turbo codes
TRANSCRIPT
Mr. Ravindra Gaikwad
Mr.Utkarsh KumarM.Tech (ECE)
Dept. of Electronics
Pondicherry University
Turbo codes
Outline
• Introduction
– Forward error correction
– Channel capacity
• Turbo codes
– Encoding
– Decoding
– Application
Error correction
• The key idea of FEC is to transmit enough redundant data to allow receiver to recover from errors all by itself. No sender retransmission required.
• The major categories of FEC codes are
– Block codes,
– Cyclic codes,
– Reed-Solomon codes,
– Convolutional codes,
– Turbo codes.
Channel
encoder
m r
• Input message m contains k symbols.
• Encoded message r contains n symbols.
• n > k where extra bits are redundant bits in the codeword.
• The code rate is k/n
Channel capacity
• The channel capacity C of a continuous channel with
bandwidth B Hertz can be perturbed by additive
Gaussian white noise of power spectral density N0/2,
provided bandwidth B satisfies
Where P is transmitted power
ondbitsBN
PBC sec/1log
0
2
Turbo codes
• Turbo codes were proposed by Berrou and Glavieux in
the 1993 International Conference in Communications.
• Performance close to the Shannon Limit.
• Mix between Convolutional and Block codes.
• The best code among FEC codes.
Key elements
• Concatenated Encoders
• Recursive convolutional encoders
• Pseudo-random interleaving
• Iterative Decoding
Concatenated encoding
• Some times single error correction codes are not good
enough for error protection
• Concatenating two or more codes will results more
powerful codes
• Types of concatenated codes
1. Serial concatenated codes
2. Parallel concatenated codes
Parallel concatenated code
RSC
Encoder 1
RSC
Encoder 2
Interleaver
input Systematic output
Parity 1
Systematic output
Parity 2
One systematic and two parity bits are generated from the message stream
Serial concatenated code
Outer
encoderInterleaver
Inner
encoder
Recursive convolutional encoder
mi
• An RSC encoder can be
constructed from a standard
convolutional encoder by
feeding back one of the
outputs.
• In coded system
performance is dominated
by low weight code words.
• A good code will causes low weight output with low
probability
• RSC will produces low weight and low probability
output
Need of interleaver
• Shannon showed that large block-length random codes
achieve channel capacity
• Only a small number of low-weight input sequences
are mapped to low-weight output sequences
• Make the code appear random, while maintaining
enough structure to permit decoding
• The interleaver ensures that the probability that both
encoders have inputs that causes low weight output is
very low.
Turbo decoding
Conv
Decoder1
Interleaver
Deinterleaver
Conv
Decoder2
Systematic
data
Parity 1
Parity 2
Decoding
• Turbo codes get their name because the decoder uses
feedback, like a turbo engine.
• Each decoder estimates the a posteriori probability
(MAP) of each data bit.
• Decoding continues for a set number of iterations.
• Performance generally improves from iteration to
iteration, but follows a law of diminishing returns
• Information exchanged by the decoders must not be
strongly correlated with systematic info or earlier
exchanges.
APPLICATION
• Wireless multimedia
– Data: use large frame sizes
• Low BER, but long latency
– Voice: use small frame sizes
• Short latency, but higher BER
• Combined equalization and error correction decoding.
• Combined multiuser detection and error correction
decoding.
Pros and cons
• Pros
– Remarkable power
efficiency in AWGN
and flat-fading
channels for
moderately low BER.
– Deign tradeoffs
suitable for delivery
of multimedia
services.
• Cons
– Long latency.
– Poor performance at
very low BER.
– Because turbo codes
operate at very low
SNR, channel
estimation and
tracking is a critical
issue.