Partial Parallel Interference Cancellation Multiuser Detection using Recurrent Neural Network Based on Hebb Learning Rule

In CDMA communication systems, in order to decrease the influence on reception performance resulted from incorrect decision of the interference users' information bits in parallel interference cancellation (PIC) process, a recurrent neural network based on Hebb learning rule is designed and applied to adjusting interference cancellation factors (ICF) in partial parallel interference cancellation (PPIC) multiuser detection. Simulation results show that the proposed Hebb-PPIC detection has strong anti-MAI ability and its performance of bit error rate (BER) is improved on the basis of conventional PIC in both conditions of ideal power control and "near-far" scenario.