Slepian-Wolf coded nested lattice quantization for Wyner-Ziv coding: High-rate performance analysis and code design (original) (raw)

Wyner-Ziv coding based on TCQ and LDPC codes

IEEE Transactions on Communications, 2009

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 distortionrate 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. in 1977. He received the MS and PhD degrees

Indexing and entropy coding of lattice codevectors

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2001

We present here two methods of entropy coding for the lattice codevectors. We compare our entropy coding methods with one method previously presented in the literature from the point of view of rate-distortion as well as of the computation complexity and memory requirements. The results are presented for artificial Laplacian and Gaussian data, as well as for LSF parameters of speech signals. In the latter case, the multiple scale lattice VQ (MSLVQ) is used for quantization, which reduces the rate gain of the entropy coding method when compared with the fixed rate case, but allows a dynamic allocation of the bits in the whole speech coding scheme.

Distortion-rate models for entropy-coded lattice vector quantization

IEEE Transactions on Image Processing, 2000

The increasing demand for real-time applications requires the use of variable-rate quantizers having good performance in the low bit rate domain. In order to minimize the complexity of quantization, as well as maintaining a reasonably high PSNR ratio, we propose to use an entropy-coded lattice vector quantizer (ECLVQ). These quantizers have proven to outperform the wellknown EZW algorithm's performance in terms of rate-distortion tradeoff.

Multiple descriptions coding for H.264/AVC using coinciding A2 lattice vector quantizer

2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2011

Applications involving multimedia communications are widespread. However available networks do not meet the users needs such as unlimited bandwidth and reliability. Therefore video compression techniques are used to decrease the size of the video data and error resiliency techniques are used to combat against channel failures. Multiple Descriptions Lattice Vector Quantization (MDLVQ) is a technique that combines these techniques and suits for robust data transmission over unreliable network channels. Multiple Descriptions Coinciding Lattice Vector Quantization (MDCLVQ) is a new MDLVQ scheme based on the coinciding sublattices of A 2 lattice. In this paper MDCLVQ has been employed in order to form an MD coding scheme for H.264/AVC video coding standard to increase the robustness of video transmission over error-prone communication channels. The proposed MD video coding scheme is applied to several reference video sequences. The experimental results show that the encoding performance of the scheme is increased while the average PSNR of the central decoder remains above 33.84. It means that error resiliency of the scheme is increased without significant drop in the reconstruction quality. In addition the proposed scheme is compared with renowned techniques. It is observed that the proposed scheme outperforms all the other algorithms in low bit rate regime.

A fast encoding method for lattice codes and quantizers

IEEE Transactions on Information Theory, 1983

their duals and certain other lattices, finds the closest lattice point to an arbitrary point of the underlying space. If the lattices are used as codes for a Gaussian channel, the algorithm provides a fast decoding procedure, or if they are used as vector quantizers the algorithm performs the analog-to-digital conversion efficiently. 'Qe present paper offers a solution to the inverse problem for the same lattices (the encoding problem for channel codes or the digital-toanalog part of quantizing), namely, given an integer k, to find the k th code vector, and to the closely related problem of finding the index k of a given code vector.

Design criteria for lattice network coding

2011

The compute-and-forward (C-F) relaying strategy proposed by Nazer and Gastpar is a powerful new approach to physical-layer network coding. Nazer-Gastpars construction of C-F codes relies on asymptotically-good lattice partitions that require the dimension of lattices to tend to infinity. Yet it remains unclear how such C-F codes can be constructed and analyzed under practical constraints. Motivated by this, an algebraic approach was taken to compute-and-forward, which provides a framework to study C-F codes constructed from finite-dimensional lattice partitions. Building on the algebraic framework, this paper moves one step further; it aims to derive the design criteria for the C-F codes constructed from finite-dimensional lattice partitions (also referred to as lattice network codes). It is shown that the receiver parameters {aℓ} and α should be chosen such that the quantity Q = |α|2 + SNRΣℓ=1L ||αhℓ - αℓ||2 is minimized, and the lattice partition should be designed such that the minimum inter-coset distance is maximized. These design criteria imply that finding the optimal receiver parameters is equivalent to solving a shortest vector problem, and designing good lattice partitions can be reduced to the design of good linear codes for complex Construction A.

Multiple Descriptions Coinciding Lattice Vector Quantizer for Wavelet Image Coding

IEEE Transactions on Image Processing, 2000

Multiple description (MD) coding has been a popular choice for robust data transmission over the unreliable network channels. Lattice vector quantization provides lower computation for efficient data compression. In this paper, a new MD coinciding lattice vector quantizer (MDCLVQ) is presented. The design of the quantizer is based on coinciding 2-D hexagonal sublattices. The coinciding sublattices are geometrically similar sublattices, with the same index but generated by different generator matrices. A novel labeling algorithm based on the hexagonal coinciding sublattices is also developed. Performance results of the MDCLVQ scheme, together with the new labeling algorithm applied to standard test images, show improvements of the central and side decoders, as compared with the renowned techniques for several test images.