Title :
Nearest neighbor decoding for additive non-Gaussian noise channels
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., MIT, Cambridge, MA, USA
fDate :
9/1/1996 12:00:00 AM
Abstract :
We study the performance of a transmission scheme employing random Gaussian codebooks and nearest neighbor decoding over a power limited additive non-Gaussian noise channel. We show that the achievable rates depend on the noise distribution only via its power and thus coincide with the capacity region of a white Gaussian noise channel with signal and noise power equal to those of the original channel. The results are presented for single-user channels as well as multiple-access channels, and are extended to fading channels with side information at the receiver
Keywords :
decoding; fading; random processes; telecommunication channels; white noise; Euclidean distance; additive nonGaussian noise channels; capacity region; fading channels; generalized cutoff rate; mismatched decoding; multiple-access channels; nearest neighbor decoding; noise distribution; performance; random Gaussian codebooks; side information; single-user channels; transmission scheme; white Gaussian noise channel; Additive noise; Decision trees; Decoding; Euclidean distance; Fading; Gaussian noise; Information theory; Nearest neighbor searches; Redundancy; Stochastic processes;
Journal_Title :
Information Theory, IEEE Transactions on