Efficient and practical resource block allocation for LTE-based D2D network via graph coloring

In this paper, we construct a practical framework for efficiently allocating long term evolution (LTE) resource blocks (RB) among the users in a device-to-device (D2D) network. For such network that presumably operates under the LTE cellular network, our aim is to improve the overall throughput of D2D connections using opportunistic or fairness-based approach. Taking the practical considerations into account, our proposed framework allows a number of connections to share a single RB whenever possible, thus utilizing the radio resources. To do so, our solution first identifies a superior set of the interference-free D2D reuse groups via graph modeling and graph coloring approach. In particular, we model a D2D network with a two-overlapping disk graph for which a suitable coloring algorithm is proposed and its performance bound is calculated. Once the reuse groups are known, our solution optimizes the RB allocation among these groups based on their reported channel condition as well as the scheduling criterion, whether it is fairness-based or opportunistic. Through numerical experiments, we show that our solution can significantly improve the throughput performance of a D2D network.     

Heteroatom Effect on Star‐Shaped Hole‐Transporting Materials for Perovskite Solar Cells

Three new star‐shaped hole‐transporting materials (HTMs) incorporating benzotripyrrole, benzotrifuran, and benzotriselenophene central cores endowed with three‐armed triphenylamine moieties ( BTP‐1 , BTF‐1 , and BTSe‐1 , respectively) are designed, synthesized, and implemented in perovskite solar cells (PSCs). The impact that the heteroatom‐containing central scaffold has on the electrochemical and photophysical properties, as well as on the photovoltaic performance, is systematically investigated and compared with their sulfur‐rich analogue ( BTT‐3 ). The new HTMs exhibit suitable highest‐occupied molecular orbitals (HOMO) levels regarding the valence band of the perovskite, which ensure efficient hole extraction at the perovskite/HTM interface. The molecular structures of BTF‐1 , BTT‐3 , and BTSe‐1 are fully elucidated by single‐crystal X‐ray crystallography as toluene solvates. The optimized (FAPbI₃)_0.85(MAPbBr₃)_0.15‐based perovskite solar cells employing the tailor‐made, chalcogenide‐based HTMs exhibit remarkable power conversion efficiencies up to 18.5%, which are comparable to the devices based on the benchmark spiro‐OMeTAD. PSCs with BTP‐1 exhibit a more limited power conversion efficiency of 15.5%, with noticeable hysteresis. This systematic study indicates that chalcogenide‐based derivatives are promising HTM candidates to compete efficiently with spiro‐OMeTAD.     

New methods for enhancing fine acquisition in dual folding algorithm of long pseudo noise codes

Long code Direct Sequence Spread Spectrum is a good choice for applications where security and antispoofing ability of a spread spectrum connection is concerned. Due to long period of spreading code, acquisition is a challenge for these systems because a trade‐off between detection probability and acquisition time must be made. For confronting this challenge, various algorithms were proposed in the literature but almost all of them focus on expediting the coarse acquisition. In this paper, we consider the efficient dual folding algorithm for coarse acquisition level and propose 3 methods for enhancing the fine acquisition level leading to faster execution of overall acquisition algorithm. The methods are based on estimations from coarse acquisition level that are not used in conventional algorithms for fine acquisition, ie, zero padding. Theoretical expressions of 2 main comparison criteria in acquisition algorithms, ie, detection probability and mean acquisition time, are derived for conventional zero padding and each of the proposed method. Besides, a coarse estimate of resource consumption is provided by the number of floating point operations for each algorithm to make a useful comparison. Considering these 3 parameters, in comparison, the proposed methods surpass zero padding in 1, 2, or all of the 3 aspects. Simulation agrees well with analytical results.     

Channel estimation based on learning automata for OFDM systems

The abundant benefits of Orthogonal Frequency‐Division Multiplexing and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system's efficiency is the accurate estimation of channel state information. In the literatures, many techniques have been studied in order to estimate the channel state information. Nowadays, the techniques based on intelligent algorithms such as genetic algorithm and particle swarm optimization (PSO) have attracted attention of researchers. With a very low pilot overhead, these techniques are able to estimate the channel frequency response properly only using the received signals. Unfortunately, each of these techniques suffers a common weakness: they have a slow convergence rate. In this paper, a new intelligent and different method has been presented for channel estimation using learning automata, entitled LA estimator, where the learning automata are search agents, and each pair is responsible for searching 1 complex coefficient of the channel frequency response. This method can achieve an accurate channel estimation with a moderate computational complexity in comparison with GA and PSO estimators. Furthermore, with higher convergence rate, our proposed method is capable of providing the same performance as GA and PSO. For a 2‐path fast fading channel, simulation results demonstrate the robustness of our proposed scheme according to the bit error rate and the mean square error.     

