Leni J. Matos

The Relevance Vector Machine Applied to the Modeling of Wireless Channels

A good modeling of the radio propagation channel is essential to the design of high-performance wireless systems; therefore, the proper interpretation of the data acquired from the sounding process is a task of major importance in the construction of such models. The relevance vector machine (RVM) constitutes a learning algorithm, based on Bayesian Statistics, used in regression and classification problems. Recently, RVM was employed to filter the channel multipath components of simulated power delay profiles embedded with noise, enabling the determination of the paths arriving at the reception antenna, their arrival times and complex amplitudes. In this paper, the RVM algorithm is further studied, regarding its detection capabilities, but the power delay profiles were obtained from measurements carried out in an indoor channel. A comparison with the constant false alarm rate (CFAR) multipath identification scheme, based on computational simulation and real channel measurements, evidences the behavior of both detection schemes. Simulations also present the detection limits of the method, such as maximum multipath magnitude ratio and minimum interarrival time. Finally, the characterization of important parameters of a real wideband multipath indoor channel is presented, in terms of confidence intervals and probability distribution fittings.

Coverage prediction models fitted to the signal measurements of digital TV in Brazilian cities

Broadcast television is one of the most important telecommunications systems in Brazil. Such relevance in the socio-cultural context requires a continuous pursuit of technical excellence in order to offer an increasingly attractive product to the viewer. Therefore, it is mandatory to care about the coverage and quality of the TV signal, especially when it comes to Digital TV. In this scenario, it is imperative to study propagation models to predict the coverage allowing broadcasters to properly project their stations and regulators to distribute the channels harmoniously. The aim of this study is to compare the field strength measurements of a Digital TV signal in five cities of Brazil, with the values predicted by some models and to conclude for the best one.

Improvement of Outdoor Signal Strength Prediction in UHF Band by Artificial Neural Network

Starting from measurements performed at 1140 MHz in an urban environment (Rio de Janeiro, Brazil), the signal strength measured is compared with the usual predictions calculated using the methods of International Telecommunication Union-Radiocommunication (ITU-R) Rec. 526-11/Cascade Knife Edge, and ITU-R Rec. 526-12/Delta-Bullington. The first model presented better adjustment to the data and, by using artificial neural networks (ANNs), this paper deals with the signal coverage prediction in a mobile channel calculated by the ITU-R model, which is used to train the ANN in order to reduce the average deviations. This hybrid application (ITU-R/ANN) showed efficiency, resulting in higher accuracy for the signal strength prediction, and an average improvement of 8 dB was achieved.

Channel characterization in the 5.8GHz band in a suburban area

Based on signal measurements carried out in the 5.8 GHz band, which is reserved for unlicensed WiMAX in Brazil, this paper evaluates narrowband and wideband characteristics on the suburban area of Tangua city in Rio de Janeiro State. Fading statistics, coverage and adjusted prediction model such as Hata-COST 231, SUI and UFPA were used in order to find the model that best fits the measurement data before ultimately determining that the UFPA model proved to be the best one. Temporal dispersion is studied through the delay spread and coherence band calculated from the power delay profiles obtained in the sounded channel.

Signal coverage in a suburban area for the 5.8 GHz frequency band

From signal measurements carried out in the 5.8 GHz band, that is reserved to unlicensed WiMAX in Brazil, this paper evaluates the signal coverage on this band in the suburban area of Tanguá. Prediction models as Hata-COST 231, SUI and UFPA (Modified SUI) were used in order to find the model that best fitted to the measurements data and then, the modified SUI model showed to be the better one.

Simulation of Indoor-Outdoor and Outdoor-Indoor Radio Channel in 960-1700 MHz Band

The design of high performance communication systems depends on the previous knowledge of the radio channel dispersive behavior. Through wideband measurements it is possible to measure such dispersion by determining parameters as delay and Doppler spread or coherence time and bandwidth. In this work, measurements carried out on the 910-1710 MHz band in a transition channel (indoor-outdoor and outdoor-indoor) generate data that permit to compare the experimental delay spread with that obtained from the simulation of this channel by using the Saleh-Valenzuela model, which is a model applied to indoor channels. Clusters of multipath in the power delay profiles are used to identify the model parameters, instead of a unique cluster. The parameters of the Turin model, which is a model applied to outdoor channel, are also identified with the same experimental data. The tools used in this paper pointed to the conclusion that the Saleh-Valenzuela model can be used to simulate the transition channel too.

Statistical characterization and simulation of a femtocell indoor radio channel

This paper presents the statistical analysis of measured propagation data in a femtocell indoor radio environment. Measurements were performed at 1.95 GHz with a 160 MHz channel bandwidth. Time domain sounding technique using PN-sequence with a matched filter was employed. Empirical and theoretical prediction using the Saleh — Valenzuela model and the Finite-Difference Time-Domain (FDTD) method, accelerated via GPU technology, were respectively carried out. So, a comparison between theoretical and experimental simulation is presented.

Power delay profile filtering techniques for indoor radio channel characterization

This paper presents a comparison of two power delay profile filtering techniques, the Relevance Vector Machine — RVM — and the Constant False Alarm Rate — CFAR. Both techniques are applied to power delay profiles (PDPs) measured in a indoor environment at 1.95 GHz on a 160 MHz channel bandwidth and the matched filter technique is used for the sounding. The RMS (root mean square) delay spreads are determined from these filtered PDPs and from the original ones. So, for all positions of the receiver, they are compared and the quadratic mean error is evaluated.

Wideband characterization of the mobile radio signal in a vegetated environment

This article presents the dispersion parameters of a mobile radio channel obtained from the measurements carried out using time domain wideband sounding, in a mixed vegetated environment with buildings, with a STDCC (Swept-Time Delay Cross Correlation) sounder. In addition, some comparisons are made with parameters obtained from other publications, in similar environments, and conclusions and suggestions are given.