Electronic transport properties of a tilted graphene pn junction

Spatial manipulation of current flow in graphene could be achieved through the use of a tilted pn junction. We show through numerical simulation that a pseudo-Hall effect (i.e. non-equilibrium charge and current density accumulating along one of the sides of a graphene ribbon) can be observed under these conditions. The tilt angle and the pn transition length are two key parameters in tuning the strength of this effect. This phenomenon can be explained using classical trajectory via ray analysis, and is therefore relatively robust against disorder. Lastly, we propose and simulate a three terminal device that allows direct experimental access to the proposed effect.Comment: 7 pages, 7 figure

Spectral Efficiency Improvements in HetNets by Exploiting Device-to-Device Communications

Next generation cellular networks require huge capacity, ubiquitous coverage and maximum energy efficiency. In order to meet these targets, Device-to-device (D2D) communication is being considered for future heterogeneous networks (HetNets). In this paper, we consider a three tier hierarchical HetNet by exploiting D2D communication in traditional HetNet. D2D communication is deployed within the HetNet where closely located mobile users are engaged in direct communication without routing the traffic through cellular access network. The proposed configuration mandates to reduce the interference offered by the resultant HetNet by reducing the transmitter-receiver distance and ensuring that the mobile users are transmitting with adaptive power subject to maintaining their desired link quality. In this context, we analyzed and compared the spectral efficiency improvements in hierarchical HetNet against traditional HetNet. Simulation results show that D2D communication offers much higher spectral efficiency as compared to traditional HetNet

16-06 Vehicle-to-Device (V2D) Communications: Readiness of the Technology and Potential Applications for People with Disability

IEEE 802.11p was developed as an amendment to IEEE 802.11 for wireless access in vehicular environments (WAVE). While WAVE is considered the de facto standard for V2V communications, in the past few years a number of communications technologies have emerged that enable direct device-to-device (D2D) communications. Technologies like Bluetooth Smart, WiFi-Direct and LTE-Direct allow devices to communicate directly without having to rely on existing communications infrastructure (e.g., base stations). More importantly, these technologies are quickly penetrating the smartphones market. The goal of this research is to conduct extensive simulation and experimental studies to assess the efficacies of utilizing D2D communications technologies in transportation scenarios focused around pedestrians and bicyclists. Specifically, we design, develop, and experiment with Smart Cone and Smart Cane systems to evaluate the readiness of D2D technologies to support transportation applications

Agent-based simulations for coverage extensions in 5G networks and beyond

Device-to-device (D2D) communications is one of the key emerging technologies for the fifth generation (5G) networks and beyond. It enables direct communication between mobile users and thereby extends coverage for devices lacking direct access to the cellular infrastructure and hence enhances network capacity. D2D networks are complex, highly dynamic and will be strongly augmented by intelligence for decision making at both the edge and core of the network, which makes them particularly difficult to predict and analyze. Conventionally, D2D systems are evaluated, investigated and analyzed using analytical and probabilistic models (e.g., from stochastic geometry). However, applying classical simulation and analytical tools to such a complex system is often hard to track and inaccurate. In this paper, we present a modeling and simulation framework from the perspective of complex-systems science and exhibit an agent-based model for the simulation of D2D coverage extensions. We also present a theoretical study to benchmark our proposed approach for a basic scenario that is less complicated to model mathematically. Our simulation results show that we are indeed able to predict coverage extensions for multi-hop scenarios and quantify the effects of street-system characteristics and pedestrian mobility on the connection time of devices to the base station (BS). To our knowledge, this is the first study that applies agent-based simulations for coverage extensions in D2D

Algorithms for Near-Term and Noisy Quantum Devices

Quantum computing promises to revolutionise many fields, including chemical simulations and machine learning. At the present moment those promises have not been realised, due to the large resource requirements of fault tolerant quantum computers, not excepting the scientific and engineering challenges to building a fault tolerant quantum computer. Instead, we currently have access to quantum devices that are both limited in qubit number, and have noisy qubits. This thesis deals with the challenges that these devices present, by investigating applications in quantum simulation for molecules and solid state systems, quantum machine learning, and by presenting a detailed simulation of a real ion trap device. We firstly build on a previous algorithm for state discrimination using a quantum machine learning model, and we show how to adapt the algorithm to work on a noisy device. This algorithm outperforms the analytical best POVM if ran on a noisy device. We then discuss how to build a quantum perceptron - the building block of a quantum neural network. We also present an algorithm for simulating the Dynamical Mean Field Theory (DMFT) using a quantum device, for two sites. We also discuss some of the difficul- ties found in scaling up that system, and present an algorithm for building the DMFT ansatz using the quantum device. We also discuss modifications to the algorithm that make it more ‘device-aware’. Finally we present a pule-level simulation of the noise in an ion trap device, designed to match the specifications of a device at the National Physical Laboratory (NPL), which we can use to direct future experimental focus. Each of these sections is preceded by a review of the relevant literature

A Hybrid Model to Extend Vehicular Intercommunication V2V through D2D Architecture

In the recent years, many solutions for Vehicle to Vehicle (V2V) communication were proposed to overcome failure problems (also known as dead ends). This paper proposes a novel framework for V2V failure recovery using Device-to-Device (D2D) communications. Based on the unified Intelligent Transportation Systems (ITS) architecture, LTE-based D2D mechanisms can improve V2V dead ends failure recovery delays. This new paradigm of hybrid V2V-D2D communications overcomes the limitations of traditional V2V routing techniques. According to NS2 simulation results, the proposed hybrid model decreases the end to end delay (E2E) of messages delivery. A complete comparison of different D2D use cases (best & worst scenarios) is presented to show the enhancements brought by our solution compared to traditional V2V techniques.Comment: 6 page

Architecture and Implementation of a Trust Model for Pervasive Applications

Collaborative effort to share resources is a significant feature of pervasive computing environments. To achieve secure service discovery and sharing, and to distinguish between malevolent and benevolent entities, trust models must be defined. It is critical to estimate a device\u27s initial trust value because of the transient nature of pervasive smart space; however, most of the prior research work on trust models for pervasive applications used the notion of constant initial trust assignment. In this paper, we design and implement a trust model called DIRT. We categorize services in different security levels and depending on the service requester\u27s context information, we calculate the initial trust value. Our trust value is assigned for each device and for each service. Our overall trust estimation for a service depends on the recommendations of the neighbouring devices, inference from other service-trust values for that device, and direct trust experience. We provide an extensive survey of related work, and we demonstrate the distinguishing features of our proposed model with respect to the existing models. We implement a healthcare-monitoring application and a location-based service prototype over DIRT. We also provide a performance analysis of the model with respect to some of its important characteristics tested in various scenarios