Abstract—Reduction of multiple access interference is
occupying great importance in wireless communication using
code division multiple access (CDMA). Different interference
cancellation schemes were developed and neural network based
canceller is one of them. This paper introduces the effect of
training parameters on achieving optimum performance on a
multi stage parallel interference canceller (PIC) based on
neural network.
Index Terms—BER, CDMA, LM algorithm, neural network.
Jahan Rosemary Joseph is with the Baselios Thomas I Catholicose
College of Engineering and Technology, Kerala, India (e-mail:
jahanrosemary@ gmail.com).
Anish Francis is with the Kerala State Electricity Board(KSEB), Kerala,
Ind ia. (e-mail: anishfran@gmail.com).
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Cite:Jahan Rosemary Joseph and Anish Francis, "Effects of Training Parameters on Neural Network Parallel
Interference Canceller for CDMA," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 548-550, 2013.
