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Progress report of LDPC codes

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mediate, besides min sum organization, needing more two way comparator and one adder. ... By Hagenauer IEEE trans on Information theory 1996 ... – PowerPoint PPT presentation

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Title: Progress report of LDPC codes


1
Progress report of LDPC codes
  • Advisor Tzi-Dar Chiueh
  • Student Hsiu-min Lin
  • Date Jan 3th, 2005

2
Outline
  • Overview of LDPC and related application
  • LDPC algorithm
  • Optimum decoding
  • Various Log Likelihood Ratio (LLR) introduction
  • Simulation result
  • LDPC architecture
  • Conclusion and Reference

3
Properties of LDPC codes
  • One kind of Block Codes
  • H is sparse
  • Very few 1s in each row and column
  • Variety of H (wr ,wc ) LDPC codes
  • That each row is of fixed weight wr and column
    is of fixed weight wc is regular
  • If not, thats irregular.
  • Suppose a LDPC code is a (n,k) block code
  • H is a (n-k) x n matrix
  • (n-k) .wr n.wc
  • Code rate k/n 1-wc/wr

4
Tanner Graph
  • H can be represented by a Tanner graph
  • For a (n,k) code, it consists of n variable nodes
    and (n-k) check nodes
  • Each edge on the graph represents a nonzero entry
    in H

check nodes
variable nodes
5
Cycle path
  • The number of 1s in common between any two
    columns.
  • Short cycle effect
  • Girth concept.

6
LDPC excellent performance
  • If block length is n , for large n practically
    all the LDPC codes in the ensemble have a minimum
    distance of at least n
  • It mean that The larger block length is, the
    better performance is
  • s is Wr and t is Wc

7
LDPC in 802.3an progress
  • LDPC is used in IEEE 802.3an (10G Ethernet using
    twist pairs)1

8
Candidate H in 802.3an 2
9
Outline
  • Overview of LDPC
  • LDPC algorithm
  • Optimum decoding
  • Various Log Likelihood Ratio (LLR) introduction
  • Simulation result
  • LDPC architecture and Reference
  • Conclusion

10
Optimum decoding
  • Assuming received signals has n bits to
    find codeword , y ,
    and each bit is independent ,

In order to compute the 0/1 probability of each
11
Optimum decoding
  • is overall information of the bit n,
  • is the intrinsic information of the bit n
  • is the extrinsic information of the bit n

?Optimum decoding with cycle free hypothesis
is interconnection of nodes in Tanner
graph. M(n) is final terminal node depending on
distribution of 1 in H matrix.
12
Optimum decoding (Cont)
  • Short cycle length and numbers effect would
    decrease performance obviously
  • Break short length by inserting new column (for
    ex generate extending (14,8) hamming code
    instead of original (7,4)hamming code)
  • Optimum decoding could be applied for all block
    and convolutional code

13
Log domain algorithm
  • Initialization
  • Horizontal3
  • Vertical

14
The variety of Log domain analysis
  • Horizontal processing stage has more flexibility
    (approximate) to trade off performance and
    complexity
  • LLR algorithm 4
  • min-sum algorithm
  • min-sum-with-correction-factor algorithm

15
Log domain simulation result
16
Log domain algorithm implementation
  • LLR algorithm
  • Usually use look up table or piecewise linear
    approximation to implement

Implementation example 1Gbps,690mW, code rate
1/2 ,1024 bit LDPC chip JSSCC(2002) 5 and
Parhi quasi-cycle overlap LDPC (IEEE trans on
VLSI 2004) 6
17
Log domain algorithm implementation
LLR min sum Min sum with correct factor
Performance Highest low Highest
Complexity Highest, use look up table (LUT) to implement tanh and arctanh. low, dont need tanh, and use comparator to search the minimum value mediate, besides min sum organization, needing more two way comparator and one adder.

