High efficiency,high switching speed,AlGaAs/GaAs P-HEMT DC–DC converter for integrated power amplifier modules

This paper presents a high efficiency, high switching frequency DC–DC buck converter in AlGaAs/GaAs technology, targeting integrated power amplifier modules for wireless communications. The switch mode, inductor load DC–DC converter adopts an interleaved structure with negatively coupled inductors. Analysis of the effect of negative coupling on the steady state and transient response of the converter is given. The coupling factor is selected to achieve a maximum power efficiency under a given duty cycle with a minimum penalty on the current ripple performance. The DC–DC converter is implemented in 0.5 μm GaAs p-HEMT process and occupies 2 × 2.1 mm² without the output network. An 8.7 nH filter inductor is implemented in 65 μm thick top copper metal layer, and flip chip bonded to the DC–DC converter board. The integrated inductor achieves a quality factor of 26 at 150 MHz. The proposed converter converts 4.5 V input to 3.3 V output for 1 A load current under 150 MHz switching frequency with a measured power efficiency of 84%, which is one of the highest efficiencies reported to date for similar current/voltage ratings.     

Spatial-Temporal Cooperative Spectrum Sensing in Flat Fading Channels for Cognitive Radio Using Extend Kalman Filter

This paper investigates a new channel gain map tracking by Space-Time Extended Kalman Filtering (STEKF) for a flat channel, and a novel spectrum sensing via Time Spatial Weighted Non-negative Lasso (TSWNL) algorithm. STEKF enables CRs to estimate and interpolate channel gain map for the entire geographical area of interest with a limited number of CRs measurements. In order to sense primary users (PU) activities, include the transmission power by each PU, location and number of active PUs, TSWNL algorithm is proposed. Numerical results illustrate that the proposed STEKF channel estimation and TSWNL sensing algorithms outperforms linear methods.     

On the prediction of solubility of alkane in carbon dioxide using the LSSVM algorithm

The increasing global energy demand and declination of oil reservoir in recent years cause the researchers attention focus on the enhancement of oil recovery approaches. One of the extensive applicable methods for enhancement of oil recovery, which has great efficiency and environmental benefits, is carbon dioxide injection. The CO₂ injection has various effects on the reservoir fluid, which causes enhancement of recovery. One of these effects is extraction of lighter components of crude oil, which straightly depends on solubility of hydrocarbons in carbon dioxide. In order to better understand of this parameter, in this study, Least squares support vector machine (LSSVM) algorithm was developed as a novel predictive tool to estimate solubility of alkane in CO₂ as function of carbon number of alkane, carbon dioxide density, pressure, and temperature. The predicting model outputs were compared with the extracted experimental solubility from literature statistically and graphically. The comparison showed the great ability and high accuracy of developed model in prediction of solubility.     

Models of Restoration Probability in WDM Networks Employing Active Restoration

The ever-increasing demand for network bandwidth makes network survivability an issue of great concern. Lightpath restoration is a valuable approach to guaranteeing an acceptable level of survivability in WDM optical networks with better resource utilization than that of its protection counterpart. Active restoration (AR) is a newly proposed lightpath restoration scheme [M. Mostafa et al. OSA Journal of Optical Networking, vol. 3, no. 4, pp. 247–260] that combines the best of protection and reactive restoration while avoiding their shortcomings. In this paper, we conduct detailed performance analysis on the restoration probability of AR-based WDM networks. In particular, analytical models of restoration probability are developed respectively for networks with full-wavelength conversion capability and for networks without wavelength conversion capability under different backup path searching schemes. Based on the new models, we investigate the effects of wavelength availability, wavelength conversion capability, path length as well as backup path seeking methods on the restoration probability.     

3D seismic and formation micro-imager (FMI) integrated study to delineate depositional pattern of Abu Madi (Upper Miocene) clastic reservoir rocks in El-Wastani gas field,onshore Nile Delta,Egypt

Ten wells (EW-4, EW-5, EW-6, EW-7, EW-8, EW-9, EW-10, EW-12, EW-13 and EW-15) were interpreted using the composite well logs, data of core analysis, gamma-ray logs, formation micro-imager logs (FMI), and 3D seismic data in SEGY format to understand the stratigraphy of the onshore, Nile Delta, Egypt.The amplitude analysis of 3-D seismic horizon slice of Lower Abu Madi rock unit together with the lithostratigraphic correlation through the study area depending on the gamma-ray log “HSGR” (left to right increasing), and the identification of type of bed geometry, nature of bed contacts, type of the sedimentary structures and the dominant formative paleocurrents by using some available borehole micro-resistivity images (FMI) and core photos. All of these techniques are used together to define the different depositional facies and depositional environment of the Messinian clastics (Lower Abu Madi rock unit), which is considered to be the main reservoir in the El-Wastani gas field, onshore Nile Delta, Egypt.The present study of depositional pattern of the Upper Miocene clastics reservoir (Lower Abu Madi rock unit) revealed that it is represented by high sinuous meandering channels or paleo-valley and three types of fluvial facies were defined; channel fill, channel margin, and floodplain basin.     

