The rate-distortion region for multiple descriptions without excess rate
IEEE Transactions on Information Theory
New results in binary multiple descriptions
IEEE Transactions on Information Theory
Elements of information theory
Elements of information theory
Binary erasure multiple descriptions: worst-case distortion
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Achieving the rate-distortion bound with low-density generator matrix codes
IEEE Transactions on Communications
New coding schemes for the symmetric K -description problem
IEEE Transactions on Information Theory
Achievable rates for multiple descriptions
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Multiple description coding with many channels
IEEE Transactions on Information Theory
n-channel symmetric multiple descriptions - part I: (n, k) source-channel erasure codes
IEEE Transactions on Information Theory
n-channel symmetric multiple descriptions-part II: An achievable rate-distortion region
IEEE Transactions on Information Theory
Successive Wyner–Ziv Coding Scheme and Its Application to the Quadratic Gaussian CEO Problem
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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The cliff effect is a phenomenon evidenced when the quality of received data drops abruptly when the channel quality falls below a critical point and does not improve once the channel quality surpasses this point. In modern networks (content delivery networks (CDNs), mobile, wireless), when content is transmitted over diverse channels to heterogeneous users, the cliff effect becomes a major impediment. In simultaneous video delivery to multiple users, the users with channel quality below the critical point will receive unwatchable streams, whereas those whose channel quality is well above it will not see any improvement. We propose a multiple description based joint source-channel coding approach to suppress the cliff effect in video delivery, which can be optimized according to a statistical description of the channels, and specific requirements of the application. After introducing the analytical model of the proposed approach, we describe two possible strategies to modify state-of-the-art video codecs. This involves design of a new data processing block based on linear complexity encoding by sparse codes, which is our ongoing work. © 2012 Alcatel-Lucent. © 2012 Wiley Periodicals, Inc.