Soft Information in Interference
Cancellation Based Multiuser Detection
July 2005
Jerome M. Shapiro, The MITRE Corporation
James Dunyak, The MITRE Corporation
ABSTRACT
This paper considers soft information in interference cancellation
based multiuser detection algorithms. For the case of binary phase-shift
keying (BPSK) modulation, a relationship between the soft information
as provided by the log likelihood ratio (LLR) and the minimum mean-square
error (MMSE) bit estimates is derived, whereby the bit estimate is given
by the hyperbolic tangent of one-half the LLR. Although this result
is known for Gaussian channels, we show that this result holds true
regardless of the underlying channel distribution. Similar relationships
are derived for quadrature phase-shift keying (QPSK) and also for more
general constellations. Results for multiuser detection (MUD) are then
derived. Starting with an analysis of the convergence dynamics, what
follows is an analysis of four canonical iterative MUD algorithms that
fit within the framework: parallel vs. serial interference cancellation
and symbol-level vs. chip-level updates. The results help explain why
chip-level algorithms lead to faster convergence for a given amount
of computation than do symbol-level algorithms, even though the chip-level
algorithms never explicitly calculate the matched filter that is known
to be a sufficient statistic. Finally, an efficient computational structure
for a MUD processing element for the chip-level parallel interference
cancellation (CPIC) is derived as a one-chip ahead prediction.
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