TY - JOUR
T1 - Energy-distortion tradeoffs in gaussian joint source-channel coding problems
AU - Jain, Aman
AU - Gündüz, Deniz
AU - Kulkarni, Sanjeev R.
AU - Poor, H. Vincent
AU - Verdú, Sergio
N1 - Funding Information:
Manuscript received August 13, 2010; revised September 28, 2011; accepted October 06, 2011. Date of publication January 31, 2012; date of current version April 17, 2012. This work was supported in part by the Center for Science of Information, the National Science Foundation (NSF) Science and Technology Center under Grant CCF-0939370, and by the NSF under Grant CNS-09-05398. The work of D. Gündüz was supported by the European Commission’s Marie Curie International Reintegration Grant Fellowship with Reference 256410 under the Seventh Framework Programme, and by the Spanish Ministry of Science and Innovation under Project TEC2010-17816 (JUNTOS). The material in this paper was presented in part at the 2010 IEEE Information Theory Workshop.
PY - 2012/5
Y1 - 2012/5
N2 - The information-theoretic notion of energy efficiency is studied in the context of various joint source-channel coding problems. The minimum transmission energy E(D) required to communicate a source over a noisy channel so that it can be reconstructed within a target distortion D is analyzed. Unlike the traditional joint source-channel coding formalisms, no restrictions are imposed on the number of channel uses per source sample. For single-source memoryless point-to-point channels, E(D)is shown to be equal to the product of the minimum energy per bit {E bmin of the channel and the rate-distortion function R(D) of the source, regardless of whether channel output feedback is available at the transmitter. The primary focus is on Gaussian sources and channels affected by additive white Gaussian noise under quadratic distortion criteria, with or without perfect channel output feedback. In particular, for two correlated Gaussian sources communicated over a Gaussian multiple-access channel, inner and outer bounds on the energy-distortion region are obtained, which coincide in special cases. For symmetric channels, the difference between the upper and lower bounds on energy is shown to be at most a constant even when the lower bound goes to infinity as D to 0. It is also shown that simple uncoded transmission schemes perform better than the separation-based schemes in many different regimes, both with and without feedback.
AB - The information-theoretic notion of energy efficiency is studied in the context of various joint source-channel coding problems. The minimum transmission energy E(D) required to communicate a source over a noisy channel so that it can be reconstructed within a target distortion D is analyzed. Unlike the traditional joint source-channel coding formalisms, no restrictions are imposed on the number of channel uses per source sample. For single-source memoryless point-to-point channels, E(D)is shown to be equal to the product of the minimum energy per bit {E bmin of the channel and the rate-distortion function R(D) of the source, regardless of whether channel output feedback is available at the transmitter. The primary focus is on Gaussian sources and channels affected by additive white Gaussian noise under quadratic distortion criteria, with or without perfect channel output feedback. In particular, for two correlated Gaussian sources communicated over a Gaussian multiple-access channel, inner and outer bounds on the energy-distortion region are obtained, which coincide in special cases. For symmetric channels, the difference between the upper and lower bounds on energy is shown to be at most a constant even when the lower bound goes to infinity as D to 0. It is also shown that simple uncoded transmission schemes perform better than the separation-based schemes in many different regimes, both with and without feedback.
KW - Energy efficiency
KW - feedback
KW - information theory
KW - joint source-channel coding
KW - multiple-access channel (MAC)
KW - separate source and channel coding
KW - uncoded transmission
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U2 - 10.1109/TIT.2012.2184912
DO - 10.1109/TIT.2012.2184912
M3 - Article
AN - SCOPUS:84860244893
SN - 0018-9448
VL - 58
SP - 3153
EP - 3168
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 5
M1 - 6142075
ER -