3 dB of performance gain was obtained when the number of chips were increased in same number of bands.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.293-297
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• 2015

Underwater acoustic communications has been limited use for military purposes in the past. However, the fields of underwater applications expend to detection, submarine and communication in recent. The excessive multipath encountered in underwater acoustic communication channel is creating inter symbol interference, which is limiting factor to achieve a high data rate and bit error rate performance. To improve the performance of a received signal in underwater communication, many researchers have been studied for channel coding scheme with excellent performance at low SNR. In this paper, we applied BCJR decoder based ( 2,1,7 ) convolution codes and to compensate for the distorted data induced by the multipath, we applying the turbo equalization method. Through the underwater experiment on the Gyeungcheun lake located in Mungyeng city, we confirmed that turbo equalization structure of BCJR has better performance than hard decision and soft decision of Viterbi decoding. We also confirmed that the error rate of decoder input is less than error rate of $10^{-1}$, all the data is decoded. We achieved sucess rate of 83% through the experiment.