• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.721-728
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• 2018

This paper introduces various linear block error correction code and compares performances of the correction circuits. As the risk of errors due to power noise has increased, ECC(: Error Correction Code) has been introduced to prevent the bit error. There are two representatives of ECC structures which are SEC-DED(: Single Error Correction Double Error Detection) and SEC-DED-DAEC(: Double Adjacent Error Correction). According to simulation results, the SEC-DED circuit has advantages of small area and short delay time compared to SEC-DED-DAEC circuits. In case of SED-DED-DAEC, there is no big difference between Dutta's and Pedro's from performance point of view. Therefore, Pedro's code is more efficient than Dutta' code since the correction rate of Pedro's code is higher than that of Dutta's code.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.535-544
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• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.97-106
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• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.498-504
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• 2009

A high-performance low-complexity decoding algorithm for LDPC codes is proposed in this paper, which has the advantages of both bit-flipping (BF) algorithm and sum-product algorithm (SPA). The proposed soft bit-flipping algorithm requires only simple comparison and addition operations for computing the messages between bit and check nodes, and the amount of those operations is also small. By increasing the utilization ratio of the computed messages and by adopting nonuniform quantization, the signal-to-noise ratio (SNR) gap to the SPA is reduced to 0.4dB at the frame error rate of 10-4 with only 5-bit assignment for quantization. LDPC codes with high column or row weights, which are not suitable for the SPA decoding due to the complexity, can be practically implemented without much worsening the error performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.3
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• pp.169-173
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• 2012

This paper investigates the performance of Turbo equalization in wireless multipath channels. Turbo equalization mainly consists of a SISO(soft-in soft-out) equalizer and a SISO decoder. Iterative channel estimators can improve the accuracy of channel estimates by soft information fed back from the SISO decoder. Comparing iterative channel estimators with LMS(least mean square) and RLS(recursive least squares) algorithms, which are the most common algorithms to estimate and track a time-varying channel impulse response, the iterative channel estimator with RLS converges more faster than the one with LMS. However, the difference of BER(bit error rate) performances gradually decreases as the number of iterations for Turbo equalization increases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.430-435
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• 2018

In this paper, an improved decoding scheme for low-complexity parity-check(LCPC) code with small code length is proposed. The LCPC code is less complex than the turbo code or low density parity check(LDPC) code and requires less memory, making it suitable for communication between internet-of-things(IoT) devices. The IoT devices are required to have low complexity due to limited energy and have a low end-to-end delay time. In addition, since the packet length to be transmitted is small and the signal processing capability of the IoT terminal is small, the LCPC coding system should be as simple as possible. The LCPC code can correct all single errors and correct some of the two errors. In this paper, the proposed decoding scheme improves the bit error rate(BER) performance without increasing the complexity by correcting both errors using the soft value of the modulator output stage. As a result of the simulation using the proposed decoding scheme, the code gain of about 1.1 [dB] was obtained at the bit error rate of $10^{-5}$ compared with the existing decoding method.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2343-2351
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• 2024

Accurately predicting the thermal hydraulic parameters of a transient reactor core under different working conditions is the first step toward reactor safety. Mass flow rate and temperature are important parameters of core thermal hydraulics, which have often been modeled as time series prediction problems. This study aims to achieve accurate and continuous prediction of core thermal hydraulic parameters under instantaneous conditions, as well as test the feasibility of a newly constructed gated recurrent unit (GRU) model based on the soft attention mechanism for core parameter predictions. Herein, the China Experimental Fast Reactor (CEFR) is used as the research object, and CEFR 1/2 core was taken as subject to carry out continuous predictive analysis of thermal parameters under transient conditions., while the subchannel analysis code named SUBCHANFLOW is used to generate the time series of core thermal-hydraulic parameters. The GRU model is used to predict the mass flow and temperature time series of the core. The results show that compared to the adaptive radial basis function neural network, the GRU network model produces better prediction results. The average relative error for temperature is less than 0.5 % when the step size is 3, and the prediction effect is better within 15 s. The average relative error of mass flow rate is less than 5 % when the step size is 10, and the prediction effect is better in the subsequent 12 s. The GRU model not only shows a higher prediction accuracy, but also captures the trends of the dynamic time series, which is useful for maintaining reactor safety and preventing nuclear power plant accidents. Furthermore, it can provide long-term continuous predictions under transient reactor conditions, which is useful for engineering applications and improving reactor safety.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.739-742
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• 2000

In this paper, we evaluate the throughput and delay performance of a wireless Local Area Network(WLAN) employing the OFDM-based IEEE 802.lla Medium Access Control(MAC) protocol by compute. simulations under wireless indoor. channel. Packet Error Rate(PER) is also investigated for the various Eb/No. It is shown that, with soft-decision Viterbi decoder, throughput and delay performance are close to those of error-free channel at Eb/No above 8dB and PER is about 2${\times}$10$\^$-5/ at Eb/No=10dB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1296-1309
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• 2023

In this paper, based on the soft cancellation (SCAN) bit-flipping (SCAN-BF) algorithm, a generalized SCAN bit-flipping (GSCAN-BF-Ω) decoding algorithm is carried out, where Ω represents the number of bits flipped or corrected at the same time. GSCAN-BF-Ω algorithm corrects the prior information of the code bits and flips the prior information of the unreliable information bits simultaneously to improve the block error rate (BLER) performance. Then, a joint threshold scheme for the GSCAN-BF-2 decoding algorithm is proposed to reduce the average decoding complexity by considering both the bit channel quality and the reliability of the coded bits. Simulation results show that the GSCAN-BF-Ω decoding algorithm reduces the average decoding latency while getting performance gains compared to the common multiple SCAN bit-flipping decoding algorithm. And the GSCAN-BF-2 decoding algorithm with the joint threshold reduces the average decoding latency further by approximately 50% with only a slight performance loss compared to the GSCAN-BF-2 decoding algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3447-3469
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• 2019

It is well-known that the cooperative communication and error control technology can improve the network performance, but most existing cooperative MAC protocols have not focused on how to cope with the contention process caused by cooperation and how to reduce the bad influence of channel packet error rate on the system performance. Inspired by this, this paper first modifies and improves the basic rules of the IEEE 802.11 Medium Access Control (MAC) protocol to optimize the contention among the multi-relay in a cooperative ARQ scheme. Secondly, a hybrid ARQ protocol with soft combining is adopted to make full use of the effective information in the error data packet and hence improve the ability of the receiver to decode the data packet correctly. The closed expressions of network performance including throughput and average packet transmission delay in a saturated network are then analyzed and derived by establishing a dedicated two-dimensional Markov model and solving its steady-state distribution. Finally, the performance evaluation and superiority of the proposed protocol are validated in different representative study cases through MATLAB simulations.