id: 01454132
dt: j
an: 01454132
au: Mobasseri, B.G.
ti: Digital modulation classification using constellation shape.
so: Signal Process. 80, No.2, 251-277 (2000).
py: 2000
pu: Elsevier Science, Amsterdam
la: EN
cc: 
ut: modulation classification; constellation; digital modulation; shape
    recognition
ci: 
li: doi:10.1016/S0165-1684(99)00127-9
ab: Summary: Constellation diagram is a traditional and powerful tool for
    design and evaluation of digital modulations. In this work we propose
    to use constellation shape as a robust signature for digital modulation
    recognition. We represent the transmitted “information” by the
    geometry of the constellation. Received information is in turn the
    recovered constellation shape that is deformed by noise, channel and
    receiver implementation. We first demonstrate that fuzzy $c$-means
    clustering is capable of robust recovery of the unknown constellation.
    To perform Bayesian inference, the reconstructed constellation is
    modeled by a discrete multiple-valued nonhomogeneous spatial random
    field. For candidate modulations, their corresponding random fields are
    modeled off-line. The unknown constellation shape is then classified by
    an ML rule based on the preceding model building phase. The algorithm
    is applicable to digital modulations of arbitrary size and
    dimensionality.
rv: