Juan Blas

Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks

The positioning methods based on received signal strength (RSS) measurements, link the RSS values to the position of the mobile station(MS) to be located. Their accuracy depends on the suitability of the propagation models used for the actual propagation conditions. In indoor wireless networks, these propagation conditions are very difficult to predict due to the unwieldy and dynamic nature of the RSS. In this paper, we present a novel method which dynamically estimates the propagation models that best fit the propagation environments, by using only RSS measurements obtained in real time. This method is based on maximizing compatibility of the MS to access points (AP) distance estimates. Once the propagation models are estimated in real time, it is possible to accurately determine the distance between the MS and each AP. By means of these distance estimates, the location of the MS can be obtained by trilateration. The method proposed coupled with simulations and measurements in a real indoor environment, demonstrates its feasibility and suitability, since it outperforms conventional RSS-based indoor location methods without using any radio map information nor a calibration stage.

Prior NLOS Measurement Correction for Positioning in Cellular Wireless Networks

A mobile station (MS) location can be estimated from the measurement of the time of arrival of the signals that travel between each base station and the MS. In this scenario, the existence of non-line-of-sight (NLOS) propagation paths has been considered to be the main drawback to achieve high precision in positioning, since NLOS propagation introduces large and unpredictable errors in the time estimates that are obtained from the measurements. In this paper, we propose a new technique, called prior NLOS measurement correction (PNMC), to effectively correct the measurements from NLOS propagation in a previous stage to the positioning process. PNMC is based on a statistical processing of a record of measurements taken over a time window. This processing relies on the statistical estimate of the NLOS measurement ratio present in our record. This estimate is used to range the NLOS recorded measurements into segments. Finally, the correction is carried out by subtracting the expected NLOS errors for each segment. Several simulations have been conducted to show the increase in accuracy obtained by the usage of PNMC and the great improvement that this prior measurement correction means to subsequent wireless location and positioning techniques.

Dynamic Routing and Wavelength Assignment in Optical Networks by Means of Genetic Algorithms

We propose a novel genetic algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in wavelength-routed optical networks. The algorithm not only obtains low call blocking probability, but it also employs a very short computation time. Moreover, it is capable of providing fairness among connections, that is, to offer approximately the same quality of service (in terms of blocking probability) for all source-destination node pairs. Since requirements on optical network availability are highly severe, we also propose an extension of the algorithm to provide fault-tolerance capability at the optical layer. It is achieved by means of protection, where each optical connection request is provided with a pair of lightpaths (a primary and a backup lightpath). Again, the genetic algorithm proves to be highly efficient, in this case, at performing routing and wavelength assignment of pairs of lightpaths.

IEEE 802.11 Distance Estimation Based on RTS/CTS Two-Frame Exchange Mechanism

The addition of positioning capabilities to wide- spread communications such as IEEE 802.11 compliant networks could open up interesting markets, in particular if a low-cost hardware has to be added to the existing one and standard RTS/CTS control frames exchange could be used for this purpose. In this paper various statistical estimators of the delay profile observed, derived from Round-Trip Time measurements, are analyzed and a linear regression of the statistical estimators is applied in order to improve the accuracy of distance estimation between a Mobile User and an Access Point. A precision in distance estimation with errors in the range of a meter is achieved.

NLOS mitigation based on range estimation error characterization in an RTT-based IEEE 802.11, indoor location system

Ranging techniques have significant effects on localization accuracy, system complexity, and system cost, in most common wireless location systems. In such systems, loss of accuracy is most often caused by the lack of a direct line-of-sight (LOS) between a mobile user (MU) and a reference access point (AP). This drawback is increased when the location system is deployed in cluttered scenarios. Modeling the non-line-of-sight (NLOS) error formally represents one way to deal with this issue. However, a trade-off decision has to be made between the efficiency of the system and its complexity and computational cost. In this paper, NLOS error is confined to single-parameter distributions, specifically Exponential and Rayleigh. Both models are introduced in the prior NLOS measurements correction (PNMC) method, and compared in terms of range and position error, in a round-trip time (RTT)-based real location system. Furthermore, improvement of accuracy by dynamically estimating Exponential or Rayleigh parameters is likewise analyzed. The results show a high NLOS bias reduction after PNMC procedure, and even greater when using dynamic parameters.

Assessment of human body influence on exposure measurements of electric field in indoor enclosures.

