Theoretical bound on modulation classification for multiple-input multiple-output (MIMO) systems over unknown, flat fading channels

Document Type

Conference Proceeding

Publication Date

4-15-2015

Abstract

Likelihood-based algorithms identify the modulation of the transmitted signal based on the computation of the likelihood function of received signals under different hypotheses (modulation formats). An important class of likelihood-based algorithms for modulation classification problems first treats the unknown channels as deterministic, and replaces the channels by their estimates. In this paper, a novel theoretical bound on the performance of this class of algorithms is proposed for multiple-input multiple-output (MIMO) systems over unknown, flat fading channels. The performance bound is developed from the Cramer-Rao bound (CRB) of blind channel estimation. It provides a useful benchmark against which it is possible to compare the performance of modulation classification algorithms, and is tighter than the theoretical bound derived based on perfect channel knowledge.

Identifier

84929208614 (Scopus)

ISBN

[9781479984282]

Publication Title

2015 49th Annual Conference on Information Sciences and Systems Ciss 2015

External Full Text Location

https://doi.org/10.1109/CISS.2015.7086878

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