arXiv subjects

Huseyin A. Inan

Publications and source records attributed to Huseyin A. Inan.

21 records · Page 2Linked to original sources

arXiv2016

Capacity of the Energy Harvesting Gaussian MAC

We consider an energy harvesting multiple access channel (MAC) where the transmitters are powered by an exogenous stochastic energy harvesting process and equipped with finite batteries. We characterize the capacity region of this channel as n-letter mutual information rate and develop inner and outer bounds that differ by a constant gap. An interesting conclusion that emerges from our results is that the sum-capacity approaches that of a standard AWGN MAC (with only an average constraint on the transmitted power), as the number of users in the MAC becomes large.

cs.IT↗

arXiv2012

Robust Estimation in Rayleigh Fading Channels Under Bounded Channel Uncertainties

We investigate channel equalization for Rayleigh fading channels under bounded channel uncertainties. We analyze three robust methods to estimate an unknown signal transmitted through a Rayleigh fading channel, where we avoid directly tuning the equalizer parameters to the available inaccurate channel information. These methods are based on minimizing certain mean-square error criteria that incorporate the channel uncertainties into the problem formulations. We present closed-form solutions to the channel equalization problems for each method and for both zero mean and nonzero mean signals. We illustrate the performances of the equalization methods through simulations.

cs.IT↗

arXiv2012

Adaptive Mixture Methods Based on Bregman Divergences

We investigate adaptive mixture methods that linearly combine outputs of $m$ constituent filters running in parallel to model a desired signal. We use "Bregman divergences" and obtain certain multiplicative updates to train the linear combination weights under an affine constraint or without any constraints. We use unnormalized relative entropy and relative entropy to define two different Bregman divergences that produce an unnormalized exponentiated gradient update and a normalized exponentiated gradient update on the mixture weights, respectively. We then carry out the mean and the mean-square transient analysis of these adaptive algorithms when they are used to combine outputs of $m$ constituent filters. We illustrate the accuracy of our results and demonstrate the effectiveness of these updates for sparse mixture systems.

cs.LG↗