Digital Signal Processing Computing Algorithms: An Overview
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Transcript Digital Signal Processing Computing Algorithms: An Overview
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
ECE738 Advanced Image Processing
Overview
• Introduction
• System Architecture
• The Links between Source and Channel
Coding
– RCPC, UEP
– PCM Transmission example
• Transmission
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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
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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
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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• Shannon’s separation theorem is no longer
applicable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
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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
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System for Transmission of Multimedia
Applications over Mobile Channels
S
C
M
C
M
M
A
A
A
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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
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Application Properties (Cont)
• BER-sensitive applications
– Data
– Error-free delivery
– Use ARQ, FEC
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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
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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
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Transmission Scheme over a
Mobile Channel
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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
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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
k
k
n 0k n 0k n n
• The corresponding n0k perforation matrix has n
ones and n0k−n zeros
http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf
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Punctured Convolutional Code Example
http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf
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Puncture Pattern and Perforation Matrix
http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf
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Rate Compatible Convolutional Code
2/3
2/3
http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf
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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
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RCPC Example
http://www.ee.byu.edu/ee/class/ee685/lectures/lecture37.pdf
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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)
2
4
2
3
4
1
D
D
D
1
D
D
D
Gs(D) = 1,
,
3
4
3
4
1
D
D
1
D
D
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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
1
Pb d d cd Pd
f
P
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Puncturing Table
Rate
Table
df
d
df
df +1
df +2
8/10
11111111
10010000
00000000
3
cd
ad
14
5
138
41
1114
276
8/12
11111111
11010010
00000000
4
cd
ad
10
3
81
22
307
74
8/14
11111111
11011110
00000000
5
cd
ad
3
1
82
22
126
29
8/16
11111111
11111111
00000000
7
cd
ad
64
16
96
24
128
32
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Comparison of systematic recursive
convolutional code with nonsystematic
codes
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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
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BER Performance of Systematic
Recursive PCPC code
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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
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PCM Transmission example - EEP
• Analog source v [1;1]
• Source coding: m-bit linear quantization (m=20)
– Quantized sample
vQ k 1 xk 2 k , xk 1,1
m
– smaller k -> more important.
• Transmission distortion
2
m
m
k
ˆ
E k 1 ( xk xk )2 4k 1 2 2 k Pb (k )
2
e
• equal Pb for all k=1,2,…,m
SNRPCM
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s2
1
2
2
e Q 4Pb 1 22m 22m
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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
ˆv k 1 ( xk )2 k , ( xk ) 1,1
m
• Gain of about 1.6dB in SNRPCM
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PCM Transmission Example
– Apply Channel Coding
• m=10
– m is smaller, quantization noise increases
• Channel coding rate = ½
– RCPSRC 8/16
– Improves total performance
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PCM Transmission Example – UEP
• Let all bits contribute the same transmission
distortion. Then,
1
Pb (k ) 2 k
2
– 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
1 2( mk )
Pb (k ) 2
12
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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
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PCM Transmission Example
- Simulation Results
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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
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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
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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
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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
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