1 / 10

Low Density Parity Check Codes An Introduction

Low Density Parity Check Codes An Introduction. Yuta Toriyama. yuta@ee.ucla.edu August 24, 2012. Channel Coding / FEC. Technique for controlling errors in transmission of data Redundancy in error-correcting code Hamming. Simple Parity Check Example. Simple scheme: repeat each bit 3 times

maisie
Download Presentation

Low Density Parity Check Codes An Introduction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Low Density Parity Check CodesAn Introduction Yuta Toriyama yuta@ee.ucla.edu August 24, 2012

  2. Channel Coding / FEC • Technique for controlling errors in transmission of data • Redundancy in error-correcting code • Hamming

  3. Simple Parity Check Example • Simple scheme: repeat each bit 3 times • Majority rule to recover single bit • (3,1) code, single error detection & correction 0 0 0 0 1 1 1 1

  4. Simple Parity Check Example • “Hypercube” representing gray code

  5. Simple Parity Check Example • “Hypercube” representing gray code

  6. Linear Block Codes • Generator matrix G (n x m) • Parity-check matrix H (m x k) • Generator matrix is a transformation from n to m dimensions • Codeword c is the nullspace (kernel) of the parity-check matrix • Example: Hamming(7,4)

  7. Low Density Parity Check Codes • Parity-check matrix is sparse • A particular LDPC code can be represented by a sparse bipartite graph (“Tanner graph”) • H is the bi-adjacency matrix of the Tanner graph

  8. Iterative Message Passing Algorithm • Iterative decoding algorithm • v-nodes and c-nodes pass “messages” to each other • Belief Propagation

  9. Non Binary LDPC • Numbers are limited elements in GF(2p) • Decoding is much more complicated • Performs better than binary LDPC, especially in the case of short or medium codeword lengths Davey, M.C.; MacKay, D.; , "Low-density parity check codes over GF(q)," Communications Letters, IEEE , vol.2, no.6, pp.165-167, June 1998

  10. Summary • LDPC codes show strong potential as a set of codes with very low BER • Computational complexity of decoding algorithms needs to be resolved to make NB-LDPC practical as well as allow for further constructive research

More Related