Information Processing and Wireless Energy Harvesting in Interference-Aware Public Safety Networks

In a public safety environment, user equipments (UEs) located within the coverage area of evolved NodeB, relay network services to out-of-coverage UEs. However, relay UEs in public safety environments are typically energy constrained and cannot operate indefinitely without recharging. Radio frequency energy harvesting has been proposed as a solution for recharging wireless UEs. In this paper, we propose a scheme for extending the lifetime of a public safety network by wirelessly charging relay UEs. In addition, we propose a relay selection method considering the battery status of relay UEs. The proposed relay selection is defined as a bipartite graph matching problem and the optimal relay is obtained through matching games technique. The proposed scheme not only improves the network lifetime but also extend the network coverage. We also conduct system level simulations to evaluate the performance of the proposed scheme. Simulation results show that the overall performance of the system is improved in terms of achievable throughput and network lifetime.     

Rainfall propagation impairments for medium elevation angle satellite‐to‐earth 12 GHz in the tropics

Rain attenuation is the dominant propagation impairment for satellite communication systems operating at frequencies above about 10 GHz. The rainfall path attenuation at 12.255 GHz measured at Universiti Sains Malaysia (USM) for 4 years (2 January to 5 December) is presented. This paper presents an empirical analysis of rain rate and rain attenuation cumulative distribution functions obtained using 1‐min integrated rainfall data and comparison of the measured data with data obtained from well‐established rain model attenuation predictions. Copyright © 2008 John Wiley & Sons, Ltd.     

Improving vehicular safety message delivery through the implementation of a cognitive vehicular network

The Wireless Access in Vehicular Environments (WAVE) protocol stack has been recently defined to enable vehicular communication on the Dedicated Short Range Communication (DSRC) frequencies. Some recent studies have demonstrated that the WAVE technology might not provide sufficient spectrum for reliable exchange of safety information over congested urban scenarios. In this paper, we address this issue, and present a novel cognitive network architecture in order to dynamically extend the Control Channel (CCH) used by vehicles to transmit safety-related information. To this aim, we propose a cooperative spectrum sensing scheme, through which vehicles can detect available spectrum resources on the 5.8 GHz ISM band along their path, and forward the data to a fixed infrastructure known as Road Side Units (RSUs). We design a novel Fuzzy-Logic based spectrum allocation algorithm, through which the RSUs infer the actual CCH contention conditions, and dynamically extend the CCH bandwidth in network congestion scenarios, by using the vacant frequencies detected by the sensing module. The simulation results reveal the effectiveness of our architecture in providing dynamic and scalable allocation of spectrum resources, and in increasing the performance of safety-related applications.     

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs.     

A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network

Recently, Underwater Wireless Sensor Networks (UWSNs) has witnessed significant attention from both academia and industries in research and development, due to the growing number of applications for wide range of purposes including commercial, scientific, environmental and military. Some of the major applications include pollution monitoring, tactical surveillance, tsunami warnings and offshore exploration. Efficient communication among sensors in UWSNs is a challenging task due to the harsh environments and peculiar characteristics of UWSNs. Therefore, design of routing protocol for efficient communication among sensors and sink is one of the fundamental research themes in UWSNs. In this context, this paper proposes a location-free Reliable and Energy efficient Pressure-Based Routing (RE-PBR) protocol for UWSNs. RE-PBR considers three parameters including link quality, depth and residual energy for balancing energy consumption and reliable data delivery. Specifically, link quality is estimated using triangle metric method. A light weight information acquisition algorithm is developed for efficient knowledge discovery of the network. Multi-metric data forwarding algorithm is designed based on route cost calculation which utilizes residual energy and link quality. Simulations are carried out in NS-2 with Aqua-Sim package to evaluate the performance of RE-PBR. The performance of the proposed protocol is compared with the stat-of-the-art techniques: DBR and EEDBR. The comprehensive performance evaluation attests the benefit of RE-PBR as compared to the state-of-the-art techniques in terms of network lifetime, energy consumption, end-to-end delay and packet delivery ratio.     

MDP-Based Network Selection Scheme by Genetic Algorithm and Simulated Annealing for Vertical-Handover in Heterogeneous Wireless Networks

The hybrid algorithm for real-time vertical handover using different objective functions has been presented to find the optimal network to connect with a good quality of service in accordance with the user’s preferences. Markov processes are widely used in performance modelling of wireless and mobile communication systems. We address the problem of optimal wireless network selection during vertical handover, based on the received information, by embedding the decision problem in a Markov decision process (MDP) with genetic algorithm (GA), we use GA to find a set of optimal decisions that ensures the best trade-off between QoS based on their priority level. Then, we emerge improved genetic algorithm (IGA) with simulated annealing (SA) as leading methods for search and optimization problems in heterogeneous wireless networks. We formulate the vertical handoff decision problem as a MDP, with the objectives of maximizing the expected total reward and minimizing average number of handoffs. A reward function is constructed to assess the QoS during each connection, and the AHP method are applied in an iterative way, by which we can work out a stationary deterministic handoff decision policy. As it is, the characteristics of the current mobile devices recommend using fast and efficient algorithms to provide solutions near to real-time. These constraints have moved us to develop intelligent algorithm that avoid the slow and massive computations. This paper compares the formulation and results of five recent optimization algorithms: artificial bee colony, GA, differential evolution, particle swarm optimization and hybrid of (GA–SA). Simulation results indicated that choosing the SA rules would minimize the cost function, and also that, the IGA–SA algorithm could decrease the number of unnecessary handovers, and thereby prevent the ‘Ping-Pong’ effect.     

