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Blind coding classification in the presence of interference in MIMO systems using ML algorithm
Author(s) -
AlMakhlasawy Rasha M.,
Hefnawy Alaa A.,
Abd Elnaby Mustafa M.,
Abd ElSamie Fathi E.
Publication year - 2019
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3901
Subject(s) - computer science , mimo , algorithm , kurtosis , rayleigh fading , coding (social sciences) , covariance matrix , blind signal separation , covariance , fading , pattern recognition (psychology) , artificial intelligence , statistics , decoding methods , mathematics , telecommunications , channel (broadcasting)
Summary This paper presents a framework for coding classification in multiple‐input multiple‐output (MIMO) systems in the presence of inter‐user interference (IUI). This framework is performed at the receiver beginning with a signal separation step. The signal separation is implemented with a multi‐user kurtosis (MUK) algorithm. The classification step estimates the code parameter (CP) using the maximum‐likelihood (ML) method applied to the covariance matrix of the received signal without a priori knowledge about the transmitted signal. Experimental results show that the proposed coding classifier is easy to implement and efficient for the classification of the CP over Rayleigh fading channels in the presence of time and frequency offsets. Furthermore, the success rate of code classification is high at low signal‐to‐noise ratios (SNRs). The signal separation increases the probability of true classification.