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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose...
We address the inter-cell interference coordination for the indoor multi-color visible light communication (VLC) network under lighting constraints. In the multi-color VLC system, soft frequency reuse-based interference coordination is adopted, which adjusts the AC powers of the cell-edge components and the cell-center components. To further improve the system throughput in the environment of dense...
Consider the optical wireless scattering communication with a photomultiplier tube (PMT) receiver utilizing finite small intervals for measuring the PMT outputs. The analog output signal for each symbol consists of a vector of the signals within the intervals. We propose the signal model for the non-ideal photon-counting receiver with a preset threshold for the hard decision on whether a photoelectron...
This paper studies the achievable rate of a relay-assisted optical wireless communication channel, and presents a novel discrete signaling method by our proposed symbol-number filling algorithm. Unlike the radio frequency counterpart, the signaling is designed subject to nonnegative, peak and average power constraints, taking the input-dependent Gaussian shot noise into account. Decode and forward...
Impulsive noise in power lines usually bears higher power spectral density than the background noise. Even a sample of such noise, if not mitigated, destroys symbols in all the subcarriers affecting channel estimation and information detection. In this paper, we study two maximum-likelihood approaches to estimate the channel in the presence of impulsive noise for an OFDM based PLC system. In both...
The Gamma-Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverbation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is intimately...
The highest energy photons in the universe come from jets of relativistic plasma powered by supermassive black holes. Our ability to study these jets is severely limited by a poor angular resolution of gamma-ray telescopes. However, the deep gravitational potentials surrounding galaxies act as natural ‘gravitational’ lenses. These gravitational lenses split background sources into multiple images,...
We present a framework for optimal Bayesian feature selection and missing value estimation. Based on this framework, we derive optimal algorithms under an independent Gaussian model, and provide fast sub-optimal methods with superb performance for a dependent Gaussian model.
This paper provides a detailed comparison study between three different vehicles' Bluetooth built-in noise cancellation filter with two widely used techniques in speech enhancement, Spectral Subtraction (SS) and Wiener filtering (WF). The main purpose is to determine if any of these two filters provide superior audio quality over the built-in filter. In literature, several authors have compared the...
In this work, we are interested in assessing the optimality of the human auditory system, when the input stimuli is natural speech that is affected by additive noise. In order to do this, we consider the DANTALE II listening test paradigm of Wagener et al., which has been used to evaluate the intelligibility of noisy speech by exposing human listeners to a selection of constructed noisy sentences...
K-nearest neighbor (k-NN) classifier can learn non-linear decision surface and requires only one hyperparameter (i.e. value of “k”) for training. The classification accuracy improves as we increase the amount of training data. With an increase in the amount of training data, computational and memory requirements also increases as it has to store and search through the entire training data for classification...
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