|Institution:||University of Texas – Arlington|
|Full text PDF:||http://hdl.handle.net/10106/434|
Prabhu, Vasant A non-linear sub-optimal multiuser detector in the form of parallel interference cancellation (PIC) has been studied. The main objective of this thesis is to develop an analytical model for PIC performance analysis and propose new near-optimum approach. Since the exact performance analysis of PIC is difficult to derive due to its nonlinear decision function, previous work tends to adopt computer simulation method or evaluate through Gaussian approximation (GA) method. For PIC detector, the GA method may not apply since there may exist a dominate interference signal. In addition, the central limit theorem is not applicable to model the residual MAI in the case of PIC due to its own structural property. We develop an analytical model to derive the exact BER performance in the case of two users, and extend the method to approximate cases when moderate-to-high SINR can be encountered. We propose a gradient adaptive parallel interference cancellation detector and investigate its performance. The presented PIC detector is equipped with a set of adaptive weights which are adjusted through a new proposed gradient adaptive step size-LMS (GASS-LMS) algorithm to reduce the cost of wrong interference estimation as existed in the conventional PIC. The initial state is deliberately set based on the function of probability of error to reflect the reliability of the tentative decision from the previous stage. While the most previous work on MUD are restricted to cases where there is no intersymbol interference (ISI), we consider the problem of joint detection of MAI and ISI, which is crucial to enhance the performance of the third and future generation systems with high data rate applications. Simulation results are provided to show that our low complexity joint detector can perform very well, yielding the bit error rate (BER) close to the non-ISI single-user error rate.