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arXiv 0705.2435cs.ITmath.IT
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基于新格表示的方形QAM球译码算法

Reduced Complexity Sphere Decoding for Square QAM via a New Lattice Representation

Luay Azzam, Ender Ayanoglu

摘要:

球形译码(SD)是一种低复杂度的最大似然(ML)检测算法,适用于数字通信中不同的线性信道。在某些情况下,SD的复杂性已被证明是指数的,在其他情况下,在某些假设下,多项式。球体半径和遍历树搜索过程中访问的节点数是算法复杂度的决定性因素。半径问题已在文献中得到广泛的讨论和处理。在本文中,我们提出了一个新的结构SD,大大降低了整体的复杂性。复杂性是衡量的浮点运算每秒(FLOPS)和访问的节点数在整个算法树搜索。这种复杂度的降低是由于利用新的点阵表示,能够彼此独立地解码每个联合检测到的符号的实部和虚部。我们进一步表明,通过模拟,新的方法实现了80%的整体复杂性降低相比,传统的SD为2x2的系统,和几乎50%的减少为4x4和6x6的情况下,从而放宽了对硬件实现的要求。

英文摘要:

Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The complexity of the SD has been shown to be exponential in some cases, and polynomial in others and under certain assumptions. The sphere radius and the number of nodes visited throughout the tree traversal search are the decisive factors for the complexity of the algorithm. The radius problem has been addressed and treated widely in the literature. In this paper, we propose a new structure for SD, which drastically reduces the overall complexity. The complexity is measured in terms of the floating point operations per second (FLOPS) and the number of nodes visited throughout the algorithm tree search. This reduction in the complexity is due to the ability of decoding the real and imaginary parts of each jointly detected symbol independently of each other, making use of the new lattice representation. We further show by simulations that the new approach achieves 80% reduction in the overall complexity compared to the conventional SD for a 2x2 system, and almost 50% reduction for the 4x4 and 6x6 cases, thus relaxing the requirements for hardware implementation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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