Open Access

LCMV Beamforming for a Novel Wireless Local Positioning System: Nonstationarity and Cyclostationarity Analysis

EURASIP Journal on Advances in Signal Processing20072007:098243

https://doi.org/10.1155/2007/98243

Received: 24 June 2006

Accepted: 21 May 2007

Published: 26 June 2007

Abstract

This paper investigates the implementation of a novel wireless local positioning system (WLPS). WLPS main components are: (a) a dynamic base station (DBS) and (b) a transponder, both mounted on mobiles. The DBS periodically transmits ID request signals. As soon as the transponder detects the ID request signal, it sends its ID (a signal with a limited duration) back to the DBS. Hence, the DBS receives noncontinuous signals periodically transmitted by the transponder. The noncontinuous nature of the WLPS leads to nonstationary received signals at the DBS receiver, while the periodic signal structure leads to the fact that the DBS received signal is also cyclostationary. This work discusses the implementation of linear constrained minimum variance (LCMV) beamforming at the DBS receiver. We demonstrate that the nonstationarity of the received signal causes the sample covariance to be an inaccurate estimate of the true signal covariance. The errors in this covariance estimate limit the applicability of LCMV beamforming. A modified covariance matrix estimator, which exploits the cyclostationarity property of WLPS system is introduced to solve the nonstationarity problem. The cyclostationarity property is discussed in detail theoretically and via simulations. It is shown that the modified covariance matrix estimator significantly improves the DBS performance. The proposed technique can be applied to periodic-sense signaling structures such as the WLPS, RFID, and reactive sensor networks.

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Authors’ Affiliations

(1)
Department of Electrical and Computer Engineering, Michigan Technological University

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Copyright

© Hui Tong et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.