Andrés Navarro Cadavid

Using game engines in ray tracing physics

This paper shows the used of a complete open source game engine and the significant advanced in computer graphics for applied ray tracing physics techniques in urban environment of propagation. We used techniques and software developed for open source game engine to: 1) The ray tracing physics algorithm for path loss, reflection and multiple diffraction. 2) The efficient use of graphic processing unit (GPU) and the multiple processor of the CPU.

Using 3-D Video Game Technology in Channel Modeling

We present here a paper on the potential use of game engines and graphic technologies for 3-D ray-based technologies used to simulate multipath channels. Our approach harnesses the power of video game development engines to provide an urban 3-D ray-based model for exploration and analysis of multipath channels for a wide frequency range in different complex outdoor and indoor scenarios. Game technologies offer a variety of options for exploiting the capabilities of graphical processing units and provide high performance in computing time with accurate results for channel modeling in current and future wireless technologies. We show the usefulness of this approach using our 3-D ray-based system in different applications.

A novel correlation adaptive receiver structure for high speed transmissions in ultra wide band systems with realistic channel estimation

Impulse radio ultra wide band (UWB) communications require robust receivers; typically Rake receivers are required to capture a large number of resolvable paths, (even hundred of paths), so large number of correlators are needed; otherwise, adaptive receivers use complex filters and channel estimation algorithms. Therefore, traditional Impulse radio receivers demand non-practical implementation structures. In this paper we propose a novel correlation-adaptive receiver structure with low complexity for indoor high speed ultra wide band systems. This novel structure combines correlation characteristics from Rake receivers with recursive filters from adaptive receivers. The receiver includes a low complexity recursive channel estimation filter capable of estimating hundreds of channel impulse responses, and a single filter-correlation filter used for coherent bit demodulation. Furthermore, we derive by simulations the bit error rate for high density multipath environments for several impulse radio modulations like TH-PPM, DS-BPSK and TH-BPSK and we compare the performance of the proposed structure with typical Rake receivers.

Handset based automatic network re-selection system for GSM/GPRS and WiFi

This paper presents the results of the development of a handset based automatic network reselection software system, which allows keeping end-to-end connections through semi-transparent handoff on WiFi/GSM-GPRS networks. A description of the developed systems software architecture is given, as well as of the components implemented for it, their functionalities and flow of control, all of which allow the permanent discovery of available networks for the mobile device, their evaluation, selection and switching to the network which offers the best ratings in its performance and operational profile, taking into account the preferences previously configured by the user. The system was developed in Java and C# for different operating systems (WinXP, WinMobile and Linux), and its interoperability has been tested in them. Some of the test scenarios are described and final comments about the tests results are given.

Simulation and analysis of compressed sensing technique as sampling and data compression and reconstruction of signals using convex programming

The information management has been treated primarily under the Nyquist sampling theory, but it is important to introduce new theories that replace deficiencies of what we know as the classical theory of sampling. These deficiencies create difficulties in data acquisition; this is a problem when large volumes of information are handled, in addition to the higher costs in storage and processing. This article presents the results obtained from the compressed sensing simulation technique applied to two types of signals. The aim of this paper was to simulate a communication system involving the data recovery applying the compressed sensing technique, analyzing sampling rates reduction, measuring the efficiency of the process and the behavior of the technique. The recovery of the signal is made using convex programming and using l1 norm minimization for recover the signals in the time domain. We used the L1Magic toolbox, which is a set of Matlab® functions used to solve optimization problems in this case with the l1eqpd function. As a summary of the obtained results, we checked the efficiency of the compressed sensing technique, minimum average rates for sampling the constructed signals, and the best performance of the technique to recover soft signals compared to non-differentiable signals. Additionally, the recovery results of an audio signal with the compressed sensing technique, by varying the sampling rate and checking the audibility of the signal, are presented. This allowed the testing of this technique in a real scenario, finding a good opportunity for the transmission of audio signals in a more efficient way.