DocumentCode :
179652
Title :
On the accuracy of the high SNR approximation of the differential entropy of signals in additive Gaussian noise
Author :
Gohary, Ramy ; Yanikomeroglu, Halim
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
5735
Lastpage :
5738
Abstract :
One approach for analyzing the high signal-to-noise ratio (SNR) capacity of non-coherent wireless communication systems is to ignore the noise component of the received signal in the computation of its differential entropy. In this paper we consider the error incurred by this approximation when the transmitter and the receiver have one antenna each, and the noise has a Gaussian distribution. For a general instance of this case, we show that the approximation error decays as 1/SNR. In addition, we consider the special instance in which the received signal corresponds to a signal transmitted over a channel with additive Gaussian noise and a Gaussian fading coefficient. For that case, we provide an explicit expression for the second order term of the Taylor series expansion of the differential entropy. To circumvent the difficulty that arises in the direct computation of that term, we invoke Schwartz´s inequality to obtain an efficiently computable bound on it, and we provide examples that illustrate the utility of this bound.
Keywords :
Gaussian channels; Gaussian distribution; Gaussian noise; antennas; approximation theory; entropy; fading channels; radio networks; radio receivers; radio transmitters; series (mathematics); Gaussian distribution; Gaussian fading coefficient; Schwartz inequality; Taylor series expansion; additive Gaussian noise; antenna; differential signal entropy; high SNR approximation; noncoherent wireless communication system; radio receiver; radio transmitter; signal-to-noise ratio; Approximation methods; Entropy; Random variables; Signal to noise ratio; Taylor series; Upper bound; High-SNR non-coherent capacity; Lebesgue dominated convergence; differential entropy; sum and product of random variables;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6854702
Filename :
6854702
Link To Document :
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