Sensor Networks-Inspired Low-Power Robust PN Code Acquisition

Algorithmic noise tolerance (ANT) techniques have reduced power consumption in many signal-processing applications, but they typically require an error-free estimator block and do not fully exploit the statistical nature of timing errors. By approaching certain computations as estimation problems, we draw inspiration from sensor networks and develop a novel power conservation scheme in which the main computation result is estimated from multiple potentially erroneous sub-computations. The sub-computations are performed by ";sensors"; and a ";fusion center"; acts as a robust estimator. This scheme is shown to offer significant power savings in a PN code acquisition application.