Turbo equalization

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Turbo equalization

  1. 1. Applications of 6-Dec-13 Turbo Equalization NISHA MENON K ROLL NO 16 1
  2. 2. Introduction 6-Dec-13 • 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. 2
  3. 3. 6-Dec-13 • 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. 3
  4. 4. Turbo Equalization 6-Dec-13 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. 4
  5. 5. 6-Dec-13 Main idea To improve the receiver performance by communicating soft information between the equalizer and the decoder. 5
  6. 6. Turbo Equalization - Algorithm 6-Dec-13 Equalize Map Demap Interleave Deinterleave Decode 6
  7. 7. Turbo Equalization Turbo equalization receiver 6-Dec-13 Transmitter 7
  8. 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. 8 6-Dec-13 Principle of Turbo Equalization
  9. 9. a priori value for information bit Input LLR value 6-Dec-13 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 . 9
  10. 10. Input 6-Dec-13 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. 10
  11. 11. 6-Dec-13 Performance The figure shows BER performance improvement upon each iteration of turbo equalizer 11
  12. 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. 12 6-Dec-13 Advantages
  13. 13. 6-Dec-13 Applications 13
  14. 14. Magnetic Recording systems 6-Dec-13 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. 14
  15. 15. 15 6-Dec-13
  16. 16. 6-Dec-13 Turbo equalization scheme based on lowdensity parity-check (LDPC) coding suppression of intra-channel nonlinearities chromatic dispersion compensation polarization-mode dispersion (PMD) compensation 16
  17. 17. 6-Dec-13 • 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. 17
  18. 18. To maximize the uplink throughput in HSPA 6-Dec-13 when transmitted packet is propagated through a dispersive channel causing self-interference, turbo equalizers are used at the receiver end 18
  19. 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 19 6-Dec-13 Two terminals A and B desire to exchange information with each other via the help of an intermediate relay node R.
  20. 20. Application in TCM • Turbo-equalization can be applied to trellis-codedmodulations. 6-Dec-13 • 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. 20
  21. 21. Applications 6-Dec-13 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 21
  22. 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. 22 6-Dec-13 Conclusion
  23. 23. Reference 6-Dec-13 [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 23
  24. 24. 24 6-Dec-13

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