降低复杂度的点阵球面解码

Asma Mejri, G. R. Othman
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引用次数: 1

摘要

基于球面搜索区域的点阵顺序解码器,如球面解码器和SB-Stack解码器,实现树搜索策略来查找ML解决方案,同时只访问属于预定义半径的球体的点阵点。它们的计算复杂度主要取决于初始球半径的选择。在这项工作中,我们提出了基于球面区域的顺序点阵解码器的新颖初始球体半径选择方法,并通过仿真显示了在保持ML性能的同时使用球体解码器时,这些方法所允许的复杂性降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reduced-complexity lattice spherical decoding
Lattice sequential decoders based on a spherical search region, such as the Sphere Decoder and the SB-Stack decoder, implement a tree-search strategy to find the ML solution while visiting only the lattice points that belong to a sphere of a predefined radius. Their computational complexity depends then critically on the choice of the initial sphere radius. We propose in this work novel initial sphere radius selection methods for spherical-region based sequential lattice decoders and show through simulations the complexity reduction allowed by such methods when the Sphere Decoder is used while maintaining ML performance.
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