Small-Sample-Support Suppression of Interference to PN-Masked Data

In the context of secure wireless communications, pseudo-noise (PN) masking of transferred data has proven to be an effective technique against eavesdropping (notable examples are military-grade communication and global-positioning systems). At the same time, PN-masked transmissions are thought to be vulnerable to interference/jamming due to lack of a minimum-mean-square-error (MMSE) disturbance suppressing solution. In this paper, for the first time we establish the MMSE operation for masked data in the form of a time (mask) varying linear filter, suggest an implementation that avoids repeated input autocorrelation matrix inversion, and develop an auxiliary-vector (AV) MMSE filter estimator with state-of-the-art short-data-record estimation performance. Simulation examples included herein illustrate the theoretical developments.