An Adaptive Parallel Interference Mitigation Technique using Artificial Neural Network in Complementary Coded MC-CDMA
Supreeti Bal, Mritunjay Kumar Rai, Hye-Jin Kim, Rahul Saha · International Journal of Future Generation Communication and Networking · 2018
In Multi-Carrier Code Division Multiple Access (MC-CDMA) method, multiuser detection in fading channel scenario is a major challenge.The scope of this work is to design a multiuser detection technique using Parallel Interference Cancellation (PIC) with Artificial Neural Network (ANN) for multiple access interference mitigation.MC-CDMA with equalization has become popular because it is able to offer better performance than conventional system in frequency selective fading channel.In this paper, performance of PIC with maximum likelihood (ML) equalization is analyzed.For optimizing the output of PIC and reducing the Bit Error Rate (BER) an artificial neural network is used.Feed forward multilayer perceptron model is applied in our proposed method.Simulation results prove that proposed combination of Artificial Neural Network and Parallel Interference Cancellation technique has better multi access interference (MAI) mitigation strength than PIC with ML equalizer.