18
Outline
  • Overview of LDPC
  • LDPC algorithm
  • Optimum decoding
  • Various Log Likelihood Ratio (LLR) introduction
  • Simulation result
  • LDPC architecture
  • Conclusion

19
Hardware Implementation issue
  • In circuit level, It is impossible to approach
    Shannon limlt.(0.0045db, block sizes is 107)
  • LDPC has better parallel processing property than
    Turbo codes.
  • Hardware architecture is divided into two
    categories.
  • -Hardware sharing (Serial, memory based )
  • 6,7,8,9,10,11
  • -parallel processing (Parallel, hardwire
  • connection ) 5
  • The key critical implementation issue in LDPC is
    interconnect handling.

20
LDPC Architecture proposed
  • Overlapped Message Passing for Quasi-Cyclic
    Low-Density Parity Check Codes6
  • To find the rule decoder could overlap between
    horizontal and vertical processing for
    quasi-cycle LDPC family.
  • A Scalable Architecture for LDPC Decoding9
  • Add the prefetcher to increase speed in memory
    based arhitecture and implement the specific
    algorithm called UMP12.
  • Low power VLSI Decoder Architecture for LDPC
    Codes10
  • Use BJCR to decode instead of sum of product
    algorithm due to lower iteration number for power
    saving purpose.

21
LDPC Architecture proposed (Cont)
  • Decoder-First Code Design8
  • Reverse traditional decoder design concept and
    use suffle network to handle horizontal
    processing.
  • Design of VLSI Implementation-Oriented LDPC
    Codes11
  • First find small code matrix H suitable for
    decoder design and then expand this matrix
    following certain rule.
  • Joint (3,k)-Regular LDPC Code and Decoder/Encoder
    Design7
  • Inspired by 8 and girth concept, Parhi tries to
    design joint en/decoder design flow

22
Conclusion and future work
  • All LDPC VLSI decoders use log domain algorithm
    to implement.
  • It seem to have less headroom to improve log
    domain algorithm since 2001.
  • In choice of LDPC architecture, memory based ones
    has more flexibility than parallel hardwired in
    recently years.
  • Continue to work on professors architecture,
    using feature has been published in papers.

23
Reference
  • 1 Channel Coding for 10GBASE-T ,Mar. 2004
    ,Katsutoshi SEKI, NEC Electronics, IEEE 802.3an
    task group.
  • 2 Performance evaluation of low latency LDPC
    code Sept 2004, Katsutoshi Seki, NEC Electronics,
    IEEE 802.3an task group.
  • 3 Iterative Decoding of Binary block and
    convolutional codes. By Hagenauer IEEE trans on
    Information theory 1996
  • 4 Efficient Implementation of the sum-product
    algorithm for decoding LDPC Codes .by Xiao-Yu Hu,
    Evangelos Eleftheriou and Ajay IEEE 2001.
  • 5 A 690-mW 1-Gb/s 1024bits,Rate-1/2 Low-Density
    Parity-Check Code Decoder by Andrew J.Blanksby
    IEEE JSSC March, 2002
  • 6 Overlapped Message Passing for Quasi-Cyclic
    Low-Density Parity Check Codes ,by Parhi,IEEE
    trans on VLSI system, June 2004.
  • 7 Joint (3,k)-Regular LDPC Code and
    Decoder/Encoder Design By Parhi , IEEE trans on
    signal processing ,April 2004
  • 8 Decoder-First Code Design, By Emmanuel
    Boutillon, University of Tornondo.

24
Reference (Cont)
  • 9 A Scalable Architecture for LDPC Decoding.
    Proceeding of the Design ,Automation and Test in
    Europe Conference IEEE 2004
  • 10 Low power VLSI Decoder Architecture for LDPC
    Codes. By Mohammad M.Mansour 2002.
  • 11 Design of VLSI Implementation-Oriented LDPC
    Codes by Hao Zhong and Tong Zhang ,IEEE 2003
  • 12 Reduced complexity iterative decoding of low
    density parity check based on belief propagation
    by M.Fossorier IEEE trans on Comm
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