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Converse Bounds on Modulation-Estimation Performance for the Gaussian Multiple-Access Channel.

Authors :
Unsal, Ayse
Knopp, Raymond
Merhav, Neri
Source :
IEEE Transactions on Information Theory; Feb2018, Vol. 64 Issue 2, p1217-1230, 14p
Publication Year :
2018

Abstract

This paper focuses on the problem of separately modulating and jointly estimating two independent continuous-valued parameters sent over a Gaussian multiple-access channel (MAC) under the mean square error (MSE) criterion without bandwidth constraints. To this end, we first improve an existing lower bound on the MSE that is obtained using the parameter modulation-estimation techniques for the single-user additive white Gaussian noise (AWGN) channel. As for the main contribution of this paper, this improved modulation-estimation analysis is generalized to the model of the two-user Gaussian MAC. We present outer bounds to the achievable region in the plane of the MSE’s of the two user parameters, which provides a trade-off between the MSE’s, where we used zero-rate lower bounds on the error probability of Gaussian channels by Shannon and Polyanskiy et al. Numerical results showed that, the multi-user adaptation of the zero-rate lower bound by Polyanskiy et al. provides a tighter overall lower bound on the MSE pairs than the classical Shannon bound. In addition, we introduced upper bounds on the MSE exponents, namely, the exponential decay rates of these MSE’s in the asymptotic regime of long blocks that could make use of any bound on the error exponent of a single-user AWGN channel. The obtained results are numerically evaluated for three different bounds on the reliability function of the Gaussian channel. It is shown that the adaptation of the reliability function by Ashikhmin et al. to the MAC provides a significantly tighter characterization than Shannon’s sphere-packing bound and the divergence bound. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
64
Issue :
2
Database :
Complementary Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
127408998
Full Text :
https://doi.org/10.1109/TIT.2017.2779837