Compressive Higher Order Cyclostationary Statistics
نویسندگان
چکیده
The application of nonlinear transformations to a linearly modulated communication signal for the purpose of revealing hidden periodicities has proven to be useful for automatic modulation recognition (AMR). The fact that the hidden periodicities, referred to as Higher Order Cyclostationary Statistics (HOCS), are compressible in the Fourier domain motivates the use of compressive sensing (CS) as an efficient acquisition protocol for capturing such signals. In this work, we consider the task of performing AMR when CS is used to acquire the communication signal. We develop a theoretical framework for estimating HOCS using the low-rate nonuniform sampling protocol from CS and validate our theory using simulated data.
منابع مشابه
Technical Report: Compressive Temporal Higher Order Cyclostationary Statistics
The application of nonlinear transformations to a cyclostationary signal for the purpose of revealing hidden periodicities has proven to be useful for applications requiring signal selectivity and noise tolerance. The fact that the hidden periodicities, referred to as cyclic moments, are often compressible in the Fourier domain motivates the use of compressive sensing (CS) as an efficient acqui...
متن کاملCHOCS: A Framework for Estimating Compressive Higher Order Cyclostationary Statistics
The framework of computing Higher Order Cyclostationary Statistics (HOCS) from an incoming signal has proven useful in a variety of applications over the past half century, from Automatic Modulation Recognition (AMR) to Time Difference of Arrival (TDOA) estimation. Much more recently, a theory known as Compressive Sensing (CS) has emerged that enables the efficient acquisition of high-bandwidth...
متن کاملDetection & Estimation of Covert Ds/ss Signals Using Higher Order Statistical Processing
Conventional linear and non-linear receivers are generally ineffective in detecting direct-sequence spread spectrum (DS/SS) signals if the spreading sequences are unavailable. An investigation into using correlation-based processing is reported showing that the cyclostationary property of DS/SS provides detection capability. Finally we describe with results an emerging technique based on higher...
متن کاملSpatio Temporal Blind Identification of Fir Channels for Multiple Users
A new method is proposed for blind identi cation of possibly nonminimumphase FIR channels with multiple users The technique exploits the structure of the signals received by an antenna array in both the temporal and spatial frequency domains Although in the single an tenna case it is necessary to use cyclostationary signals or higher order statistics to identify the magnitude and phase of the c...
متن کاملBlind source-separation using second-order cyclostationary statistics
This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast funct...
متن کامل