Information unequal error protection using polar codes

Hadi, Ammar; Alsusa, Emad; Al-Dweik, Arafat

doi:10.1049/iet-com.2017.1195

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…The scenario that HEVC and polar codes are involved in source and channel coding respectively is not tackled in the above mentioned works. As for JSCC related polar codes, Jin et al [26] considered joint source Joint Source-Channel Decoding of Polar Codes for HEVC Based Video Streaming 100:5 and channel polarization and Hadi et al [21] utilized the channel polarisation property to achieve UEP.…”

Section: Polar Code Related Jscd Schemesmentioning

confidence: 99%

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Lin

Zhang

et al. 2022

ACM Trans. Multimedia Comput. Commun. Appl.

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Ultra High-Definition (UHD) and Virtual Reality (VR) video streaming over 5G networks are emerging, in which High-Efficiency Video Coding (HEVC) is used as source coding to compress videos more efficiently and polar code is used as channel coding to transmit bitstream reliably over an error-prone channel. In this article, a novel Joint Source-Channel Decoding (JSCD) of polar codes for HEVC-based video streaming is presented to improve the streaming reliability and visual quality. Firstly, a Kernel Density Estimation (KDE) fitting approach is proposed to estimate the positions of error channel decoded bits. Secondly, a modified polar decoder called R-SCFlip is designed to improve the channel decoding accuracy. Finally, to combine the KDE estimator and the R-SCFlip decoder together, the JSCD scheme is implemented in an iterative process. Extensive experimental results reveal that, compared to the conventional methods without JSCD, the error data-frame correction ratios are increased. Averagely, 1.07% and 1.11% Frame Error Ratio (FER) improvements have been achieved for Additive White Gaussian Noise (AWGN) and Rayleigh fading channels, respectively. Meanwhile, the qualities of the recovered videos are significantly improved. For the 2D videos, the average Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) gains reach 14% and 34%, respectively. For the 360֯ videos, the average improvements in terms of Weighted-to-Spherically-uniform PSNR (WS-PSNR) and Voronoi-based Video Multimethod Assessment Fusion (VI-VMAF) reach 21% and 7%, respectively.

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Section: Polar Code Related Jscd Schemesmentioning

confidence: 99%

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Lin

Zhang

et al. 2022

ACM Trans. Multimedia Comput. Commun. Appl.

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“…

P e_{N} false(i false)

is calculated in AWGN channel by GA algorithm. According to [4, 10], it is convenient to achieve UEP for information with different importance levels, through mapping information importance to bit‐channel reliability. Firstly, all information bits are sorted into a number of subsets where each subset has its own important level or reliability requirement.…”

Section: Polar Codes and Uep Propertymentioning

confidence: 99%

“…Note that polar codes can be utilised to achieve efficient UEP without any significant modification to the procedures of encoding and decoding. The similar UEP scheme has been applied to the JPEG2000 compression technique [10] and shows better performance than the conventional transmission with EEP. In [18], in consideration of the error propagation problem in SC decoding, a modified construction of polar code is proposed to improve UEP performance.…”

Section: Polar Codes and Uep Propertymentioning

confidence: 99%

“…By channel polarisation operation on N independent uses of a binary‐input discrete memoryless channel (BI‐DMC), N bit‐channels with distinguished capacities or reliabilities are generated. Through mapping between the reliability of bit‐channels and the importance of information bits, it is easy to achieve the UEP property by assigning more important information to the most reliable bit‐channels [4, 10]. This is an obvious advantage of polar codes in contrast to other types of coding schemes such as turbo and LDPC codes.…”

Section: Introductionmentioning

confidence: 99%

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Rateless transmission of polar codes with information unequal error protection

et al. 2019

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“…In [6], a low complexity UEP scheme is designed to jointly allocate bits among source coding, channel coding and cooperation to minimize the reconstructed distortion of JPEG 2000 image transmission at the receiver. The authors of [7] introduce a technique that utilizes the channel polarization property of polar codes to achieve UEP without any significant modification within the context of JPEG 2000. In [8], a hierarchical channel coding schemes providing UEP is used for progressive quality JPEG 2000 image transmission over noisy channel.…”

Section: Introductionmentioning

confidence: 99%

Efficient Multiple Concatenated Codes With Turbo-Like Decoding for UEP Wireless Transmission of Scalable JPEG 2000 Images

et al. 2019

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Most multimedia source encoders produce scalable bit streams that are vulnerable to noisy channel effects. Unequal error protection (UEP) designs are attractive solutions for such scalable bit streams. In the other hand, the structure of multiple concatenated codes, which consist of the combination of two or more elementary encoders and interleavers, offers a flexible implementation of unequal data protection. To provide an efficient protection for embedded source bit streams, an adaptive concatenated coding/decoding design is proposed in this paper inspired by serially concatenated turbo codes. This scheme involves iterative decoding of concatenated codes for JPEG 2000 image transmission. In the case of time varying channels, the concatenated coding rates are adaptively chosen to maximize the visual quality. The simulation results show that the proposed scheme achieves better image quality improvements at the receiver side compared with a conventional multiple turbo codes-based design, with significant peak-signal-to-noise ratio gains. INDEX TERMS Scalable bit streams, unequal error protection (UEP), multiple concatenated codes, iterative decoding, JPEG 2000. Recently, [5] proposed a turbo code that provides descending protection capabilities for the data according to their locations

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Information unequal error protection using polar codes

Cited by 16 publications

References 24 publications

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Rateless transmission of polar codes with information unequal error protection

Efficient Multiple Concatenated Codes With Turbo-Like Decoding for UEP Wireless Transmission of Scalable JPEG 2000 Images

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