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Paper Presentation Channel Coding and Transmission Aspects for Wireless Multimedia

Paper Presentation Channel Coding and Transmission Aspects for Wireless Multimedia. Authors: Joachim Hagenauer, Thomas Stochhammer Source: Proceedings of the IEEE , Volume: 87 Issue: 10 , Oct 1999, pp. 1764 -1777 Originally Presented by Hong Hong Chang, Feb 17, 2003. Overview. Introduction

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Paper Presentation Channel Coding and Transmission Aspects for Wireless Multimedia

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  1. Paper PresentationChannel Coding and Transmission Aspects for Wireless Multimedia Authors: Joachim Hagenauer, Thomas Stochhammer Source: Proceedings of the IEEE , Volume: 87 Issue: 10 , Oct 1999, pp. 1764 -1777 Originally Presented by Hong Hong Chang, Feb 17, 2003

  2. Overview • Introduction • System Architecture • The Links between Source and Channel Coding • RCPC, UEP • PCM Transmission example • Transmission (C) 2005 by Yu Hen Hu

  3. Wireless Channel • Multipath fading • Doppler spreading • Effect of distance • Quite noisy • High BER • average error rates up to 10% • Channel coding is necessary http://www.wireless.per.nl:202/multimed/cdrom97/indoor.htm (C) 2005 by Yu Hen Hu

  4. Source Coding & Channel Coding (I) • Shannon’s separation theorem • source coding - long blocks of source symbols • channel coding -a sequence of random block codes with infinite length • Infinite delay data Source Coding Channel Coding Modulation transmission (C) 2005 by Yu Hen Hu

  5. Source Coding & Channel Coding (II) • Shannon’s separation theorem is no longer applicable • short blocks, small delays • Combined and joint source and channel coding • MPEG II audio layer • Source-controlled channel decoding • Uses the residual redundancy of the uncompressed or partly compressed source data to improve channel decoding (C) 2005 by Yu Hen Hu

  6. Transmissions - Two Kinds of Data Channels • Mode 1 • Error free delivery • Using ARQ • Delay and bit throughput rate (BTR) vary according to the channel conditions • Mode 2 • Guarantees constant bit rate and delay • Errors occur (C) 2005 by Yu Hen Hu

  7. System for Transmission of Multimedia Applications over Mobile Channels S C M A C M A M A (C) 2005 by Yu Hen Hu

  8. Application Properties • Delay-sensitive applications • Speech, video telephony • Use frequent resynchronization, reduced predictive coding • No ARQ, deep interleaving or long block codes • BTR-sensitive applications • Audio, video • Use bidirectional predictive coding, long term rate control algorithms • Might use error protection interleaving, serial or parallel concatenated coding or ARQ to exploit the provided bandwidth as optimally as possible (C) 2005 by Yu Hen Hu

  9. Application Properties (Cont) • BER-sensitive applications • Data • Error-free delivery • Use ARQ, FEC (C) 2005 by Yu Hen Hu

  10. Multimedia Transmission • Each application may request different QoS • All application are combined into one single transmission stream • New layer necessary for multimedia transmission Adaptation Layer Multiplex Layer (C) 2005 by Yu Hen Hu

  11. Adaptation Layer and Multiplex Layer • Adaptation layer • Adapt the requesting upper application to transmission condition according to the required QoS • Have tools for error detection, error correction, bit reordering, retransmission protocols • Multiplex layer • Multiplex the adaptation layer bit streams or packets into one single bit steam • Optimizing the throughput, minimize misdeliveries (C) 2005 by Yu Hen Hu

  12. Transmission Scheme over a Mobile Channel (C) 2005 by Yu Hen Hu

  13. Links between Source Coding and Channel Coding • Channel State Information (CSI) • Connected by soft decision of demodulator/detector • Soft decision gains 2-3dB • Source Significant Information (SSI) • For unequal error protection (UEP) • Rate-compatible punctured convolutional code (RCPC) • Decision Reliability Information (DRI) • Soft output from channel decoder • Source a priori/a posteriori information (SAI) • probability of next bit, correlation • Reduce channel decoder error rate (C) 2005 by Yu Hen Hu

  14. Rate-Compatible Punctured Convolutional Code for Unequal Error Protection • Start with a rate 1/n0linear convolutional code • Encode k input bits to produce n0k output bits • Delete n0k−n bits from the output bits • The code rate is • The corresponding n0k perforation matrix has n ones and n0k−n zeros http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  15. Punctured Convolutional Code Example http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  16. Puncture Pattern and Perforation Matrix http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  17. Rate Compatible Convolutional Code 2/3 2/3 http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  18. Rate Compatible Punctured Convolutional Code • A family of punctured codes are rate compatibleif the codeword bits from the higher-rate code are embedded in the lower rate codes. • The zeros in perforation matrices of the lower rate codes are also the zeros in the perforation matrices of the higher rate • The ones in in perforation matrices of the higher rate codes are also ones in in perforation matrices of the lower rate codes. http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  19. RCPC Example http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

