National Aeronautics and Space Administration (NASA) is investigating cognitive technologies for their future communication architecture. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK), and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite - Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Modulation classification of satellite communication signals using cumulants and neural networks


    Contributors:


    Publication date :

    2017-06-01


    Size :

    695293 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Spiking Neural Networks for Detecting Satellite Internet of Things Signals

    Dakic, Kosta / Al Homssi, Bassel / Walia, Sumeet et al. | IEEE | 2024


    Passive Maritime Surveillance Using Satellite Communication Signals

    Stove, Andrew G. / Gashinova, Marina S. / Hristov, Stanislav et al. | IEEE | 2017

    Free access

    Noise subspace techniques in non-gaussian noise using cumulants

    Sadler, B.M. / Giannakis, G.B. / Shamsunder, S. | IEEE | 1995