Journal of the Association of Engineers, India

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Minimization of Error in Two Diversity Channels with Uncorrelated Gaussian Variables in Binary Communication System


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1 Birbhum Institute of Engineering and Technology, Suri, Birbhum-731101, India
     

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The performance of a binary digital system in the presence of an uncorrelated Gaussian variable is considered here. The mean square value or expectation of the uncorrelated variables has zero mean and square ischolar_main of spread of the distributed function with respect to these variables is variance of the noise components. On the basis of linear combination of two received signals one have to detect the value of controlled parameter, k optimally so that the probability of error should be minimized in the total binary communication system.

Keywords

Gaussian Variables, Error Function, Q Function, Variance, Optimum Detection.
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  • Minimization of Error in Two Diversity Channels with Uncorrelated Gaussian Variables in Binary Communication System

Abstract Views: 429  |  PDF Views: 4

Authors

Nirmalya Chandra
Birbhum Institute of Engineering and Technology, Suri, Birbhum-731101, India
Nilangshu Chattopadhyay
Birbhum Institute of Engineering and Technology, Suri, Birbhum-731101, India
Arghya Sen
Birbhum Institute of Engineering and Technology, Suri, Birbhum-731101, India
Alik Kumar Ghosh
Birbhum Institute of Engineering and Technology, Suri, Birbhum-731101, India

Abstract


The performance of a binary digital system in the presence of an uncorrelated Gaussian variable is considered here. The mean square value or expectation of the uncorrelated variables has zero mean and square ischolar_main of spread of the distributed function with respect to these variables is variance of the noise components. On the basis of linear combination of two received signals one have to detect the value of controlled parameter, k optimally so that the probability of error should be minimized in the total binary communication system.

Keywords


Gaussian Variables, Error Function, Q Function, Variance, Optimum Detection.

References





DOI: https://doi.org/10.22485/jaei%2F2017%2Fv87%2Fi1-2%2F158488