Abstract
This paper investigates the transmission of grey scale images encoded with polar codes and de-coded with successive cancellation list (SCL) decoders in the presence of additive white Gaussian noise. Po-lar codes seem a natural choice for this application be-cause of their error-correction efficiency combined with fast decoding. Computer simulations are carried out for evaluating the influence of different code block lengths in the quality of the decoded images. At the encoder a default polar code construction is used in combination with binary phase shift keying modulation. The results are compared with those obtained by using the clas-sic successive cancellation (SC) decoding introduced by Arikan. The quality of the reconstructed images is assessed by using peak signal to noise ratio (PSNR) and the structural similarity (SSIM) index. Curves of PSNR and SSIM versus code block length are presented il-lustrating the improvement in performance of SCL in comparison with SC.
Highlights
The ever increasing use of Internet services leads to challenges concerning transmission or storage of signals, such as image and video
Differing from the work in (Payommai & Chamnongthai, 2013) and (Mishra et al, 2014), the main goal of this paper is to investigate the quality of grey scale images transmitted through a communication system, where images are encoded with polar codes for transmission over an AWGN channel, using binary phase-shift keying (BPSK) modulation and successive cancellation list (SCL) decoding, for signal to noise ratio (Eb/N0) values in the range of 0 dB to 2 dB, i.e., low signal to noise ratios
The quality of the reconstructed images is assessed by their corresponding peak signal to noise ratio (PSNR) and structural similarity (SSIM) for a range of values of Eb/N0 and block lengths N
Summary
The ever increasing use of Internet services leads to challenges concerning transmission or storage of signals, such as image and video. Latency becomes a critical issue in bi-directional digital communication systems as, for example, live ex-change of medical images or mobile phone conversation. Among other improvements in future mobile systems, 5G mobile phone systems (Carlton, 2017) will employ both polar codes (Arikan, 2009) and low density parity check codes (Gallager, 2001) to reduce latency. In this paper we make use of a recent contribution to error-correcting codes, called polar codes by Arikan (Arikan, 2009), as mentioned earlier, considering the context of image transmission. Polar coding for image and speech transmission using successive cancellation (SC) decoding has been proved to perform better than low density parity check (LDPC) codes over AWGN channels (Zhao, Shi, & Wang, 2011; Payommai & Chamnongthai, 2013). The concatenation of a polar code with a BCH code is considered in (Mishra et al, 2014) and shown to improve performance in comparison with the use of polar codes, at a cost of reducing overall code rate
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