Title :
Capacity-achieving distributions for non-Gaussian additive noise channels
Author_Institution :
Lucent Technol. Bell Labs., Holmdel, NJ, USA
Abstract :
We characterize the capacity-achieving distribution for a class of non-Gaussian additive noise channels, when the transmitter is subject to an “average” power constraint. Specifically, we show that if the probability density function of the noise, in addition to satisfying some mild technical conditions, has a tail which decays at a rate slower (resp. faster) than the Gaussian, then the capacity-achieving distribution has bounded (resp. unbounded) support
Keywords :
channel capacity; discrete time systems; probability; statistical analysis; average power constraint; bounded support; capacity-achieving distributions; discrete-time channel; nonGaussian additive noise channels; probability density function; transmitter; unbounded support; Additive noise; Density functional theory; Density measurement; Entropy; Gaussian noise; Hydrogen; Noise measurement; Tail; Transmitters; Yttrium;
Conference_Titel :
Information Theory, 2000. Proceedings. IEEE International Symposium on
Conference_Location :
Sorrento
Print_ISBN :
0-7803-5857-0
DOI :
10.1109/ISIT.2000.866730