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Energy Efficient SCMA Supported Downlink Cloud-RANs for 5G Networks
(IEEE, 2020)
Cloud-radio access networks (C-RANs) are regarded as a promising solution to provide low cost services among users through the centralized coordination of baseband units for 5G wireless networks. The coordinated multi-point ...
Optical spatial modulation design
(Royal Soc, 2020)
Visible light communication (VLC) systems are inherently signal-to-noise ratio (SNR) limited due to link budget constraints. One favourable method to overcome this limitation is to focus on the pre-log factors of the channel ...
Metastable reverse-phase droplets within ordered phases: Renormalization-group calculation of field and temperature dependence of limiting size
(AMER PHYSICAL SOC, 2020)
Metastable reverse-phase droplets are calculated by renormalization-group theory by evaluating the magnetization of a droplet under magnetic field, matching the boundary condition with the reverse phase and noting whether ...
Minimum Length Scheduling for Full Duplex Time-Critical Wireless Powered Communication Networks
(IEEE, 2020)
Radio frequency (RF) energy harvesting is key in attaining perpetual lifetime for time-critical wireless powered communication networks (WPCNs) due to full control on energy transfer, far field region, small and low-cost ...
Optimal On-Off Transmission Schemes for Full Duplex Wireless Powered Communication Networks
(IEEE, 2020)
In this paper, we consider a full duplex wireless powered communication network where multiple users with radio frequency energy harvesting capability communicate to an energy broadcasting hybrid access point. We investigate ...
Frustrated Potts model: Multiplicity eliminates chaos via reentrance
(Amer Physical Soc, 2020)
The frustrated q-state Potts model is solved exactly on a hierarchical lattice, yielding chaos under rescaling, namely, the signature of a spin-glass phase, as previously seen for the Ising (q = 2) model. However, the ...
A Hybrid Deep Learning Framework for Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data
(Mdpi, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
Throughput maximization in discrete rate based full duplex wireless powered communication networks
(John Wıley & Sons Ltd, 2020)
In this study, we consider a discrete rate full-duplex wireless powered communication network. We characterize a novel optimization framework for sum throughput maximization to determine the rate adaptation and transmission ...
Across dimensions: Two- and three-dimensional phase transitions from the iterative renormalization-group theory of chains
(2020)
Sharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...