Higher-Order Asymptotics of Mutual Information for Nonlinear Channels with Non-Gaussian Noise
Problems of Information Transmission
Multiplexing two information sources over fading channels: a cross-layer design perspective
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Foundations and Trends® in Networking
Capacity of a single spiking neuron channel
Neural Computation
Mutual information of multipath channels with imperfect channel information
IEEE Transactions on Communications
Design criterion and construction methods for partially coherent multiple antenna constellations
IEEE Transactions on Wireless Communications
On the capacity and energy efficiency of training-based transmissions over fading channels
IEEE Transactions on Information Theory
Optimal constellations for the low-SNR noncoherent MIMO block Rayleigh-fading channel
IEEE Transactions on Information Theory
The fading number of multiple-input multiple-output fading channels with memory
IEEE Transactions on Information Theory
On the sensitivity of noncoherent capacity to the channel model
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Error rate analysis for peaky signaling over fading channels
IEEE Transactions on Communications
Capacity of optical intensity channels with peak and average power constraints
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Noncoherent capacity of underspread fading channels
IEEE Transactions on Information Theory
Problems of Information Transmission
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We consider transmission over a discrete-time Rayleigh fading channel, in which successive symbols face independent fading, and where neither the transmitter nor the receiver has channel state information. Subject to an average power constraint, we study the capacity-achieving distribution of this channel and prove it to be discrete with a finite number of mass points, one of them located at the origin. We numerically compute the capacity and the corresponding optimal distribution as a function of the signal-to-noise ratio (SNR). The behavior of the channel at low SNR is studied and finally a comparison is drawn with the ideal additive white Gaussian noise channel