Wireless Synchronization Preamble Detection Scheme Using Bispectra-Based Statistics in the Presence of Stationary Noise

Abstract

Higher-order statistical analysis has been applied in many areas of communication systems, such as blind equalization, pattern recognition and channel estimation; among others. In this paper, wireless preamble sequences in additive noise are processed to reduce the signal to noise ratio of synchronization signals thereby improving interconnectivity. For such end, detection structures using matched filtering in the form of passive implementation along with cumulant-based processing are proposed. A framework based on bispectra is used to obtain the probability of detection confirming successful synchronization in the presence of Gaussian and non-Gaussian noise. Signal bispectra and power of the tests are estimated over a number of samples within the length of standard wireless preamble signals.