Decoding in weighted combinatorial and other metrics

以加权组合和其他指标进行解码

• 批准号: 216040227
• 负责人: Professor Dr.-Ing. Martin Bossert
• 金额: --
• 依托单位: Institut für Nachrichtentechnik (NT)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/216040227?language=en
• 关键词: Decoding; weighted; combinatorial; other; metrics

There exist low-complexity hard-input bounded distance decoders for many block codes. However, low complexity soft-input decoding remains still a challenging task. Our goal is to propose a soft-input decoding of block codes for channels with memory. For memoryless channels such soft-input decoding, called Generalized Minimum Distance (GMD) decoding, was suggested by Forney in 1966. GMD decoding uses reliabilities of received symbols and can be considered as a bounded distance decoding in a weighted (by the reliabilities) Hamming metric. The Hamming metric matches discrete memoryless symmetric channels, i.e., maximum-likelihood decoding in such channels is equivalent to minimum distance decoding in the Hamming metric. GMD decoding uses a hardinput error-and-erasure decoder of the block code in a multitrial manner, where in each decoding trial, a number of least reliable received symbols are erased before decoding. Hundreds of publications show that GMD decoding is a universal procedure (applicable to an arbitrary code) with very good performance and low complexity. As a result, it has many practical applications for different memoryless channels and for the decoding (generalized) concatenated codes.

存在用于许多分组码的低复杂度硬输入有界距离解码器。然而，低复杂度的软输入解码仍然是一个具有挑战性的任务。我们的目标是提出一个软输入解码的分组码的信道记忆。对于无记忆信道，这种软输入解码，称为广义最小距离（GMD）解码，是由Forney在1966年提出的。GMD解码使用接收到的符号的可靠性，并且可以被认为是加权（通过可靠性）汉明度量中的有界距离解码。汉明度量匹配离散无记忆对称信道，即，这种信道中的最大似然解码等效于汉明度量中的最小距离解码。GMD解码以多次试验的方式使用分组码的硬输入错误和擦除解码器，其中在每次解码试验中，在解码之前擦除多个最不可靠的接收符号。数以百计的出版物表明，GMD解码是一个通用的过程（适用于任意代码），具有非常好的性能和低复杂度。因此，它对不同的无记忆信道和（广义）级联码的译码有许多实际应用。