Name
Abstract | ||
|---|---|---|
This paper considers trellis coded quantization (TCQ) and low-density parity-check (LDPC) codes for the quadratic Gaussian Wyner-Ziv coding problem. After TCQ of the source X, LDPC codes are used to implement Slepian-Wolf coding of the quantized source Q(X) with side information Y at the decoder. Assuming 256-state TCQ and ideal Slepian-Wolf coding in the sense of achieving the theoretical limit H(Q(X)|Y), we experimentally show that Slepian-Wolf coded TCQ performs 0.2 dB away from the Wyner-Ziv distortion-rate function DWZ(R) at high rate. This result mirrors that of entropy-constrained TCQ in classic source coding of Gaussian sources. Furthermore, using 8,192-state TCQ and assuming ideal Slepian-Wolf coding, our simulations show that Slepian-Wolf coded TCQ performs only 0.1 dB away from DWZ(R) at high rate. These results establish the practical performance limit of Slepian-Wolf coded TCQ for quadratic Gaussian Wyner-Ziv coding. Practical designs give performance very close to the theoretical limit. For example, with 8,192-state TCQ, irregular LDPC codes for Slepian-Wolf coding and optimal non-linear estimation at the decoder, our performance gap to DWZ(R) is 0.20 dB, 0.22 dB, 0.30 dB, and 0.93 dB at 3.83 bit per sample (b/s), 1.83 b/s, 1.53 b/s, and 1.05 b/s, respectively. When 256-state 4-D trellis-coded vector quantization instead of TCQ is employed, the performance gap to DWZ(R) is 0.51 dB, 0.51 dB, 0.54 dB, and 0.80 dB at 2.04 b/s, 1.38 b/s, 1.0 b/s, and 0.5 b/s, respectively. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TCOMM.2009.02.070287 | IEEE Transactions on Communications |
Keywords | Field | DocType |
gaussian source,high rate,192-state tcq,256-state tcq,practical performance limit,ldpc code,quadratic gaussian wyner-ziv coding,performance gap,ideal slepian-wolf coding,slepian-wolf coding,entropy-constrained tcq,entropy coding,source coding,source code,optimal estimation | Low-density parity-check code,Source code,Quadratic equation,Coding (social sciences),Optimal estimation,Electronic engineering,Vector quantization,Gaussian,Quantization (physics),Mathematics | Journal |
Volume | Issue | ISSN |
57 | 2 | 0090-6778 |
Citations | PageRank | References |
41 | 2.19 | 30 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Yang | 1 | 218 | 19.75 |
| Samuel Cheng | 2 | 56 | 8.24 |
| Zixiang Xiong | 3 | 3444 | 275.03 |
| Wei Zhao | 4 | 3532 | 404.01 |