Cryptography Reference
In-Depth Information
establish a theoretical expression for the coecients of the equalizer, explicitly
taking into account the presence of
a priori
information on the transmitted
data. This progress has proved to be particularly interesting for packet mode
transmissions, in which the coecients of the equalizer are precalculated once
from an estimation of the impulse response of the channel, and applied to the
whole received block.
MMSE turbo equalization relies on a soft-input soft-output linear equaliza-
tion scheme optimized according to the MMSE criterion. This type of equalizer
is also sometimes known as a "linear MMSE equalizer with
a priori
information"
in the literature. This section describes the principle of this equalizer, assuming
that we know the parameters of the channel, which enables the filter coecients
to be calculated directly. Its implementation in adaptive form is also discussed.
We next present some examples of MMSE turbo equalizer performance, and we
describe the (
Digital Signal Processor
, or DSP) implementation of this solution.
This part ends with a reflection on the potential applications of MMSE turbo
equalization.
Principle of soft-input soft-ouput linear MMSE equalization
Generally, the linear soft-input soft-output MMSE equalizer can formally be
decomposed into three main functions (Figure 11.14).
Figure 11.14 - Soft-input soft-output linear equalizer optimized according to the
MMSE criterion.
1. The first operation, the SISO mapping, calculates a soft estimate for the
transmitted symbols, denoted
x
=(
x
0
, ..., x
N−
1
)
,fromthe
a priori
in-
formation
L
a
(
x
)
coming from the decoder at the previous iteration.
2. The linear equalizer then uses estimated data
x
i
to rebuild and cancel the
ISI affecting the received signal. The resulting signal is filtered in order
to eliminate residual interference. The filter coecients are optimized so
as to minimize the mean square error between the equalized data and
