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Optimal Factorization in Lattice-Reduction-Aided and Integer-Forcing Linear Equalization

机译:格子减少和整数强迫线性均衡的最优分解

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Lattice-reduction-aided (LRA) equalization is a very interesting multi-user equalization technique as it enables a lowcomplexity full-diversity detection. To this end, the multipleinput/ multiple-output channel is factorized into a reduced variant and a unimodular integer matrix. Inspired by the closely related finite-field processing strategy of integer-forcing (IF) equalization, this factorization task has recently been relaxed to nonunimodular integer matrices. In this paper, the claim of a significant performance gain induced by the IF philosophy is revisited. For that purpose, lattice-basis-reduction approaches are reviewed; the optimal one with respect to channel equalization is identified. A fair comparison between unimodular LRA and IF strategy is given, complemented by detailed numerical results.
机译:晶格减少辅助(LRA)均衡是一种非常有趣的多用户均衡技术,因为它可以实现低复杂度的全分集检测。为此,将多输入/多输出通道分解为精简变量和单模整数矩阵。受紧密相关的整数强制(IF)均衡有限域处理策略的启发,该分解任务最近已放宽到非单模整数矩阵。本文重新讨论了由IF哲学引起的显着性能提升的主张。为此目的,审查了减少晶格的方法;确定关于信道均衡的最佳方案。给出了单模LRA和IF策略之间的合理比较,并辅以详细的数值结果。

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