Tapered beamforming for concentric ring arrays

In this paper, some conventional filtering windows are modified and applied to uniform concentric circular antenna arrays (UCCA) for spatial smoothing and sidelobe reduction. The modified windows are applied to individual rings of the array that will taper the corresponding current amplitudes. The resulted sidelobe level, beamwidth and stability for amplitude errors are discussed for the different proposed tapering windows where it shows a sidelobe reduction to about 49 dB as in the case of Binomial UCCA while the Hamming window shows the most immunity to tapered amplitude errors.     

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

In this paper, a novel full-duplex overlay cognitive wireless powered communication network (FD-OCWPCN) is proposed where a full-duplex (FD) hybrid-access point (H-AP) supports the full access of all battery-free secondary users (SUs). The H-AP broadcasts wireless power to empower the nearby SUs in the downlink (DL) phase while decoding the information transmitted uplink (UL) phase by the SUs, simultaneously. To overcome the self-interference (SI) phenomenon in FD-OCWPCN, the problem of maximizing the system sum-throughput with optimal UL-DL transmission/reception time and H-AP’s transmit power allocation is considered. This problem is non-convex under perfect/imperfect SI cancelation (SIC), so we employ the active interference temperature control and the gradient projection techniques to effectively reduce it into a convex problem. Closed-form expressions for the perfect/imperfect SIC cases are also derived. To assess the performance of the FD-OCWPCN, a comparison with a half-duplex OCWPCN (HD-OCWPCN) is provided. The achievable average sum-throughput for different FD/HD-OCWPCN is compared in the context of the average and peak transmit power at the H-AP, the number of SUs, path loss exponent and fairness metric. The simulation results depict the superiority of the FD-OCWPCN over the HD-OCWPCN for the perfect SIC and the effective imperfect SIC.

     

On Efficient Traffic Distribution for Disaster Area Communication Using Wireless Mesh Networks

In recent time, a great deal of research effort has been directed toward promptly facilitating post-disaster communication by using wireless mesh networks (WMNs). WMN technology has been considered to be effectively exploited for this purpose as it provides multi-hop communication through an access network comprising wireless mesh routers, which are connected to the Internet through gateways (GWs). One of the critical challenges in using WMNs for establishing disaster-recovery networks is the issue of distributing traffic among the users in a balanced manner in order to avoid congestion at the GWs. To overcome this issue, we envision a disaster zone WMN comprising a network management center. First, we thoroughly investigate the problem of traffic load balancing amongst the GWs in our considered disaster zone WMN. Then, we develop traffic load distribution techniques from two perspectives. Our proposal from the first perspective hinges upon a balanced distribution of the bandwidth to be allocated per user. On the other hand, our second perspective considers the dynamic (i.e., varying) bandwidth demands from the disaster zone users that requires a more practical and refined distribution of the available bandwidth by following an intelligent forecasting method. The effectiveness of our proposals is evaluated through computer-based simulations.     

A new quantum-dot cellular automata full-adder

A novel expandable five-input majority gate for quantum-dot cellular automata and a new full-adder cell are presented. Quantum-dot cellular automata (QCA) is an emerging technology and a possible alternative for semiconductor transistor based technologies. A novel QCA majority-logic gate is proposed. This component is suitable for designing QCA circuits. The gate is simple in structure and powerful in terms of implementing digital functions. By applying these kinds of gates, the hardware requirement for a QCA design can be reduced and circuits can be simpler in level, gate counts and clock phases. In order to verify the functionality of the proposed device, some physical proofs are provided. The proper functionality of the FA is checked by means of computer simulations using QCADesigner tool. Both simulation results and physical relations confirm our claims and its usefulness in designing every digital circuit.     

Thermal and rheological properties of nanoparticle modified asphalt binder at low and intermediate temperature range

There is a paucity of knowledge regarding the effect of nanoparticles on the performance of asphalt binder against fatigue and low-temperature cracking. In this research, asphalt binders were modified using SiO₂, TiO₂, and CaCO₃ nanoparticles, and rheological and thermal properties of the modified binders were investigated. Differential scanning calorimetry was used to determine glass transition temperature, and rheological properties at low and intermediate temperatures were determined using bending beam and dynamic shear rheometers, respectively. The results suggested that the addition of these nanoparticles increases glass transition temperature and the low-temperature stiffness of asphalt binder. Furthermore, increase in complex shear modulus and decrease in phase angle values were observed at intermediate temperatures. It can be concluded that inferior performance at low and intermediate temperature is expected by the addition of nanoparticles to asphalt binder.