Performance of direct-oversampling correlator-type receivers in chaos-based DS-CDMA systems over frequency non-selective fading channels

In this paper, we present a study on the performance of direct-oversampling correlator-type receivers in chaos-based direct-sequence code division multiple access systems over frequency non-selective fading channels. At the input, the received signal is sampled at a sampling rate higher than the chip rate. This oversampling step is used to precisely determine the delayed-signal components from multipath fading channels, which can be combined together by a correlator for the sake of increasing the SNR at its output. The main advantage of using direct-oversampling correlator-type receivers is not only their low energy consumption due to their simple structure, but also their ability to exploit the non-selective fading characteristic of multipath channels to improve the overall system performance in scenarios with limited data speeds and low energy requirements, such as low-rate wireless personal area networks. Mathematical models in discrete-time domain for the conventional transmitting side with multiple access operation, the generalized non-selective Rayleigh fading channel, and the proposed receiver are provided and described. A rough theoretical bit-error-rate (BER) expression is first derived by means of Gaussian approximation. We then define the main component in the expression and build its probability mass function through numerical computation. The final BER estimation is carried out by integrating the rough expression over possible discrete values of the PFM. In order to validate our findings, PC simulation is performed and simulated performance is compared with the corresponding estimated one. Obtained results show that the system performance get better with the increment of the number of paths in the channel.Peer ReviewedPostprint (author's final draft

Design Guidelines for Agent Based Model Visualization

In the field of agent-based modeling (ABM), visualizations play an important role in identifying, communicating and understanding important behavior of the modeled phenomenon. However, many modelers tend to create ineffective visualizations of Agent Based Models (ABM) due to lack of experience with visual design. This paper provides ABM visualization design guidelines in order to improve visual design with ABM toolkits. These guidelines will assist the modeler in creating clear and understandable ABM visualizations. We begin by introducing a non-hierarchical categorization of ABM visualizations. This categorization serves as a starting point in the creation of an ABM visualization. We go on to present well-known design techniques in the context of ABM visualization. These techniques are based on Gestalt psychology, semiology of graphics, and scientific visualization. They improve the visualization design by facilitating specific tasks, and providing a common language to critique visualizations through the use of visual variables. Subsequently, we discuss the application of these design techniques to simplify, emphasize and explain an ABM visualization. Finally, we illustrate these guidelines using a simple redesign of a NetLogo ABM visualization. These guidelines can be used to inform the development of design tools that assist users in the creation of ABM visualizations.Visualization, Design, Graphics, Guidelines, Communication, Agent-Based Modeling

A Physical Layer Model for G3-PLC Networks Simulation

This work presents a model of the G3-PLC physical (PHY) layer tailored for network simulations. It allows simulating frequency selective channels with non-stationary colored noise. Collisions with other frames are modeled taking into account the length and the power of the interfering frames. Frame errors are estimated using the effective signal-to-interference-and-noise ratio mapping (ESM) function. The proposed PHY layer has been integrated into a distributed event-based simulator developed by Microchip. The layer 2+ stack of the simulator uses the same code that actual Microchip G3-PLC devices. Validation has been accomplished by comparing its results to a test network deployed in the laboratory. The latter consists of a coordinator and one hundred meters distributed in 5 levels. Faster-than-real-time simulations and an excellent agreement between the simulated and the measured performance indicators at the application layer have been obtained.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model

Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein-Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.Comment: 38 pages, in press at Systematic Biolog

A HIERARCHICAL BAYES APPROACH TO MODELING CHOICE DATA: A STUDY OF WETLAND RESTORATION PROGRAMS

This study examines the factors the influence the values and importance that landowners place on the attributes of voluntary wetland restoration programs. Choice-based conjoint analysis, a stated preference method, was used to estimate the marginal utilities and values for restoration program attributes for North Carolina landowners. Landowner preferences were estimated at individual and aggregate levels to examine the importance of modeling heterogeneous preferences. Choice modeling performed at both aggregate and individual levels demonstrated the information gains from a disaggregated approach.Research Methods/ Statistical Methods,