Dependability analysis for characterizing Google cluster reliability

Cloud solutions are emerging as a new suitable way of transforming traditional IT data centers to highly available and reliable computing resources for hosting critical applications and data. However, software and hardware failures are a common problem in cloud datacenters that can lead to harmful damages. In this paper, we analyze the physical server failures in the Google cloud datacenter. We study the Google cluster properties to investigate the relationship among physical servers' failure rate and jobs failure events. The failure rate of Google cluster executed jobs and servers is taken into consideration during a 29‐day period. We present a reliability model for Google cluster physical machines using the continuous time Markov chains according to this observation. We attempt to analyze the obtained model through SHARPE software packages to improve the understanding of failure events in the Google cloud cluster. We also explore the cluster availability based on parameters like steady‐state availability, steady‐state unavailability, mean time to failure, and mean time to repair in the Google cluster.     

Low-Power Symmetrical Rectifier for Passive UHF RFID Transponder

Rectifier design is one of the challenging issues in passive radio-frequency identification (RFID) systems. Differential structures are good candidates as rectifiers to their high conversion efficiencies. In this paper, a novel structure is proposed to produce symmetrical power-supply utilizing differential circuit configuration simulated in 130nm CMOS technology. The proposed rectifier can provide 1.34 V DC power with 382% voltage conversion efficiency, thus demonstrated its higher performance over existing designs.     

An Intra-domain Mobility Handling Scheme Across All-IP Wireless Networks

The rapid growth of wireless network technology such as HSDPA and WiMAX, has lead to greater demand for access to Internet via mobile hosts. Supporting mobile connection with fast and smooth roaming across heterogeneous wireless technologies has been an important challenge over past years. In this paper, a novel multilayer scheme for QoS-aware intra-domain mobility management is proposed. The mobility support capability is embedded in key components for the domain access network, namely, the Paging Access Routers and the Mobility-support Anchor Servers (MASs). The MASs are organized in three layers; starting from the top layer Superior-MASs, Middle-MASs and Inferior-MASs, respectively. The proposed scheme identified mobility support functionality, includes intra-domain anchor specification, route optimization algorithm, intra/inter-anchor mobility support, paging and authentication management. Simulation results of the proposed scheme show fair performance especially in the presence of QoS sensitive services.     

Deposition and characterization of molybdenum thin films using dc-plasma magnetron sputtering

Molebdenum (Mo) thin films were deposited on well-cleaned soda-lime glass substrates using DC-plasma magnetron sputtering. In the design of experiment deposition was optimized for maximum beneficial characteristics by monitoring effect of process variables such as deposition power (100–200 W). Their electrical, structural and morphological properties were analyzed to study the effect of these variables. The electrical resistivity of Mo thin films could be reduced by increasing deposition power. Within the range of analyzed deposition power, Mo thin films showed a mono crystalline nature and the crystallites were found to have an orientation along [110] direction. The surface morphology of thin films showed that a highly dense micro structure has been obtained. The surface roughness of films increased with deposition power. The adhesion of Mo thin films could be improved by increasing the deposition power. Atomic force microscopy was used for the topographical study of the films and to determine the roughness of the films. X-ray diffractrometer and scanning electron microscopy analysis were used to investigate the crystallinity and surface morphology of the films. Hall effect measurement system was used to find resistivity, carrier mobility and carrier density of deposited films. The adhesion test was performed using scotch hatch tape adhesion test. Mo thin films prepared at deposition power of 200 W, substrate temperature of 23°C and Ar pressure of 0.0123 mbar exhibited a mono crystalline structure with an orientation along (110) direction, thickness of ～550 nm and electrical resistivity value of 0.57 × 10^?4 Ω cm.     

Achieving Outstanding Mechanical Performance in Reinforced Elastomeric Composite Fibers Using Large Sheets of Graphene Oxide

A simple fiber spinning method used to fabricate elastomeric composite fibers with outstanding mechanical performance is demonstrated. By taking advantage of the large size of as‐prepared graphene oxide sheets (in the order of tens of micrometers) and their liquid crystalline behavior, elastomeric composite fibers with outstanding low strain properties have been fabricated without compromising their high strain properties. For example, the modulus and yield stress of the parent elastomer improved by 80‐ and 40‐fold, respectively, while maintaining the high extensibility of ～400% strain inherent to the parent elastomer. This outstanding mechanical performance was shown to be dependent upon the GO sheet size. Insights into how both the GO sheet size dimension and dispersion parameters influence the mechanical behavior at various applied strains are discussed.     

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.