Authors: Joachim Hagenauer, Thomas Stochhammer 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 System Architecture The Links between Source and Channel Coding RCPC, UEP PCM Transmission example Transmission (C) 2005 by Yu Hen Hu

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

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

Source Coding & Channel Coding (II) Shannon’s separation theorem is no longer applicable short blocks, small delays Combined and joint source and channel coding MPEG II audio layer Source-controlled channel decoding Uses the residual redundancy of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

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

System for Transmission of Multimedia Applications over Mobile Channels (C) 2005 by Yu Hen Hu

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

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

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

Adaptation Layer and Multiplex 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

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

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

Rate-Compatible Punctured Convolutional Code for Unequal Error Protection Start with a rate 1/n0 linear 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

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

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

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

Rate Compatible Punctured Convolutional Code A family of punctured codes are rate compatible if 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

RCPC Example Note that the rates are progressive. So that the amount of FEP can be adapted to different importance of the content. http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf (C) 2005 by Yu Hen Hu

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

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

Puncturing Table Rate Table df d df +1 df +2 8/10 3 cd ad 14 5 138 41 11111111 10010000 00000000 3 cd ad 14 5 138 41 1114 276 8/12 11010010 4 10 81 22 307 74 8/14 11011110 1 82 126 29 8/16 7 64 16 96 24 128 32 (C) 2005 by Yu Hen Hu

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

Encoder & Decoder Encoder Decoder 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

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

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

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

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

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

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

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

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

Approaches to Improve the Transmission of Multimedia I 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

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

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

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