LCMV beamforming for a novel wireless local positioning system: A stationarity analysis

In this paper, we discuss the implementation of Linear Constrained Minimum Variance (LCMV) beamforming (BF) for a novel Wireless Local Position System (WLPS *). WLPS main components are: (a) a dynamic base station (DBS), and (b) a transponder (TRX), both mounted on mobiles. WLPS might be considered as a node in a Mobile Adhoc NETwork (MANET). Each TRX is assigned an identification (ID) code. DBS transmits periodic short bursts of energy which contains an ID request (IDR) signal. The TRX transmits back its ID code (a signal with a limited duration) to the DBS as soon as it detects the IDR signal. Hence, the DBS receives non-continuous signals transmitted by TRX. In this work, we assume asynchronous Direct-Sequence Code Division Multiple Access (DS-CDMA) transmission from the TRX with antenna array/LCMV BF mounted at the DBS, and we discuss the implementation of the observed signal covariance matrix for LCMV BF. In LCMV BF, the observed covariance matrix should be estimated. Usually sample covariance matrix (SCM) is used to estimate this covariance matrix assuming a stationary model for the observed data which is the case in many communication systems. However, due to the non-stationary behavior of the received signal in WLPS systems, SCM does not lead to a high WLPS performance compared to even a conventional beamformer. A modified covariance matrix estimation method which utilizes the cyclostationarity property of WLPS system is introduced as a solution to this problem. It is shown that this method leads to a significant improvement in the WLPS performance.