• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1296-1309
• /
• 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)
• /
• v.18 no.5
• /
• pp.1412-1430
• /
• 2024

The soft cancellation list (SCANL) decoding algorithm for polar codes runs L soft cancellation (SCAN) decoders with different decoding factor graphs. Although it can achieve better decoding performance than SCAN algorithm, it has high latency. In this paper, a fast simplified SCANL (Fast-SSCANL) algorithm that runs L independent Fast-SSCAN decoders is proposed. In Fast-SSCANL decoder, special nodes in each factor graph is identified, and corresponding low-latency decoding approaches for each special node is propose first. Then, syndrome check aided Fast-SSCANL (SC-Fast-SSCANL) algorithm is further put forward. The ordinary nodes satisfied the syndrome check will execute hard decision directly without traversing the factor graph, thereby reducing the decoding latency further. Simulation results show that Fast-SSCANL and SC-Fast-SSCANL algorithms can achieve the same BER performance as the SCANL algorithm with lower latency. Fast-SSCANL algorithm can reduce latency by more than 83% compared with SCANL, and SC-Fast-SSCANL algorithm can reduce more than 85% latency compared with SCANL regardless of code length and code rate.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.3
• /
• pp.880-894
• /
• 1997

In this paper,we propose a new algorithm to perform DCT(Discrete Cosine Transform) withn the area reduced by prdeicting position of quantization coefficients to be zero.This proposed algorithm not only decreases the enoding time and the decoding time by reducing computation amount of FDCT(Forward DCT)and IDCT(Inverse DCT) but also increases comprossion ratio by performing each diffirent horizontal- vereical zig-zag scan assording to the calssified block size for each block on the huffiman coeing.Traditional image coding method performs the samd DCT computation and zig-zag scan over all blocks,however this proposed algorthm reduces FDCT computation time by setting to zero insted of computing DCT for quantization codfficients outside classfified block size on the encoding.Also,the algorithm reduces IDCT computation the by performing IDCT for only dequantization coefficients within calssified block size on the decoding.In addition, the algorithm reduces Run-Length by carrying out horizontal-vertical zig-zag scan approriate to the slassified block chraateristics,thus providing the improverment of the compression ratio,On the on ther hand,this proposed algorithm can be applied to 16*16 block processing in which the compression ratio and the image resolution are optimal but the encoding time and the decoding time take long.Also,the algorithm can be extended to motion image coding requirng real time processing.

• Journal of Information Technology Applications and Management
• /
• v.11 no.2
• /
• pp.179-190
• /
• 2004

This paper describes the design of hacking prevention systems using a smart card. It consists of two parts, i.e., PC authentication and Keyboard-buffer hacking prevention. PC authentication function is a procedure to handle the access control to the target PC. The card's serial number is used for PIN(Personal Identification Number) and is converted into hash-code by SHA-1 hash-function to verify the valid users. The Keyboard-buffer hacking prevention function converts the scan codes into the encoded forms using RSA algorithm on the Java Card, and puts them into the keyboard-buffer to protect from illegal hacking. The encoded information in the buffer is again decoded by the RSA algorithm and displayed on the screen. in this paper, we use RSA_PKCS#1 algorithm for encoding and decoding. The reason using RSA technique instead of DES or Triple-DES is for the expansion to multi-functions in the future on PKI. Moreover, in the ubiquitous computing environment, this smart card security system can be used to protect the private information from the illegal attack in any computing device anywhere. Therefore, our security system can protect PC user's information more efficiently and guarantee a legal PC access authority against any illegal attack in a very convenient way.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.1 no.3
• /
• pp.97-103
• /
• 2008

In this paper, $256{\times}256$ input image is classified into a validity block and an edge block of $8{\times}8$ block for image compression. DCT(Discrete Cosine Transform) is executed only for the DC coefficient that is validity coefficients for a validity block. Predict the position where a quantization coefficient becomes 0 for an edge block, I propose new algorithm to execute DCT in the reduced region. Not only this algorithm that I proposed reduces computational complexity of FDCT(Forward DCT) and IDCT(Inverse DCT) and decreases encoding time and decoding time. I let compressibility increase by accomplishing other stability verticality zigzag scan by the block size that was classified for each block at the time of huffman encoding each. In addition, the algorithm that I suggested reduces Run-Length by accomplishing the level verticality zigzag scan that is good for a classified block characteristic and, I offer the compressibility that improved thereby.