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Progress report of LDPC codes. Advisor : Tzi-Dar Chiueh Student : Hsiu-min Lin Date : Jan 3 th , 2005. Outline. Overview of LDPC and related application LDPC algorithm Optimum decoding Various Log Likelihood Ratio (LLR) introduction Simulation result LDPC architecture
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Progress report of LDPC codes Advisor : Tzi-Dar Chiueh Student : Hsiu-min Lin Date : Jan 3th, 2005
Outline • Overview of LDPC and related application • LDPC algorithm • Optimum decoding • Various Log Likelihood Ratio (LLR) introduction • Simulation result • LDPC architecture • Conclusion and Reference
Properties of LDPC codes • One kind of Block Codes • H is sparse • Very few 1’s 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 isregular • If not, that’sirregular. • 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
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
Cycle path • The number of 1’s in common between any two columns. • Short cycle effect • Girth concept.
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
LDPC in 802.3an progress • LDPC is used in IEEE 802.3an (10G Ethernet using twist pairs)[1]
Outline • Overview of LDPC • LDPC algorithm • Optimum decoding • Various Log Likelihood Ratio (LLR) introduction • Simulation result • LDPC architecture and Reference • Conclusion
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
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.
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
Log domain algorithm • Initialization: • Horizontal:[3] • Vertical:
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
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]
Outline • Overview of LDPC • LDPC algorithm • Optimum decoding • Various Log Likelihood Ratio (LLR) introduction • Simulation result • LDPC architecture • Conclusion
Hardware Implementation issue • In circuit level, It is impossible to approach Shannon limlt.(0.0045db, block sizes is 10^7) • 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.
LDPC Architecture proposed • Overlapped Message Passing for Quasi-Cyclic Low-Density Parity Check Codes[6]: • To find the rule decoder could overlap between horizontal and vertical processing for quasi-cycle LDPC family. • A Scalable Architecture for LDPC Decoding[9]: • Add the prefetcher to increase speed in memory based arhitecture and implement the specific algorithm called UMP[12]. • Low power VLSI Decoder Architecture for LDPC Codes[10]: • Use BJCR to decode instead of sum of product algorithm due to lower iteration number for power saving purpose.
LDPC Architecture proposed (Cont) • Decoder-First Code Design[8]: • Reverse traditional decoder design concept and use suffle network to handle horizontal processing. • Design of VLSI Implementation-Oriented LDPC Codes[11]: • 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 Design[7]: • Inspired by [8] and girth concept, Parhi tries to design joint en/decoder design flow
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 professor’s architecture, using feature has been published in papers.
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.
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