TY - GEN
T1 - Sparse source recovery with graph in network coding
AU - Yu, Sung Bok
AU - Choe, Yoonsik
N1 - Publisher Copyright:
© 2016 Asia Pacific Signal and Information Processing Association.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/1/17
Y1 - 2017/1/17
N2 - In network coding, the successive original video frame data can be transmitted at once. However, if insufficient number of innovative packets are transmitted due to the packet loss or delay, network coding system is to be underdetermined. Thus, since network coding matrix (random coefficient matrix) is not invertible, original data cannot be recovered by matrix inversion. To solve this problem, in this paper, a new compressive sensing method with graph Laplacian regularizer is proposed, which exploits correlation between successive original video frame data. Experimental results demonstrate the effectiveness of proposed algorithm, implemented by the alternative direction multiplier method (ADMM) and show that PSNR values from reconstructed images are above 33dB with coding matrix Φ CM×N of which measurement M = 0.75N and 22dB with measurement M = 0.66N, respectively.
AB - In network coding, the successive original video frame data can be transmitted at once. However, if insufficient number of innovative packets are transmitted due to the packet loss or delay, network coding system is to be underdetermined. Thus, since network coding matrix (random coefficient matrix) is not invertible, original data cannot be recovered by matrix inversion. To solve this problem, in this paper, a new compressive sensing method with graph Laplacian regularizer is proposed, which exploits correlation between successive original video frame data. Experimental results demonstrate the effectiveness of proposed algorithm, implemented by the alternative direction multiplier method (ADMM) and show that PSNR values from reconstructed images are above 33dB with coding matrix Φ CM×N of which measurement M = 0.75N and 22dB with measurement M = 0.66N, respectively.
UR - http://www.scopus.com/inward/record.url?scp=85013777455&partnerID=8YFLogxK
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U2 - 10.1109/APSIPA.2016.7820844
DO - 10.1109/APSIPA.2016.7820844
M3 - Conference contribution
AN - SCOPUS:85013777455
T3 - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
BT - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Y2 - 13 December 2016 through 16 December 2016
ER -