首页> 外文学位 >Linear interactive encoding and decoding schemes for lossless source coding with decoder only side information.
【24h】

Linear interactive encoding and decoding schemes for lossless source coding with decoder only side information.

机译:仅使用解码器附带信息的无损源编码的线性交互式编码和解码方案。

获取原文
获取原文并翻译 | 示例

摘要

Near lossless source coding with side information only at the decoder, was first considered by Slepian and Wolf in 1970s, and rediscovered recently due to applications such as sensor network and distributed video coding. Suppose X is a source and Y is the side information. The coding scheme proposed by Slepian and Wolf, called SW coding, in which information only flows from the encoder to the decoder, was shown to achieve the rate H(X|Y) asymptotically for stationary ergodic source pairs. As H(X|Y) is the minimum achievable rate even if the encoder is informed of the side information Y, this implies the optimality of SW coding for any stationary ergodic source-side information pairs. However, it is shown by Yang and He that SW coding can not achieve this rate for most of non-ergodic source-side information pairs.;The results reviewed above show that IED schemes are much more appealing than SW coding schemes to applications where the interaction between the encoder and the decoder is possible. However, the IED schemes proposed by Yang and He do not have an intrinsic structure that is amenable to design and implement in practice. Towards practical design, we restrict the encoding method to linear block codes, resulting in linear IED schemes. It is then shown that this restriction will not undermine the asymptotic performance of IED, in the sense that a sequence of linear IED schemes can be always found for any stationary ergodic source-side information pair (X, Y) to achieve the rate of conditional entropy H(X| Y). Moreover, the result can also be extended to non-ergodic source-side information pairs.;Another step of practical design of IED schemes is to make the computational complexity incurred by encoding and decoding feasible. In the framework of linear IED, a scheme can be conveniently described by parity check matrices. It can be easily observed that density of these matrices (measured as the average number of non-zero entries) is directly related to the scheme's encoding and decoding complexity: the complexity increases as the density increases. Further, we get an interesting trade-off between the density of the associated parity check matrices and the resulting symbol error probability. Our analysis reveals that as long as enp*n = O(log n/n), where epsilonn and p*n are real numbers, one can always construct a sequence of universal linear IED schemes { In } such that the average density of the parity check matrices associated with In is concentrated around (| X | -- 1) p*n , and the resulting symbol error probability is upper bounded by epsilon n+o(epsilonn). In addition, if some modification applies to linear IED schemes, it can be shown that p*n can be as low as lognn while the symbol error probability goes to zero asymptotically.;To implement the idea of linear IED and follow the instinct provided by the result above, Low Density Parity Check (LDPC) codes and Belief Propagation (BP) decoding are utilized. Considering incremental encoding is needed in IED, a successive LDPC code based on syndrome splitting is