Turbo codes.ppt
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Turbo codes.ppt Turbo codes.ppt Presentation Transcript

  • Turbo Codes
    Prasanta Kumar Barik
    Computer Science & Engg.
    Regd No-0701106246
  • Agenda
    Project objectives and motivations
    Channel Coding
    Turbo Codes Technology
    Turbo Codes Performance
    Turbo Coding Application
    Conclusion
  • Communication System
    Structural modular approach
    Various components
    Of defined functions
    Channel
    Coding
    Source
    Coding
    Modulation
    Formatting
    Digitization
    Multiplexing
    Access
    techniques
    send
    receive
  • Channel Coding
    To encode the information sent over a communication
    channel in such a way that in the presence of channel noise, errors can be detected and/or corrected.
    Can be categorized into
    Backward error correction (BEC)
    Forward error correction (FEC )
    Objective: provide coded signals with better distance properties
  • Types of coding
    Block coding
    Convolutional coding: codes differ from block codes in the sense that they do not break the message stream into fixed-size blocks. Instead redundancy is added continuously to the whole stream. The encoder keeps M previous input bits in memory. Each output bit of the encoder then depends on the current input bit as well as the M stored bits.
  • Structured Redundency
    Channel
    encoder
    Input word
    Output word
    n-bit
    k-bit
    codeword
    Code sequence
    Redundancy = (n-k)
    Code rate = k/n
  • A Need for Better Codes
    Energy efficiency vs Bandwidth efficiency
    Codes with lower rate (i.e. bigger redundancy) correctmore errors.then communication system can operate with a lower transmit power, transmit over longer distances, tolerate more interference, use smaller antennas and transmit at a higher data rate. These properties make the code energy efficient.
    low-rate codes have a large overhead and are hence more heavy on bandwidth consumption. Also, decoding complexity grows exponentially with code length.
  • Shannon Theory
    For every combination of bandwidth (W), channel type, signal power (S) and received noise power (N), there is a theoretical upper limit on the data transmission rate R, for which error-free data transmission is possible. This limit is called channel capacity or also Shannon capacity.
    sets a limit to the energy efficiency of a code.
  • A decibel is a relative measure. If E is the actual energy and Eref is the theoretical lower bound, then the relative energy increase in decibels is
     
    .
      Since,  
    A twofold relative energy increase equals 3dB.
     
  • Turbo codes
    Turbo codes are a class of error correcting codes codes introduced in 1993 that come closer to approaching Shannon’s limit than any other class of error correcting codes.
    Turbo codes achieve their remarkable performance with relatively low complexity encoding and decoding algorithms.
  • Turbo Encoder
    RSC
    Input
    Interleaver
    random
    Systematic codeword
    RSC
    X
    Y1
    Y2
  • Recursive Systematic Coders
    Copy of the data in natural order
    Systematic
    Recursive
    S1
    S2
    S3
    Data stream
    Calculated parity bits
  • Interleaver
    The interleaver’s function is to permute low weight code words in one encoder into high weight code words for the other encoder.
    A “row-column” interleaver: data is written row-wise and read columnwise.While very simple, it also provides little randomness.
    A “helical” interleaver: data is written row-wise and read diagonally.
     An “odd-even” interleaver: first, the bits are left uninterleaved and encoded,but only the odd-positioned coded bits are stored. Then, the bits arescrambled and encoded, but now only the even-positioned coded bits arestored. Odd-even encoders can be used, when the second encoder producesone output bit per one input bit.
  • Turbo Decoding
    Criterion
    For n probabilistic processors working together to estimate common symbols, all of them should agree on the symbols with the probabilities as a single decoder could do
  • Turbo Decoder
  • Turbo Decoder
    • The inputs to the decoders are the Log likelihood ratio (LLR) for the individual symbol d.
    • LLR value for the symbol d is defined ( Berrou) as
  • Turbo Decoder
    The SISO decoder reevaluates the LLR utilizing the local Y1 and Y2 redundancies to improve the confidence
    • The value z is the extrinsic value determined by the same decoder and it is negative if d is 0 and it is positive if d is 1
    • The updated LLR is fed into the other decoder and which calculates the z and updates the LLR for several iterations
    • After several iterations , both decoders converge to a value for that symbol.
  • Turbo Decoding
    Compare the LLR output, to see if the estimate is towards 0 or 1 then take HD
  • How Do they Work (© IEEE spectrum)
  • How Do they Work (© IEEE spectrum)
  • Turbo Codes Performance
  • Turbo Codes Applications
    Deep space exploration
    Mobile 3G systems
    In use in Japan
    UMTS
  • Conclusion : End of Search
    Turbo codes achieved the theorical limits with small gap
    Give rise to new codes : Low Density Parity Check (LDPC)
    Need
    Improvements in decoding delay
  • Reference
    http://www.google.com
    [2] University of South Australia, Institute for Telecommunications Research,Turbo coding research group. http://www.itr.unisa.edu.au/~steven/turbo/.
    [3] S.A. Barbulescu and S.S. Pietrobon. Turbo codes: A tutorial on a new class of powerful error correction coding schemes. Part I: Code structures and interleaverdesign. J. Elec. and Electron.Eng., Australia, 19:129–142, September 1999.
  • Thank You…..