Pre-processed back propagation neural networks for CDMA interference cancellation

Author

Geevarghese, B. ; Thomas, Julian ; Anil, Mehmet Ali ; Francis, Ashish

Author_Institution

Ambedkar Univ., Muzaffarpur, India

fYear

2013

fDate

25-26 March 2013

Firstpage

100

Lastpage

103

Abstract

This paper attempts to show the effects of pre-processing in bit error rate of neural network interference cancellation in spread spectrum receivers. Multiple access interference (MAI) which is one of the primary issues in CDMA multiuser detection is combated by interference cancellers. Feed-Forward Neural Networks with back propagation is used for interference cancellers. The works shows that pre-processing can bring adequate improvement in bit error rate as well as complexity.

Keywords

backpropagation; code division multiple access; error statistics; feedforward neural nets; interference suppression; multiuser detection; radio receivers; spread spectrum communication; telecommunication computing; CDMA multiuser detection; bit error rate; feedforward neural networks; interference cancellers; multiple access interference; neural network interference cancellation; preprocessed back propagation neural networks; spread spectrum receivers; Biological neural networks; Bit error rate; Interference cancellation; Multiaccess communication; Receivers; Back Propagation Algorithm; Bit Error Rate; Code Division Multiple Access; Neural network; Pre-processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference on

Conference_Location

Tirunelveli

Print_ISBN

978-1-4673-5037-2

Type

conf

DOI

10.1109/ICE-CCN.2013.6528472

Filename

6528472