  20. Recursive Systematic Encoder Structure • Memory M=4 , Mother code rate = ½, Puncturing rate = 8/12 • Nonsystematic vs Systematic G(D) = (1+D3+D4, 1+D+D2+D4, 1+D2+D3+D4) Gs(D) = (C) 2005 by Yu Hen Hu

  21. Error Probability Upper Bound • df– free distance, the minimum distance of any path from the correct path • cd– the sum of all information weights on all wrong path of distance d starting inside one puncturing period • Pd – the pairwise error probability of two code sequences at distance d (C) 2005 by Yu Hen Hu

  22. Puncturing Table (C) 2005 by Yu Hen Hu

  23. Comparison of systematic recursive convolutional code with nonsystematic codes (C) 2005 by Yu Hen Hu

  24. Encoder & Decoder • Encoder • Puncture • Repeat – replacing “1” by “2” or any higher integer in the puncturing tables • Decoder • Punctured bits are stuffed with zeros • Repeated bits are combined by adding soft values • Header of frame contains the coding rate information of payload • Easily adapted to multimedia and channel requirements via puncturing control (C) 2005 by Yu Hen Hu

  25. BER Performance of Systematic Recursive PCPC code (C) 2005 by Yu Hen Hu

  26. Soft-In/Soft-Out Decoding • Decoding algorithm • Viterbi (VA) • Maximum-a-posteriori-probability-symbol-by-symbol (MAP) • VA and MAP can accept soft values • Source a priori information • Channel state information • VA and MAP can deliver soft outputs (C) 2005 by Yu Hen Hu

  27. PCM Transmission example - EEP • Analog source • Source coding: m-bit linear quantization (m=20) • Quantized sample • smaller k -> more important. • Transmission distortion • equal Pbfor all k=1,2,…,m (C) 2005 by Yu Hen Hu

  28. PCM Transmission Example – Applying Soft Bits • CSI is transformed to a DRI and directly passed to the source decoder. Thus, λ(x) (soft value) is obtained • Reconstructed PCM value • Gain of about 1.6dB in SNRPCM (C) 2005 by Yu Hen Hu

  29. PCM Transmission Example – Apply Channel Coding • m=10 • m is smaller, quantization noise increases • Channel coding rate = ½ • RCPSRC 8/16 • Improves total performance (C) 2005 by Yu Hen Hu

  30. PCM Transmission Example – UEP • Let all bits contribute the same transmission distortion. Then, • Small k, small Pb • Use this information for unequal error-protection design • Require that transmission distortion of each bit is smaller than quantization distortion. We have (C) 2005 by Yu Hen Hu

  31. PCM Transmission Example: RCPSRC code for UEP • Employ • the upper bound for the bit error probability • Distance spectra of puncture table • Obtain a certain rate R(k) for each bit class at different channel SNR • Rate distribution for PCM Transmission (C) 2005 by Yu Hen Hu

  32. PCM Transmission Example - Simulation Results (C) 2005 by Yu Hen Hu

  33. Approaches to Improve the Transmission of Multimedia I. Error Resilient Source Coding • Fixed length coding • more stable against channel error • MPEG-4 error resilient mode • Space the Resync markers evenly throughout the bit stream • All predictively encoded information is confined within one video packet to prevent the propagation of errors (C) 2005 by Yu Hen Hu

  34. II. Improved Receiver Algorithms • European Digital Satellite TV-Broadcasting standard • MPEG-2 based source coding • Concatenated coding scheme • Error-concealment techniques based on temporal, spatial, frequency • Joint-source channel coding • Instead of remove residual redundancy by using VLC, keep it and use it at the receiver side to achieve more reliable decoding • Soft source decoding (C) 2005 by Yu Hen Hu

  35. III. Source Adapted UEP • RCPC • Application to GSM speech • Turbo Code • Channel coding is applied according to the bit sensitivity • Application to hierarchical video broadcast • Base layer and enhancement layer (C) 2005 by Yu Hen Hu

  36. IV. Channel Adapted Combined Source-Channel Coding Methods • Goal • Allocate bit rates in an optimal way between source and channel encoders as the source and channel vary • Minimize end-to-end distortion • Feed back the CSI from the decoder to the encoder on a reverse channel (C) 2005 by Yu Hen Hu

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