|
Math @ Duke
|
Publications [#343276] of Henry Pfister
Papers Published
- Zhang, F; Pfister, HD, On the Iterative Decoding of High-Rate LDPC Codes With Applications in
Compressed Sensing
(March, 2009)
(last updated on 2023/06/01)
Abstract: This paper considers the performance of $(j,k)$-regular low-density
parity-check (LDPC) codes with message-passing (MP) decoding algorithms in the
high-rate regime. In particular, we derive the high-rate scaling law for MP
decoding of LDPC codes on the binary erasure channel (BEC) and the $q$-ary
symmetric channel ($q$-SC). For the BEC, the density evolution (DE) threshold
of iterative decoding scales like $\Theta(k^{-1})$ and the critical stopping
ratio scales like $\Theta(k^{-j/(j-2)})$. For the $q$-SC, the DE threshold of
verification decoding depends on the details of the decoder and scales like
$\Theta(k^{-1})$ for one decoder.
Using the fact that coding over large finite alphabets is very similar to
coding over the real numbers, the analysis of verification decoding is also
extended to the the compressed sensing (CS) of strictly-sparse signals. A DE
based approach is used to analyze the CS systems with randomized-reconstruction
guarantees. This leads to the result that strictly-sparse signals can be
reconstructed efficiently with high-probability using a constant oversampling
ratio (i.e., when the number of measurements scales linearly with the sparsity
of the signal). A stopping-set based approach is also used to get stronger
(e.g., uniform-in-probability) reconstruction guarantees.
|
|
|
|
dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821
| |
Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320
|
|