Effective LLL Reduction for Lattice Decoding

ISIT(2007)

引用 91|浏览4
暂无评分
摘要
The use of Lenstra-Lenstra-Lovasz (LLL) lattice reduction significantly improves the performance of zero-forcing (ZF) and successive interference cancellation (SIC) decoders in multi-input multi-output (MIMO) communications. Capitalizing on the observation that the decision region of SIC is determined by the Gram-Schmidt vectors rather than the basis itself, we propose the use of effective LLL reduction in SIC decoding, where size reduction is only performed for pairs of consecutive basis vectors. We establish the theoretic upper bound O(n3 log n) on the average complexity of effective LLL reduction for the i.i.d. Gaussian model of MIMO fading channels, which is an order lower than previously thought. Moreover, an effectively LLL-reduced basis can easily be transformed into the standard LLL-reduced basis for the purpose of ZF decoding.
更多
查看译文
关键词
lattice decoding,gaussian channels,gram-schmidt vector,fading channels,channel coding,mimo fading channel,multi input multi output communication,zero-forcing decoder,computational complexity,wireless channels,mimo communication,gaussian model,interference suppression,successive interference cancellation decoder,lenstra-lenstra-lovasz lattice reduction,decoding,lattice theory,zero forcing,lattices,algorithm design and analysis,cryptography,upper bound,interference cancellation,lattice reduction,fading channel,vectors,mimo
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要