Maurizio A. Spirito

On the accuracy of cellular mobile station location estimation

This paper analyzes the accuracy of the multilateration techniques of possible application in mobile communications networks. A general mathematical framework including all the multilateration techniques that process absolute and/or relative distance measurements between the mobile station and multiple base transceiver stations is introduced. Based on this scheme, a general measure of positioning accuracy is first derived and then analyzed in the special cases defined by three techniques of possible implementation in GSM-based systems. A geometrical interpretation of the formulas that define the location accuracy and a comparison between the techniques from the geometric conditioning point of view are also given.

Cooperative spectrum sensing based on the limiting eigenvalue ratio distribution in wishart matrices

Recent advances in random matrix theory have spurred the adoption of eigenvalue-based detection techniques for cooperative spectrum sensing in cognitive radio. These techniques use the ratio between the largest and the smallest eigenvalues of the received signal covariance matrix to infer the presence or absence of the primary signal. The results derived so far are based on asymptotical assumptions, due to the difficulties in characterizing the exact eigenvalues ratio distribution. By exploiting a recent result on the limiting distribution of the smallest eigenvalue in complex Wishart matrices, in this paper we derive an expression for the limiting eigenvalue ratio distribution, which turns out to be much more accurate than the previous approximations also in the non-asymptotical region. This result is then applied to calculate the decision sensing threshold as a function of a target probability of false alarm. Numerical simulations show that the proposed detection rule provides a substantial improvement compared to the other eigenvalue-based algorithms.

On the hyperbolic positioning of GSM mobile stations

This paper presents a method for locating GSM mobile stations (MSs) using a hyperbolic position location technique. The proposed solution makes use only of GSM functions, avoiding additional GPS (Global Positioning System) equipment. The algorithm is implemented with an extended Kalman filter (EKF) that, processing the time delay difference of arrival (TDOA) measurements, allows one to estimate both the position and the speed vectors of the MS. The TDOA estimates from at least three base transceiver stations (BTSs) are obtained from OTD (observed time difference) and RTD (real time difference) parameters yet defined by ETSI for a GSM Phase 2 network. Computer simulations are provided to show the feasibility of the proposed approach.

Preliminary experimental results of a GSM mobile phones positioning system based on timing advance

This paper reports some indicative results of the performances characterizing a GSM mobile station location method based on timing advance (TA). Processed TA values have been collected during a field trial in a GSM network. Location calculation results and measurement statistics are also provided.

The VIRTUS Middleware: An XMPP Based Architecture for Secure IoT Communications

Before a wider adoption of the Internet of Things (IoT) vision occurs, many urgent technological and social challenging issues still need to be addressed, including device interoperability, systems autonomy, privacy and security concerns, which could have a significant impact on several aspects of everyday-life or potential end-user. Due to the very large number of technologies normally in place within the IoT paradigm, some type of middleware layer is employed to enforce seamless integration of devices and data within the same information network. Within such middleware, data must be exchanged respecting strict protection constraints. Both the networking and security issues have driven the design and the development of the VIRTUS Middleware, an IoT middleware relying on the open XMPP protocol to provide secure event- driven communications within an IoT scenario. Leveraging the standard security features provided by XMPP, the middleware offers a reliable and secure communication channel for distributed applications, protected with both authentication (through TLS protocol) and encryption (SASL protocol) mechanisms. The proposed architecture provides the possibility to isolate an instance of VIRTUS, allowing the exchange of data only within a private network. This paper presents an overview of VIRTUS, providing an overall platform description and details regarding its security features.

Experimental performance of methods to estimate the location of legacy handsets in GSM

This paper focuses on the location estimation of legacy GSM (Global System for Mobile communications) handsets. Three network-based software location methods using CI (cell identity), TA (timing advance), and RXLEV (received signal strength) information available in GSM are presented and their implementation is discussed. Experimental performance of the methods in a commercial GSM network is presented and a comparative analysis is carried out. It is shown that the location error of the most accurate method tends to scale according to the average cell size.

Hybrid GNSS-Terrestrial Cooperative Positioning Based on Particle Filter

We propose a novel hybrid GNSS-terrestrial localization algorithm based on particle filter that fuses ranging data from both satellites and terrestrial receivers. The proposed positioning approach, named hybrid-cooperative particle filter (HCPF), is fully distributed and allows both increased positioning availability and accuracy compared to GNSS-only localization in challenged scenarios. Moreover, simulation results based on a realistic indoor scenario show that the proposed solution outperforms several state of the art algorithms such as unscented Kalman filter and an approach based on belief propagation.

Probability of Missed Detection in Eigenvalue Ratio Spectrum Sensing

Eigenvalue-based detection is an efficient signal detection technique, recently introduced in the Cognitive Radio context to guarantee a reliable identification of primary users. In this paper we contribute to the theoretical analysis of this detection scheme by deriving a mathematical expression for the probability of missed detection as a function of the number of cooperating receivers, the number of samples and the signal-to-noise ratio of the primary user. The analysis is referred to a detector using as test statistic the ratio between the largest and the smallest eigenvalue of the covariance matrix. Along with previous results on the probability of false alarm, this contribution completes the performance evaluation of this type of detector.

Hybrid Indoor Positioning Approaches Based on WSN and RFID

Nowadays indoor positioning applications have received great attentions among short range wireless communication systems. In particular, Wireless Sensor Network (WSN) is the most widely used technology for indoor localization as it is cheap and easy to deploy. However, location accuracy is limited by the harsh propagation of the Radio Frequency (RF) signals in indoor environments, for instance, caused by the presence of obstacles between wireless nodes, multi-paths, interference, etc. To overcome these effects and improve positioning accuracy, Radio Frequency Identification (RFID) technology is employed to assist the WSN based positioning. This paper proposes two hybrid positioning approaches based both on WSN and RFID. One solution uses an Extended Kalman Filter (EKF) algorithm while the other one uses a Particle Filter (PF) approach. Both methods are compared through Matlab simulations which demonstrate that in general the WSN/RFID hybrid approach is feasible and provides good positioning estimation capabilities even under harsh indoor conditions.

WLAN-Based Real Time Vehicle Locating System

This paper presents a wireless local area network (WLAN)-based real time system for indoors and outdoors ve- hicle localization. The proposed solution uses a neural network trained with a map of received power fingerprints from WLAN Access Points (APs) surrounding the vehicle. The practical implementation of the system is described and results from an outdoor experimental testbed are analyzed to address system performance in terms of calibration, estimation complexity, and location accuracy. Pre- and post-processing approaches aimed at improving system accuracy are also discussed. Index Terms—positioning, neural network, fingerprint, real time locating system, wireless local area network ∗