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SUMMARY:Design techniques for sparse regression codes - Adam Greig\, CUED
DTSTART:20180518T110000Z
DTEND:20180518T120000Z
UID:TALK103846@talks.cam.ac.uk
CONTACT:Prof. Ramji Venkataramanan
DESCRIPTION:Sparse regression codes (SPARCs) are a recent coding scheme fo
 r the additive white Gaussian noise channel\, which achieve rates approach
 ing the Shannon capacity of the channel with polynomial time decoding algo
 rithms. This talk will introduce the codes and decoding algorithms\, and t
 hen discuss techniques to improve their empirical performance and implemen
 tation efficiency. \n\nIn addition to optimising key code parameters such 
 as power allocation\, a novel decoder which combines a SPARC with an outer
  LDPC code is presented. This construction achieves excellent error perfor
 mance which can exceed that of LDPC codes alone. Finally a new code struct
 ure called _modulated SPARC_ is described. This structure also efficiently
  achieves the Shannon capacity and represents an interesting direction for
  future work.
LOCATION:LT6\, Baker Building\, CUED
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