| Autor: |
Ullah, Khadem, Minallah, Nasru, Nayab, Durre, Ahmed, Ishtiaque, Frnda, Jaroslav, Nedoma, Jan |
| Předmět: |
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| Zdroj: |
Computers, Materials & Continua; 2023, Vol. 75 Issue 1, p995-1010, 16p |
| Abstrakt: |
With the ever growth of Internet users, video applications, and massive data traffic across the network, there is a higher need for reliable bandwidth-efficient multimedia communication. Versatile Video Coding (VVC/H.266) is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding (HEVC) while providing versatile effective use for Ultra-High Definition (HD) videos. This article analyzes the quality performance of convolutional codes, turbo codes and self-concatenated convolutional (SCC) codes based on performance metrics for reliable future video communication. The advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon limit. Turbo codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional (RSC) encoders in a parallel fashion. Constituent RSC encoders may be operating on the same or different architectures and code rates. The proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading (SP-DSTS) for video transmission in order to provide bandwidth-efficient wireless video communication. Moreover, simulation results show that turbo codes defeat convolutional codes with an averaged Eb/N0 gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an Eb/N0 gain of 3.5 dBatBit ErrorRate (BER) of 10-4. The Peak Signal to Noise Ratio (PSNR) results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at Eb/N0 value of 4.5 dB. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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