Magneto‐Thermal Metrics Can Mirror the Long‐Term Intracellular Fate of Magneto‐Plasmonic Nanohybrids and Reveal the Remarkable Shielding Effect of Gold

Multifunctional nanoparticles such as magneto‐plasmonic nanohybrids are rising theranostic agents. However, little is yet known of their fate within the cellular environment. In order to reach an understanding of their biotransformations, reliable metrics for tracking and quantification of such materials properties during their intracellular journey are needed. In this study, their long‐term (one month) intracellular fate is followed within stem‐cell spheroids used as tissue replicas. A set of magnetic (magnetization) and thermal (magnetic hyperthermia, photothermia) metrics is implemented to provide reliable insightsinto the intracellular status. It shows that biodegradation is modulated by the morphology and thickness of the gold shell. First a massive dissolution of the iron oxide core (nanoflower‐like) is observed, starting with dissociation of the multigrain structure. Second, it is demonstrated that an uninterrupted gold shell can preserve the magnetic core and properties (particularly magnetic hyperthermia). In addition to the magnetic and thermal metrics, intracellular high‐resolution chemical nanocartography evidences the gradual degradation of the magnetic cores. It also shows different transformation scenarios, from the release of small gold seeds when the magnetic core is dissolved (interesting for long‐term elimination) to the protection of the magnetic core (interesting for long‐term therapeutic applicability).     

A Novel Artificial Intelligence Based Timing Synchronization Scheme for Smart Grid Applications

The smart grid control applications necessitate real-time communication systems with time efficiency for real-time monitoring, measurement, and control. Time-efficient communication systems should have the ability to function in severe propagation conditions in smart grid applications. The data/packet communications need to be maintained by synchronized timing and reliability through equally considering the signal deterioration occurrences, which are propagation delay, phase errors and channel conditions. Phase synchronization plays a vital part in the digital smart grid to get precise and real-time control measurement information. IEEE C37.118 and IEC 61850 had implemented for the synchronization communication to measure as well as control the smart grid applications. Both IEEE C37.118 and IEC 61850 experienced a huge propagation and packet delays due to synchronization precision issues. Because of these delays and errors, measurement and monitoring of the smart grid application in real-time is not accurate. Therefore, it has been investigated that the time synchronization in real-time is a critical challenge in smart grid applications, and for this issue, other errors raised consequently. The existing communication systems are designed with the phasor measurement unit (PMU) along with communication protocol IEEE C37.118 and uses the GPS timestamps as the reference clock stamps. The absence of GPS increases the clock offsets, which surely can hamper the synchronization process and the full control measurement system that can be imprecise. Therefore, to reduce this clock offsets, a new algorithm is needed which may consider any alternative reference timestamps rather than GPS. The revolutionary Artificial Intelligence (AI) enables the industrial revolution to provide a significant performance to engineering solutions. Therefore, this article proposed the AI-based Synchronization scheme to mitigate smart grid timing issues. The backpropagation neural network is applied as the AI method that employs the timing estimations and error corrections for the precise performances. The novel AIFS scheme is considered the radio communication functionalities in order to connect the external timing server. The performance of the proposed AIFS scheme is evaluated using a MATLAB-based simulation approach. Simulation results show that the proposed scheme performs better than the existing system.

     

Efficient Photomodulation of Visible Eu(III) and Invisible Yb(III) Luminescences using DTE Photochromic Ligands for Optical Encryption

This work describes a class of complex combining three dithienylethene units and a lanthanide ion used as an optical system displaying a double encryption method: i) a colorful code, drawn and erased under UV and visible irradiations respectively, due to coloration and discoloration of the photochromic entities, and ii) a concomitant gradual disappearance and progressive restoration of the associated lanthanide ion luminescence triggered with the same stimuli. The innovation of the system stems from the emission color tunability, i.e., with either a lanthanide ion emitting only in the visible range (Eu³⁺) or with another lanthanide ion emitting only in the near infrared (NIR) range (Yb³⁺), therefore observable, or not, to the naked eye. This system is the very first one to achieve efficient repeatable modulation of pure NIR luminescence on photochemical command. Furthermore, it is proven to be highly efficient when embedded in a PDMS polymer opening real opportunities for practical applications as anti‐counterfeiting.     

Camera calibration using symmetric objects.

This paper proposes a novel method for camera calibration using images of a mirror symmetric object. Assuming unit aspect ratio and zero skew, we show that interimage homographies can be expressed as a function of only the principal point. By minimizing symmetric transfer errors, we thus obtain an accurate solution for the camera parameters. We also extend our approach to a calibration technique using images of a 1-D object with a fixed pivoting point. Unlike existing methods that rely on orthogonality or pole-polar relationship, our approach utilizes new inter-image constraints and does not require knowledge of the 3-D coordinates of feature points. To demonstrate the effectiveness of the approach, we present results for both synthetic and real images.