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An improved method of maximum likelihood decoding algorithms using the most reliable basis based on a order relation among binary vectors

机译:基于二值向量之间顺序关系的最可靠基础的最大似然解码算法的改进方法

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摘要

Several reliability based maximum likelihood decoding (MLD) algorithms of linear block codes have been widely studied. These algorithms efficiently search the most likely codeword, using the most reliable basis of generator matrix whose leftmost k (the dimension of code) columns are the most reliable and linearly independent. In this paper, several sufficient conditions for eliminating unnecessary candidate codewords or their metrics computations are derived for MLD algorithms using the most reliable basis by utilizing a order relation among binary vectors. Under the certain assumption of generation order of candidate codewords, we devise an adaptive implementation of the derived conditions. Consequently, the MLD algorithm employing the derived conditions reduces the number of generated candidate codeword and of real number operations, compared to a conventional MLD using the MRB without the degradation in error performance.
机译:已经广泛研究了几种基于可靠性的线性分组码的最大似然解码(MLD)算法。这些算法使用生成器矩阵的最可靠基础,有效地搜索最可能的码字,该生成器矩阵的最左边的k(代码维)列是最可靠且线性独立的。在本文中,通过利用二进制向量之间的顺序关系,使用最可靠的基础为MLD算法推导了消除不必要的候选码字或其度量计算的几个充分条件。在候选码字的生成顺序一定的假设下,我们设计了导出条件的自适应实现。因此,与使用MRB的传统MLD相比,采用导出条件的MLD算法减少了生成的候选码字和实数运算的数量,而不会降低错误性能。

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