Capacity limits of spectrum‐sharing systems over hyper‐fading channels

Cognitive radio (CR) with spectrum‐sharing feature is a promising technique to address the spectrum under‐utilization problem in dynamically changing environments. In this paper, the achievable capacity gain of spectrum‐sharing systems over dynamic fading environments is studied. To perform a general analysis, a theoretical fading model called hyper‐fading model that is suitable to the dynamic nature of CR channel is proposed. Closed‐form expressions of probability density function (PDF) and cumulative density function (CDF) of the signal‐to‐noise ratio (SNR) for secondary users (SUs) in spectrum‐sharing systems are derived. In addition, the capacity gains achievable with spectrum‐sharing systems in high and low power regions are obtained. The effects of different fading figures, average fading powers, interference temperatures, peak powers of secondary transmitters, and numbers of SUs on the achievable capacity are investigated. The analytical and simulation results show that the fading figure of the channel between SUs and primary base‐station (PBS), which describes the diversity of the channel, does not contribute significantly to the system performance gain. Copyright © 2011 John Wiley & Sons, Ltd.     

Effects of annealing on the structural and magnetic properties of flame spray pyrolyzed MnFe2O4 nanoparticles

In this study, manganese ferrite (MnFe₂O₄) nanoparticles were produced through flame spray pyrolysis (FSP). To investigate the effects of heat treatment, the nanoparticles were annealed between 400 and 650°C for 4 h in air in a comparative manner. The structural, chemical, morphological, and magnetic properties of the nanoparticles were evaluated using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), dynamic light scattering (DLS), and vibrating sample magnetometry (VSM), respectively. The XRD results showed that the nanoparticles synthesized by the FSP method exhibited the MnFe₂O₄ spinel ferrite structure. The annealing process led to the decomposition of MnFe₂O₄ into various phases. According to the morphological analysis, the as-synthesized particles were hemispherical–cubic in shape and had an average particle size of less than 100 nm. In addition, the chemical bond structures of the nanoparticles were confirmed in detail by XPS elemental analysis. The highest saturation magnetization was recorded as 33.50 emu/g for the as-produced nanoparticles. The saturation magnetization of the nanoparticles decreased with increasing annealing temperature, while coercivity increased.     

Systemic reliability of bridge networks with mobile sensing-based model updating for postevent transportation decisions

This paper proposes the upscaling of conventional individual bridge health monitoring problems into urban regions and transportation networks via mobile and smart sensing techniques together with an innovative reconnaissance procedure. The paper associates structural failure probabilities with systemic features and proposes decision criteria to optimize postdisaster actions. Twenty bridges constituting transportation network infrastructure compose the testbed region and utilize smartphone accelerometers for dynamics characterization in a vibration-based framework. In this framework, reconnaissance output serves for model development, and mobile sensor data enable finite element model updating. Structural reliability analyses merged in a chain setting generate the systemic behavior of cascaded bridge performance. Combining systemic reliability with transportation and health services demand, one can optimize the response strategies of the bridge population and strategize disaster-related decisions in a postevent assessment setting. Based on a testbed region with remote access to nearby vicinities, 18 earthquake scenarios are conducted to visualize the optimal evacuation strategies on the network, taking systemic bridge performance into consideration. Cost-free mobile sensing support adds one more fundamental information source for reducing the uncertainty of the models and, therefore, improves associated mitigation actions.