• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.39-47
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• 2021

Lempel-Ziv coding is one of the most famous source coding schemes. The output of this source coding is usually a non-uniform code, which requires additional source coding, such as arithmetic coding, to reduce a redundancy. However, this additional source code increases complexity and decoding latency. Thus, this paper proposes the optimal maximum a-posteriori (MAP) receiver for non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC). First, we derive an analytical expression of the bit-error rate (BER) for non-uniform source NOMA with SSC. Then, Monte Carlo simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform source. Moreover, we also show that the BER of an approximate analytical expression is in a good agreement with the BER of Monte Carlo simulation. As a result, the proposed optimal MAP receiver for non-uniform source could be a promising scheme for NOMA with SSC, to reduce complexity and decoding latency due to additional source coding.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.265-271
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• 2010

This paper discusses a new software package, DEM_Comp, developed for effectively compressing large digital elevation model (DEM) data sets based on Lempel-Ziv-Welch (LZW) compression and Huffman coding. DEM_Comp was developed using the $C^{++}$ language running on a Windows-series operating system. DEM_Comp was also tested on various test sites with different territorial attributes, and the results were evaluated. Recently, a high-resolution version of the DEM has been obtained using new equipment and the related technologies of LiDAR (LIght Detection And Radar) and SAR (Synthetic Aperture Radar). DEM compression is useful because it helps reduce the disk space or transmission bandwidth. Generally, data compression is divided into two processes: i) analyzing the relationships in the data and ii) deciding on the compression and storage methods. DEM_Comp was developed using a three-step compression algorithm applying a DEM with a regular grid, Lempel-Ziv compression, and Huffman coding. When pre-processing alone was used on high- and low-relief terrain, the efficiency was approximately 83%, but after completing all three steps of the algorithm, this increased to 97%. Compared with general commercial compression software, these results show approximately 14% better performance. DEM_Comp as developed in this research features a more efficient way of distributing, storing, and managing large high-resolution DEMs.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.322-331
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• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.48-54
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• 2021

In most existing researches on non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC), uniform sources have been usually considered. For the first part in this two-part paper, for the strongest channel gain user, we showed that the bit-error rate (BER) for the optimal maximum a-posteriori (MAP) receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform sources. We demonstrate that in communication scenarios of the non-uniform source NOMA schemes, for the weakest channel gain user, the BER performance of the optimal MAP receiver for a non-uniform source improves greatly, compared to that of the conventional receiver for uniform sources. We first derive an analytical expression of the BER for non-uniform source NOMA with SSC. Then, simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves, compared with that of the conventional maximum likelihood (ML) receiver for the uniform sources. In result, the proposed optimal MAP receiver for the non-uniform source could be a promising scheme for SSC NOMA, with improved BER performances.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.78-84
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• 2022

In this paper, to improve further the bit-error rate (BER) performance of the stronger channel user in non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC), we propose a smart bit-to-symbol (BTS) mapping of SSC. First, the analytical expression for the total allocated power of the proposed BTS mapping scheme is derived, and then we show that the BER of the proposed BTS mapping scheme improves further, compared to that of the existing BTS mapping scheme. Moreover, based on the simulations, the signal-to-noise (SNR) gain of the proposed BTS mapping scheme over the existing BTS mapping scheme is calculated. In result, the proposed BTS mapping could be a candidate scheme for non-uniform source SSC NOMA with the SNR gain.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.36-41
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• 2022

Recently, to improve the performance of the strongest channel gain user in non-orthogonal multiple access (NOMA) with a non-uniform source and symmetric superposition coding (SSC), a novel bit-to-symbol (BTS) mapping have been proposed. However, only the performance of the user with the stronger channel gain was analyzed. Thus, we compare the bit-error rate (BER) of the new BTS scheme with that of uniform sources, especially for the user with weakest channel gain. First, we show that the performance of the novel BTS scheme for the user with weakest channel gain also improves, compared to that of the uniform sources. Furthermore, the signal-to-noise (SNR) gain of the new BTS scheme over the uniform sourcesis calculated. As a consequence, the novel BTS scheme would improve the performance of the user with weakest channel gain as well as that with the stronger channel gain for SSC NOMA with a non-uniform source.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.33-40
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• 2002

In this paper, we proposed a lossless compression algorithm of medical images which is essential technique in picture archive and communication system. Mammographic image and magnetic resonance image in among medical images used in this study, proposed a region growing segmentation algorithm for compression of these images. A proposed algorithm was partition by three sub region which error image, discontinuity index map, high order bit data from original image. And generated discontinuity index image data and error image which apply to a region growing algorithm are compressed using JBIG(Joint Bi-level Image experts Group) algorithm that is international hi-level image compression standard and proper image compression technique of gray code digital Images. The proposed lossless compression method resulted in, on the average, lossless compression to about 73.14% with a database of high-resolution digital mammography images. In comparison with direct coding by JBIG, JPEG, and Lempel-Ziv coding methods, the proposed method performed better by 3.7%, 7.9% and 23.6% on the database used.