proposed, and the splitting rule is optimized according to density evolution results. Moreover, as existing BP decoding algorithms can only apply to limited kinds of correlation between the source X and the side information Y, a new BP decoding algorithm is proposed, which applies to the case where the correlation between Y and X can be modelled as a finite state channel. It then can be shown that the existing BP algorithms, which apply to hidden Markov state channels, such as GE channels and Markov Modulated Channels, are the special cases of this new algorithm. Finally, simulation results show that linear IED schemes are indeed superior to SW coding schemes.;Recently, a new source coding paradigm called interactive encoding and decoding (IED) was proposed for near lossless coding with side information only at the decoder. In such paradigm, information flows in both ways, from the encoder to the decoder and vice verse, and the behaviour of the encoder also relies on the bits sent back from the decoder. The compression rate of an IED scheme is defined as average number of bits per symbol exchanged between the encoder and the decoder. In contrary to SW coding, IED can achieve the rate of H(X|Y) for any stationary source-side information pairs, ergodic or not. Also it was shown that for memoryless source-side information pairs, IED schemes achieve better redundancy performance than SW coding schemes. And universal IED can be built coupled with classical universal codes for any stationary ergodic source-side information pairs, while it is well known that there does not exist a universal SW coding scheme.
机译:Slepian和Wolf在1970年代首次考虑了仅在解码器处带有辅助信息的近乎无损的源编码,由于诸如传感器网络和分布式视频编码等应用,最近又重新发现了这种方法。假设X是来源,Y是辅助信息。 Slepian和Wolf提出的编码方案称为SW编码,其中信息仅从编码器流向解码器,对于固定的遍历源对,它渐近地达到了速率H(X | Y)。因为即使将边信息Y告知编码器,H(X | Y)仍是最小可达到的速率,所以这意味着对于任何平稳的遍历源侧信息对,SW编码都是最优的。然而,Yang和He证明,对于大多数非遍历源侧信息对,SW编码无法达到此速率。上面的结果表明,对于以下应用,IED方案比SW编码方案更具吸引力。编码器和解码器之间可以进行交互。但是,Yang和He提出的IED方案没有一个可以在实践中设计和实施的固有结构。在实际设计中,我们将编码方法限制为线性分组码,从而产生线性IED方案。然后表明,从某种意义上说,对于任何平稳的遍历源侧信息对(X,Y),总可以找到一系列线性IED方案,以达到有条件的速率,这种限制不会破坏IED的渐近性能。熵H(X | Y)。此外,该结果还可以扩展到非遍历的源侧信息对。IED方案的实际设计的另一步骤是使通过编码和解码而引起的计算复杂性可行。在线性IED的框架中,可以通过奇偶校验矩阵方便地描述一个方案。可以很容易地观察到,这些矩阵的密度(以非零项的平均数衡量)与方案的编码和解码复杂度直接相关:复杂度随着密度的增加而增加。此外,我们在相关的奇偶校验矩阵的密度和所得的符号错误概率之间进行了有趣的权衡。我们的分析表明,只要enp * n = O(log n / n)(其中epsilonn和p * n是实数),就可以始终构造一系列通用线性IED方案{In},使得与In相关的奇偶校验矩阵集中在(| X |-1)p * n周围,所得的符号错误概率以epsilon n + o(epsilonn)为上限。此外,如果对线性IED方案进行一些修改,则可以证明p * n可以低至lognn,而符号错误概率渐近地变为零。;实现线性IED的思想并遵循由IED提供的本能上面的结果,利用了低密度奇偶校验(LDPC)码和置信度传播(BP)解码。考虑到IED中需要增量编码,提出了基于校正子分裂的连续LDPC码,并根据密度演化结果优化了分裂规则。此外,由于现有的BP解码算法只能应用于源X和辅助信息Y之间的有限种类的相关性,因此提出了一种新的BP解码算法,该算法适用于可以将Y和X之间的相关性建模为A的情况。有限状态通道。然后可以证明,适用于隐藏的马尔可夫状态信道(例如GE信道和马尔可夫调制信道)的现有BP算法是该新算法的特殊情况。最后,仿真结果表明线性IED方案确实优于SW编码方案。;最近,提出了一种新的源编码范例,称为交互式编码和解码(IED),用于仅在解码器处具有边信息的近无损编码。在这样的范例中,信息以两种方式从编码器流向解码器,反之亦然,编码器的行为也依赖于从解码器发回的位。 IED方案的压缩率定义为在编码器和解码器之间交换的每个符号的平均位数。与SW编码相反,IED可以针对遍历与否的任何固定源侧信息对实现H(X | Y)的速率。还表明,对于无记忆源侧信息对,IED方案比SW编码方案具有更好的冗余性能。对于众所周知的不存在通用SW编码方案的情况,可以将通用IED与经典通用代码结合起来用于任何固定的遍历源侧信息对。

著录项

  • 作者

    Meng, Jin.;

  • 作者单位

    University of Waterloo (Canada).;

  • 授予单位 University of Waterloo (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.A.Sc.
  • 年度 2008
  • 页码 80 p.
  • 总页数 80
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:41

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号