Abstract

Multiuser detection deals with demodulation of mutually interfering digital streams in digital communications. Multiple Access Interference (MAI) presents a major obstacle to reliable communications in Code Division Multiple Access (CDMA) systems. This fact results in a user capacity limit for CDMA systems in the sense that there exists a maximum number of users that can simultaneously communicate over the channel for specified level of performance. Over the years, researchers explored different methods of Multiuser Detection (MUD) to overcome the channel capacity limitation. In this thesis, we have investigated through various techniques of Iterative (Turbo) MUD that employ channel encoder/decoders, with different performance/complexity trade-off. We have developed the idea of concatenating two effective techniques, which are Partial Parallel Interference Cancellation (PPIC) and updated Decorrelating Detector (DD). By deriving appropriate formulas, we have been able to achieve a better performance/complexity trade-off in comparison to the other competing methods such as Serial Interference Cancellation (SIC), Parallel interference Cancellation (PIC), and single DD. Our proposed algorithm uses tentative soft-decisions at both of the multiple PPIC stages and input of the updated DD, to produce the most reliably estimated received data for the MAI cancellation and data detection. Simulation results are given for a multitude of different situations to demonstrate the performance of our proposed algorithm over the other traditional methods. Moreover, at medium to high Signal to Noise Ratio (SNR), the destructive effects of MAI can almost be overcome by iterative processing, and single-user performance can be achieved for the channels with medium cross-correlation.