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Quantum states with equal unlockable correlations and quantum discord

In the context of quantum locking of classical correlations protocols, the condition for equality of the amount of unlockable correlations and quantum discord of general classical-quantum states is investigated.‎ Based on this condition, the structure of such general states is obtained.‎ This condition imposes two constraints on the structure of general classical-quantum states.‎ After presenting the interpretation of these constraints, their role in quantum locking protocols is discussed.‎

vSPACE: VNF Simultaneous Placement, Admission Control and Embedding

In future wireless networks, network functions virtualization lays the foundations for establishing a new dynamic resource management framework to efficiently utilize network resources.‎ In this paper, a network service can be viewed as a chain of virtual network functions (VNFs), called a service function chain (SFC), served via placement, admission control (AC), and embedding into network infrastructure, based on the resource management objectives and the state of network.‎

Antenna Allocation and Pricing inVirtualized Massive MIMO Networks via Stackelberg Game,

We study a resource allocation problem for the uplink of a virtualized massive multiple-input multiple-output system, where the antennas at the base station are priced and virtualized among the service providers (SPs).‎ The mobile network operator (MNO) who owns the infrastructure decides the price per antenna, and a Stackelberg game is formulated for the net profit maximization of the MNO, while the minimum rate requirements of SPs are satisfied.‎

Leveraging synergy of SDWN and multi-layer resource management for 5G networks,

Fifth-generation (5G) networks are envisioned to predispose flexible edge-to-core infrastructure to offer diverse applications.‎ Convergence of software-defined networking, software-defined radio, and virtualisation on the concept of software-defined wireless networking (SDWN) is a promising approach to support such dynamic networks.‎ The principal technique behind the 5G-SDWN framework is the separation of control and data planes that allows the abstraction of resources as transmission parameters of users.‎

Multi-Objective Resource Allocation in Density-Aware Design of C-RAN in 5G

In this paper, a multi-objective resource allocation algorithm in a novel density-aware design of virtualized software-defined cloud radio access network (C-RAN) is proposed.‎ We consider two design modes based on the average density of users: 1) high-density mode when a large number of low-cost remote radio heads (RRHs) without baseband processing capability are controlled by one single base station and 2) low-density mode when a small number of RRHs with baseband processing capability are deployed.‎

Increasing the Quality of Reconstructed Signal in Compressive Sensing Utilizing Kronecker Technique

Quality of reconstruction of signals sampled using compressive sensing (CS) algorithmdepends on the compression factor and the length of the measurement.A simple method to pre-process data before reconstruction of compressively sampled signals using Kroneckertechnique that  improves  thequality  of recovery  is  proposed.‎

A Hidden Markov Model Scheme for Lip Biometrics Authentication Based on Vertical Grooves Angles

As the lips move too quickly, the shape of lips images may differ from one situation to another for an individual such as the cases of smiling or frowning.‎ In this paper, we propose a novel approach to automatic classification of lips images which are captured by digital camera.‎ We focus on the lower part of lips based on morphological features of the grooves.‎ Image processing techniques are employed to replace the traditional lipprints to detect human identification with intelligent systems.‎

Scheduling Solution Decrease The Total Task Completion Time in Wireless Sensor Actor Network

In this paper, we present a scheduling model based on queuing theory to minimize the network make-span in wireless sensor and actor networks.‎ We compute the best rate of distribution of tasks by the network sink to allocated actors through a steady state analysis of our proposed model to solve equations and inequalities.‎ It is shown that this distribution rate can enhance the total residual energies of the actor nodes, too.‎

Big Data Based Self-Optimization Networking in Next Generation Mobile Networks

Using self-optimization techniques is the only viable solution for increasing the efficiency in next generation mobile networks.‎ The goal of proposing a self-optimization model is to maximize the network efficiency and increase the quality of services provided to microcell and femto-cell users, considering the limited resources in radio access networks.‎ To increase the model efficiency, we applied the big data technique for analyzing data and increasing the accuracy of the decision-making process.‎

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