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Wireless Communications and Mobile Computing
Volume 2018, Article ID 6387214, 13 pages
Research Article

Efficient Quantization with Linear Index Coding for Deep-Space Images

1School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
2Institute of Space Technology, Islamabad, Pakistan
3Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China

Correspondence should be addressed to Qin Huang; nc.ude.aaub@gnauhniq

Received 24 November 2017; Revised 14 May 2018; Accepted 10 September 2018; Published 11 October 2018

Academic Editor: Gonzalo Vazquez-Vilar

Copyright © 2018 Rehan Mahmood et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Due to inevitable propagation delay involved in deep-space communication systems, very high cost is associated with the retransmission of erroneous segments. Quantization with linear index coding (QLIC) scheme is known to provide compression along with robust transmission of deep-space images, and thus the likelihood of retransmissions is significantly reduced. This paper aims to improve its spectral efficiency as well as robustness. First, multiple quantization refinement levels per transmitted source block of QLIC are proposed to increase spectral efficiency. Then, iterative multipass decoding is introduced to jointly decode the subsource symbol-planes. It achieves better PSNR of the reconstructed image as compared to the baseline one-pass decoding approach of QLIC.