Smart Multistage Partial Parallel Interference Cancellation Estimator for DS/CDMA System

摘要

A conventional DS/CDMA system treats each user separately as a signal, with other users considered as noise or Multiple Access Interference (MAI). Due to random time offset between signals, it is impossible to design the code waveforms to be completely orthogonal. The conventional detector does not take into account the existence of MAI. MAI is a factor which limits the capacity and performance of DS/CDMA system. Parallel Interference Cancellers (PIC) simultaneously subtract off all of the users' signals from all of the others. The spectral efficiency E_(eff) and energy efficiency (reception sensitivity) are measures of SS techniques. The value of (E_b/N_0) to obtain a specified Bit Error Rate (BER) (～ 10~(-9)). In DS system code weight determines the error rate. PIC is one of nonlinear multiuser detection approaches which try to improve performance at the cost of low computing complexity and short processing delay. Artificial Neural Network (ANN) mechanism for the interference cancellation in a direct sequence code-division multiple access (DS/ CDMA) communication system is proposed here. The proposed ANN architecture for multistage PIC is trained as Multiple Access Interference (MAI) detector to improve the performance of a multistage PIC. To facilitate performance comparison of proposed model with traditional and other methods a Graphical User Interface (GUI) is designed which enables user to flexibly perform interactive tasks of studying and compare the methods in terms of their performance.