arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0909.0555cs.ITmath.IT
收藏

降低复杂度的球形译码

Reduced Complexity Sphere Decoding

Boyu Li, Ender Ayanoglu

摘要:

在多输入多输出(MIMO)系统中,球形译码(SD)可以达到与全搜索最大似然(ML)译码相当的性能,同时降低了复杂度。一些研究人员报告了进一步降低SD复杂性的技术。本文介绍了一种新的技术,它大大降低了SD的计算复杂性,而不牺牲性能。通过解构解码度量以减少计算的数量并利用格表示的结构来实现减少。此外,SD的应用,采用建议的智能实现非常低的计算复杂性的介绍。本申请以有效的方式计算比特交织卷积编码MIMO系统的软比特度量。基于降低的复杂度SD,所提出的智能实现采用初始半径获得的迫零判决反馈均衡(ZF-DFE),以确保没有空球。除此之外,还结合了特定数据结构的技术,以有效地减少SD执行的次数。仿真结果表明,这些方法在未编码和编码MIMO系统的计算复杂性方面都取得了实质性的增益。

英文摘要:

In Multiple-Input Multiple-Output (MIMO) systems, Sphere Decoding (SD) can achieve performance equivalent to full search Maximum Likelihood (ML) decoding, with reduced complexity. Several researchers reported techniques that reduce the complexity of SD further. In this paper, a new technique is introduced which decreases the computational complexity of SD substantially, without sacrificing performance. The reduction is accomplished by deconstructing the decoding metric to decrease the number of computations and exploiting the structure of a lattice representation. Furthermore, an application of SD, employing a proposed smart implementation with very low computational complexity is introduced. This application calculates the soft bit metrics of a bit-interleaved convolutional-coded MIMO system in an efficient manner. Based on the reduced complexity SD, the proposed smart implementation employs the initial radius acquired by Zero-Forcing Decision Feedback Equalization (ZF-DFE) which ensures no empty spheres. Other than that, a technique of a particular data structure is also incorporated to efficiently reduce the number of executions carried out by SD. Simulation results show that these approaches achieve substantial gains in terms of the computational complexity for both uncoded and coded MIMO systems.

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。

↑