application of turbo equalization

1. Applications of
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Turbo Equalization
NISHA MENON K
ROLL NO 16
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2. Introduction
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• Data transmission over ISI channels is a classical problem in
communication systems.
• Conventional approaches implement an equalizer to remove
ISI or use MAP or maximum likelihood (ML) detection.
• Data reliability can be enhanced using coding , when the data
is encoded in the transmitter prior to transmission.
• For reasons of complexity of coding, the receiver then
typically performs separate equalization and decoding of the
data.
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• Significant performance gains can be achieved through
joint equalization and decoding at the cost of added
complexity.
• Complexity of joint equalization and decoding can be
reduced by using a technique
called "turbo
equalization" algorithm where detection and
decoding are performed in an iterative fashion.
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4. Turbo Equalization
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o Turbo Codes have aroused much exciting due to their
ability to achieve performance very close to the Shannon
limit at moderate BERs for large enough information
sequence block lengths .
o Extension of the turbo decoding principle to the
equalization process is referred to as Turbo equalization
o Turbo equalization is an iterative equalization and
decoding technique that can achieve equally impressive
performance gains for communication systems.
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Main idea
To improve the receiver performance by
communicating soft information between the
equalizer and the decoder.
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6. Turbo Equalization - Algorithm
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Equalize
Map
Demap
Interleave
Deinterleave
Decode
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7. Turbo Equalization
Turbo
equalization
receiver
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Transmitter
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8. • The turbo equalizer is an iterative receiver which operates the
equalization and decoding processes several times on the same
set of received channel symbols
• The basic principle of turbo equalization is to communicate the
soft information which reflects the reliability of the estimated
encoded bits, between the channel equalizer and the decoder
iteratively.
• Soft information is used instead of hard information in order to
improve the bit error rate performance.
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Principle of Turbo Equalization

9. a priori value
for information
bit
Input LLR
value
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Principle of Turbo Equalization
Extrinsic value
Soft
Input
Soft Output
Algorithm
a posteriori
value for
information bit
A SISO algorithm that processes soft decision inputs and generates soft decision outputs
is the core of iterative algorithm in the coding schemes .
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10. Input
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Block Diagram
SISO equalizer will combine
observations and prior probabilities
to produce aposteriori probabilities
The interleavers are included into
the iterative update loop to further
disperse the direct feedback effect.
The algorithm creates locally highly
correlated output.
These
correlations
between
neighboring symbols are largely
suppressed by the interleaver.
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Performance
The figure shows BER performance improvement upon each iteration of turbo equalizer
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12. o TEQs have been shown to be successful in mitigating the
effects of inter-symbol interference (ISI)
o They are capable of attaining a performance near that
over nondispersive channels.
o They have the potential of mitigating the effects of
channel estimation errors and synchronization errors.
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Advantages

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Applications
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14. Magnetic Recording systems
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Magnetic recording channels may be considered as
communication channels that are severely dispersive in
nature.
Received signal is first equalized to a desired target of
small memory length using a linear filter
PRML detection is then applied to generate the soft or
hard decision estimate of each bit.
As the normalized density increases, PRML detection
incurs more and more loss due to a larger amount of
residual ISI and stronger noise correlation
Turbo equalization (TE) scheme can be proposed, in
which the PRML detector and the decoder exchange
extrinsic soft information between each other.
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Turbo equalization scheme based on lowdensity parity-check (LDPC) coding
suppression of intra-channel
nonlinearities
chromatic dispersion
compensation
polarization-mode dispersion
(PMD) compensation
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• Suppression of fiber nonlinearities in codedmodulation schemes with coherent detection by
using turbo equalization
• Maximum a posteriori probability (MAP) turbo
equalizer based on the sliding-window multilevel BahlCocke-Jelinek-Raviv algorithm is used.
• It is suitable for simultaneous nonlinear and linear
impairment mitigation in multilevel codedmodulation schemes with coherent detection. The
scheme employs LDPC codes as channel codes.
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18. To maximize the uplink throughput in
HSPA
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when transmitted packet is propagated through a
dispersive channel causing self-interference, turbo
equalizers are used at the receiver end
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19. Application in PLNC
In this scheme, A and B take turns to send their message to R in the first two
intervals.
R receives a superposition of modulated signals corresponding to
and
then detect the two messages from the received signal by using turbo
equalization.
.R
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Two terminals A and B desire to exchange information with each other via the
help of an intermediate relay node R.

20. Application in TCM
• Turbo-equalization can be applied to trellis-codedmodulations.
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• The receiver is composed of a symbol detector or an
equalizer realizing soft-output equalization, a
deinterleaver, a soft-input soft-output channel
decoder based on the a posteriori probability (APP)
algorithm.
• A specific computation, iterating probabilities
rather than extrinsic information, allows the
application of turbo equalization to TCM.
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21. Applications
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o Turbo equalization can improve SC-FDMA performance.
as it enhance the transmission over a frequency selective
fading channel.
o Turbo equalization receivers are used for GSM/EDGE
radio access network using QAM modulation for
overcoming the dispersion of a priori information.
o Turbo equalization and iterative (turbo) estimation
techniques are used for packet data transmission
o Turbo equalization can be used for an 8-PSK modulation
scheme in a mobile TDMA communication system
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22. • With each successive iteration channel equalizer and
decoder provides more reliable LLR values which are
associated to the transmitted source bits and encoded bits.
• With increasing number of iteration, it will achieve
significant improvements in BER performance
• Turbo equalizations are mainly used in applications where
ISI is to be removed.
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Conclusion

23. Reference
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[1]Koetter, R.; Singer, A.; Tuchler, M.: Turbo Equalization IEEE Signal
Processing Magazine, vol. 21, no. 1, pp 67-80, Jan 2004
[2]Tüchler, M.; Koetter, R.; Singer, A.: Turbo Equalization: Principles
and New Results IEEE Trans. Communication ., vol. 50, pp. 754-767,
May 2002
[3]Tuchler, M.; Singer, A.; Koetter, R.: Minimum Mean Squared Error
Equalization Using A-priori Information IEEE Trans. Signal Processing,
vol. 50, pp. 673-683, March 2002
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