Personal exposure meters (PEMs) used for measuring exposure to electromagnetic fields (EMF) are typically used in epidemiological studies. As is well known, these measurement devices cause a perturbation of real EMF exposure levels due to the presence of the human body in the immediate proximity. This paper aims to model the alteration caused by the body shadow effect (BSE) in motion conditions and in indoor enclosures at the Wi-Fi frequency of 2.4 GHz. For this purpose, simulation techniques based on ray-tracing have been carried out, and their results have been verified experimentally. A good agreement exists between simulation and experimental results in terms of electric field (E-field) levels, and taking into account the cumulative distribution function (CDF) of the spatial distribution of amplitude. The Kolmogorov-Smirnov (KS) test provides a P-value greater than 0.05, in fact close to 1. It has been found that the influence of the presence of the human body can be characterized as an angle of shadow that depends on the dimensions of the indoor enclosure. The CDFs show that the E-field levels in indoor conditions follow a lognormal distribution in the absence of the human body and under the influence of BSE. In conclusion, the perturbation caused by BSE in PEMs readings cannot be compensated for by correction factors. Although the mean value is well adjusted, BSE causes changes in CDF that would require improvements in measurement protocols and in the design of measuring devices to subsequently avoid systematic errors.

Dynamic estimation of optimum path loss model in a RSS positioning system

The development of location techniques in urban and indoor environments by using measurements of received signal strength (RSS) has as a main drawback the fact that in such environments the value of RSS depends on many unpredictable and changeable factors, not only on the actual distance between mobile station (MS) and the different base stations (BSs). With the aim of solving these limitations of RSS-based location systems, in this paper we present a novel technique to find out which model best describes the different propagations of signals traveling between the MS and the different BSs. This method estimates accurately and dynamically, all the path loss exponents that model the signal attenuation in propagation paths to each BS, only by using the received signal strength measurements that are obtained in each moment. Therefore, our method does not need any previous knowledge about user position or kind of propagation environment. From the estimation of the different path loss exponents, we obtain much more accurate distance estimations than those obtained by using a generic and unique propagation model previously fixed. We present the results obtained by using the methods described in this paper, from real measurements taken in a GSM network as well as from computer simulations. By using the techniques presented in this paper we can see the great improvement in the precision on estimating distances from the MS and the different BSs. The results obtained from the real measurements support the simulations results and show how that improvement in the distance estimation makes the location much more accurate.

E-field assessment errors associated with RF dosemeters for different angles of arrival

In this paper, an analysis of the surface electric field on a human body based on finite-difference time-domain simulations is presented. A statistical analysis of the dosemeter interaction with the human body has been made by means of the variations of the relative orientation of the human body from the RF source. Variations of the RF source frequency have also been made, by comparing three different services FM, GSM-900 and DCS-1800. Three different scenarios have been simulated where the angle of arrival of the main RF contribution impinges on the human body with a certain probability. Despite the differences between the scenarios, the variations in the electric field strength at each frequency are negligible where the dosemeter would be located.

Statistical perturbations in personal exposure meters caused by the human body in dynamic outdoor environments.

Personal exposure meters (PEM) are routinely used for the exposure assessment to radio frequency electric or magnetic fields. However, their readings are subject to errors associated with perturbations of the fields caused by the presence of the human body. This paper presents a novel analysis method for the characterization of this effect. Using ray-tracing techniques, PEM measurements have been emulated, with and without an approximation of this shadowing effect. In particular, the Global System for Mobile Communication mobile phone frequency band was chosen for its ubiquity and, specifically, we considered the case where the subject is walking outdoors in a relatively open area. These simulations have been contrasted with real PEM measurements in a 35-min walk. Results show a good agreement in terms of root mean square error and E-field cumulative distribution function (CDF), with a significant improvement when the shadowing effect is taken into account. In particular, the Kolmogorov-Smirnov (KS) test provides a P-value of 0.05 when considering the shadowing effect, versus a P-value of 10⁻¹⁴ when this effect is ignored. In addition, although the E-field levels in the absence of a human body have been found to follow a Nakagami distribution, a lognormal distribution fits the statistics of the PEM values better than the Nakagami distribution. As a conclusion, although the mean could be adjusted by using correction factors, there are also other changes in the CDF that require particular attention due to the shadowing effect because they might lead to a systematic error.

Nature-Inspired Routing and Wavelength Assignment Algorithms for Optical Circuit-Switched Polymorphic Networks

Polymorphic optical networks simultaneously support several optical switching paradigms over a single physical network. In this way, they provide service differentiation at the optical layer by employing the most appropriate paradigm for each service. One type of such architecture is the optical circuit-switched polymorphic network (OCSPN), which combines optical circuit switching paradigms with different grades of dynamism. The performance of this network relies on the utilization of efficient routing and wavelength assignment (RWA) algorithms. In this article, we review the fundamentals of OCSPNs and present a set of efficient RWA algorithms based on ant colony optimization and genetic algorithms.