P.E. Leuthold

Bio: P.E. Leuthold is an academic researcher from ETH Zurich. The author has contributed to research in topics: Radio propagation & Mobile telephony. The author has an hindex of 1, co-authored 1 publications receiving 107 citations.

Radiowave propagation in mobile communications: an overview of European research

Abstract: Detailed knowledge of radio propagation effects is a keystone for the development and performance assessment of mobile communication systems. Although a lot of investigations have already been carried out, there remains a need to gain deeper insight into the complex mechanisms which govern radio propagation. The authors first present a summary of the propagation mechanisms and discuss some issues related to radio channel parameters and measurement techniques. Then a systematic description of the propagation and simulation models developed within various European projects is given. The survey focuses on the main features of these models and the rationale behind their elaboration.

Applications of antenna arrays to mobile communications. I. Performance improvement, feasibility, and system considerations

Abstract: The demand for wireless mobile communications services is growing at an explosive rate, with the anticipation that communication to a mobile device anywhere on the globe at all times will be available in the near future. An array of antennas mounted on vehicles, ships, aircraft, satellites, and base stations is expected to play an important role in fulfilling the increased demand of channel requirement for these services, as well as for the realization of the dream that a portable communications device the size of a wristwatch be available at an affordable cost for such services. This paper is the first of a two-part study. It provides a comprehensive treatment, at a level appropriate to nonspecialists, of the use of an antenna array to enhance the efficiency of mobile communications systems. It presents an overview of mobile communications as well as details of how an array may be used in various mobile communications systems, including land-mobile, indoor-radio, and satellite-based systems. It discusses advantages of an array of antennas in a mobile communications system, highlights improvements that are possible by using multiple antennas compared to a single antenna in a system, and provides details on the feasibility of antenna arrays for mobile communications applications.

Channel parameter estimation in mobile radio environments using the SAGE algorithm

Abstract: This study investigates the application potential of the SAGE (space-alternating generalized expectation-maximization) algorithm to jointly estimate the relative delay, incidence azimuth, Doppler frequency, and complex amplitude of impinging waves in mobile radio environments The performance, ie, high-resolution ability, accuracy, and convergence rate of the scheme, is assessed in synthetic and real macro- and pico-cellular channels The results indicate that the scheme overcomes the resolution limitation inherent to classical techniques like the Fourier or beam-forming methods In particular, it is shown that waves which exhibit an arbitrarily small difference in azimuth can be easily separated as long as their delays or Doppler frequencies differ by a fraction of the intrinsic resolution of the measurement equipment Two waves are claimed to be separated when the mean-squared estimation errors (MSEEs) of the estimates of their parameters are close to the corresponding Cramer-Rao lower bounds (CRLBs) derived in a scenario where only a single wave is impinging The adverb easily means that the MSEEs rapidly approach the CLRBs, ie, within less than 20 iteration cycles Convergence of the log-likelihood sequence is achieved after approximately ten iteration cycles when the scheme is applied in real channels In this use, the estimated dominant waves can be related to a scatterer/reflector in the propagation environment The investigations demonstrate that the SAGE algorithm is a powerful high-resolution tool that can be successfully applied for parameter extraction from extensive channel measurement data, especially for the purpose of channel modeling

A Probabilistic Approach to WLAN User Location Estimation

Abstract: We estimate the location of a WLAN user based on radio signal strength measurements performed by the user’s mobile terminal. In our approach the physical properties of the signal propagation are not taken into account directly. Instead the location estimation is regarded as a machine learning problem in which the task is to model how the signal strengths are distributed in different geographical areas based on a sample of measurements collected at several known locations. We present a probabilistic framework for solving the location estimation problem. In the empirical part of the paper we demonstrate the feasibility of this approach by reporting results of field tests in which a probabilistic location estimation method is validated in a real-world indoor environment.

A statistical modeling approach to location estimation

Abstract: Some location estimation methods, such as the GPS satellite navigation system, require nonstandard features either in the mobile terminal or the network. Solutions based on generic technologies not intended for location estimation purposes, such as the cell-ID method in GSM/GPRS cellular networks, are usually problematic due to their inadequate location estimation accuracy. In order to enable accurate location estimation when only inaccurate measurements are available, we present an approach to location estimation that is different from the prevailing geometric one. We call our approach the statistical modeling approach. As an example application of the proposed statistical modeling framework, we present a location estimation method based on a statistical signal power model. We also present encouraging empirical results from simulated experiments supported by real-world field tests.

A practical path loss model for indoor WiFi positioning enhancement

Abstract: Positioning within a local area refers to technology whereby each node is self-aware of its position. Based on empirical study, this paper proposes an enhancement to the path loss model in the indoor environment for improved accuracy in the relationship between distance and received signal strength. We further demonstrate the potential of our model for the WiFi positioning system, where the mean errors in the distance estimation are 2.3 m and 2.9 m for line of sight and non line of sight environments, respectively.