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Abstract:
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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. |
