| Summary: | Multiuser Detection (MUD) receiver techniques leverage the signal structure of overlapping transmissions to reduce inter-user interference and improve system performance. One main application for MUD research has been reducing inter-user interference in Code-Division Multiple Access (CDMA) channels with performance degradation caused by the near-far effect. In this thesis, we explore MUD techniques for the case where two co-channel, synchronous users use digital modulations and CDMA is not used. We present three different MUD methods for demodulation and examine the tradespace between performance and complexity. We first examine the Optimal MUD algorithm. The modeling technique of virtual constellations is used to apply the single user maximum likelihood (ML) detector to two synchronous users sharing a common pulse shape and to assess and understand performance. We show how, in some cases, Optimal MUD can be used to enable near single-user performance in the presence of a strong interferer. We also identify cases where the interferer’s signal causes a significant increase in error rates, due to the interactions of the two users’ constellations, and how the phase difference between the two users can greatly vary the shape of the performance curves. The complexity of Optimum MUD motivates our investigation of Successive Interference Cancellation (SIC), a reduced complexity MUD algorithm. For some cases, the performance of SIC is equivalent to Optimum MUD. However, in other cases, an increase in phase difference between the two signals causes the performance of the two algorithms to diverge. To handle the cases where the performance of SIC is unacceptable, we develop the Hybrid Method (HM) algorithm. The HM algorithm is a two stage, reduced complexity algorithm that evaluates a subset of virtual constellation points. We showed how for a small increase in complexity, the HM algorithm achieves comparable performance to Optimum MUD in the cases where SIC performs poorly. This performance and complexity analysis provides insights into the tradeoffs between these three algorithm approaches for MUD system design. These results can be applied to the design of future multiuser communications systems where the best MUD algorithm, one that best balances complexity with performance, is chosen based on channel estimates.
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