How significant is the assumption of the uniform channel phase distribution on the performance of spatial multiplexing MIMO system?

Spatial multiplexing (SMX) multiple-input multiple-output (MIMO) systems are promising candidates to enhance the achievable throughput and the overall spectral efficiency in future wireless systems. Performance studies of these systems over different channel conditions assume simplified models for the channel phase distribution. This paper highlights the impact of the channel phase distribution assumption on the performance of SMX MIMO systems. The Nakagami-m and the \(\eta -\mu\) fading channels are considered in this study. In existing literature, performance studies of SMX MIMO systems over Nakagami-m fading channel assume uniform phase distribution. Though, it has been reported recently that the Nakagami-m channel phase distribution is not uniform. In this article, we show that the assumption of the channel phase distribution has a major impact on the performance of SMX MIMO systems. The obtained results demonstrate that the performance of SMX MIMO systems significantly varies with different channel phase distributions. Furthermore, it is shown that uniform assumption of channel phase distribution is incorrect and leads to erroneous conclusions. Detailed performance analysis for more accurate channel models are provided and results are sustained through Monte-Carlo simulations.     

Measurement and Explanation of DC/RF Power Loci of an Active Patch Antenna

A case study of an active transmitting patch antenna revealed a characteristic loop locus of DC power versus RF output power as drive frequency was varied, with an operational bandwidth substantially smaller than the impedance bandwidth of the radiator. An approximate simulation technique, based on separation of the output capacitance of the power transistor, yielded easily visualized plots of power dependence on internal load impedance, and a simple interpretation of the experimental results in terms of a near‐resonance condition between the output capacitance and output packaging inductance.     

Uniform and Non-uniform Thermoelement Subject to Lateral Heat Convection

A general energy equation of quasi-one-dimensional heat flow in a longitudinal thermoelement (TE) of a curved side that is subjected to an electric field and convection heat transfer on the curved surface is developed. The energy equation is solved for the temperature distribution in two cases; uniform cross-section TE and non-uniform cross-section TE. Analytical solutions for a uniform cross-section TE with uniform electrical and thermophysical properties are obtained, whereas numerical solutions are provided for a non-uniform cross-section TE. Two parameters playing a vital role in the thermal performance of the TE are identified: the heat resistance ratio (HRR) and the energy growing ratio (EGR). The HRR represents the ratio of the longitudinal conduction maximum thermal resistance to the lateral convection maximum thermal resistance. The EGR represents the ratio of Joule’s electrical heating to Fourier’s heat conduction. The effects of varying these two parameters, as well as the TE geometry, have been thoroughly investigated.     

Reliability of mesh and torus topologies in the presence of faults

Mesh and torus topologies have been used to implement various multicomputer architectures. Faults in these networks significantly degrade their performance. In this paper, a new Markov model is used to derive a closed form analytical solution for the terminal reliability of the mesh and 2‐dimensional torus. The effect of the added links in the torus on reliability is studied. Networks of various dimensions are analyzed, and all the analytical results are verified by computer simulations. Although the mesh‐connected topology is considered in this paper, the analysis can be readily adopted for any network topology. This revised version was published online in June 2006 with corrections to the Cover Date.     

Application of multitemporal Landsat data to monitor land cover changes in the Eastern Nile Delta region,Egypt

Due to the progressive increase in development of desert land in Egypt, the demand for efficient and accurate land cover change information is increasing. In this study, we apply the methodology of post‐classification change detection to map and monitor land cover change patterns related to agricultural development and urban expansion in the desert fringes of the Eastern Nile Delta region. Using a hybrid classification approach, we employ multitemporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images from 1984, 1990 and 2003 to produce three land cover/land‐use maps. Post‐classification comparison of these maps was used to obtain ‘from–to’ statistics and change detection maps. The change detection results show that agricultural development increased by 14% through the study period. The average annual rate of land reclamation during 1990–2003 (4511 ha a^?1) was comparable to that during 1984–1990 (4644 ha a^?1), reflecting a systematic national plan for desert reclamation that went into effect. We find that the increase in urbanization (by ca 21 300 ha) during 1990–2003 was predominantly due to encroachment into traditionally cultivated land at the fringes of urban centres. Our results accurately quantify the land cover changes and delineate their spatial patterns, demonstrating the utility of Landsat data in analysing landscape dynamics over time. Such information is critical for making efficient and sustainable policies for resource management.     

Performances study of compact printed diversity antenna in the presence of user's body for LTE mobile phone applications

In this article, three kinds of user effect are considered, namely, “specific anthropomorphic mannequin (SAM) head and personal digital assistants (PDA) hand (talk mode),” “PDA hand (data mode),” and “Dual hands (read mode)” for the performance study of the compact LTE MIMO antenna. This is in continuation of the previously published work which has been investigated in the free space. However, the designed antenna covers LTE700 (0.747‐0.787 GHz) and WWAN (1.7‐3.04 GHz) based on ?6 dB reflection coefficient. Further, the effect of users' body is investigated by placing the planar monopole antenna (PMA) on the top and the bottom portion of the mobile printed circuit board (PCB). The performances like S‐parameters, radiation performances, diversity performances, and channel capacity loss are studied and optimal location of PMA is assigned either top or bottom portion of mobile phone PCB based on the results obtained from the respective positions. Finally, the specific absorption rate is estimated and found well below the standard limit of FCC that is, less than 1.6 W/kg over 1 g tissue and European that is, 2 W/kg over 10 g tissue. In present work, it is observed that top positioned PMA provides optimal performances in the user proximity over PCB.     

A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

In cognitive radio networks (CoR), the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability. Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection. However, these methods do not take into account the effect of sample size and its effect on improving CoR performance. In general, a large sample size results in more reliable detection, but takes longer sensing time and increases complexity. Thus, the locally sensed sample size is an optimization problem. Therefore, optimizing the local sample size for each cognitive user helps to improve CoR performance. In this study, two new methods are proposed to find the optimum sample size to achieve objective-based improved (single/double) threshold energy detection, these methods are the optimum sample size N* and neural networks (NN) optimization. Through the evaluation, it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate, detection probability, and throughput.

     

Virus detection using clonal selection algorithm with Genetic Algorithm (VDC algorithm)

This paper presents a novel approach for computer viruses detection based on modeling the structures and dynamics of real life paradigm that exists in the bodies of all living creatures. It aims to develop an algorithm based on the concept of the artificial immune system (AIS) for the purpose of detecting viruses. The algorithm is called Virus Detection Clonal algorithm (VDC), and it is derived from the clonal selection algorithm. The VDC algorithm consists of three basic steps: cloning, hyper-mutation and stochastic re-selection. In later stage, the developed VDC algorithm is subjected to validation, which consists of two phases; learning and testing. Two main parameters are determined; one of them is setting the number of signatures per clone (Fat), while the other defines the hypermutation probability (Pm). Later on, the Genetic Algorithm (GA) is used as a tool, to improve the developed algorithm by searching the values of the main parameters (Fat and Pm) to reproduce better results. The results have shown that the detection rate of viruses, by using the developed algorithm, is 94.4%, whereas the detection rate of false positives has reached 0%. These percentages indicate that the VDC algorithm is sufficient and usable in this field. Moreover, the results of employing the GA to optimize the VDC algorithm have shown an improvement in the detection speed of the algorithm.     

The degree of e-business entrepreneurship and long-term sustainability: an institutional perspective

Information Systems and e-Business Management - The purpose of this study is to develop and validate an institutional model to investigate the relationships among institutional drivers, the degree...