On the sumrate loss of quadratic Gaussian multiterminal source coding
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This work studies the sumrate loss of quadratic Gaussian multiterminal source coding, i.e., the difference between the minimum sumrates of distributed encoding and joint encoding (both with joint decoding) of correlated Gaussian sources subject to MSE distortion constraints on individual sources. It is shown that under the nondegraded assumption, i.e., all target distortions are simultaneously achievable by a BergerTung scheme, the supremum of the sumrate loss of distributed encoding over joint encoding of L jointly Gaussian sources increases almost linearly in the number of sources L, with an asymptotic slope of 0.1083 b/s per source as L goes to infinity. This result is obtained even though we currently do not have the full knowledge of the minimum sumrate for the distributed encoding case. The main idea is to upperbound the minimum sumrate of multiterminal source coding by that achieved by parallel Gaussian test channels while lowerbounding the minimum sumrate of joint encoding by a reverse waterfilling solution to a relaxed joint encoding problem of the same set of Gaussian sources with a sumdistortion constraint (that equals the sum of the individual target distortions). We show that under the nondegraded assumption, the supremum difference between the upper bound for distributed encoding and the lower bound for joint encoding is achieved in the bieigen equalvariance with equal distortion case, in which both bounds are known to be tight. © 2010 IEEE.
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Yang, Y., Zhang, Y., & Xiong, Z.
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Yang, YangZhang, YifuXiong, Zixiang
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International Standard Book Number (ISBN) 13
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