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Interference Alignment Algorithms for the $K$ User Constant MIMO Interference Channel

机译:用户常量MIMO干扰信道 $ K $ 的干扰对准算法

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摘要

This paper considers the degrees of freedom (DOF) for a $K$ user multiple-input multiple-output (MIMO) $M times N$ interference channel using interference alignment (IA). A new performance metric for evaluating the efficacy of IA algorithms is proposed, which measures the extent to which the desired signal dimensionality is preserved after zero-forcing the interference at the receiver. Inspired by the metric, two algorithms are proposed for designing the linear precoders and receive filters for IA in the constant MIMO interference channel with a finite number of symbol extensions. The first algorithm uses an eigenbeamforming method to align sub-streams of the interference to reduce the dimensionality of the interference at all the receivers. The second algorithm is iterative, and is based on minimizing the interference leakage power while preserving the dimensionality of the desired signal space at the intended receivers. The improved performance of the algorithms is illustrated by comparing them with existing algorithms for IA using Monte Carlo simulations.
机译:本文考虑了 $ K $ 用户多输入多输出(MIMO)的自由度(DOF)<使用干扰对齐(IA),公式FormulaType =“ inline”> $ M乘以N $ 干扰通道。提出了一种新的性能指标,用于评估IA算法的有效性,该指标度量了在将接收器的干扰强制为零后保留所需信号维数的程度。受到度量的启发,提出了两种算法,用于在具有有限数量的符号扩展的恒定MIMO干扰信道中设计线性预编码器和IA的接收滤波器。第一种算法使用特征波束形成方法来对齐干扰的子流,以降低所有接收器处的干扰维数。第二种算法是迭代的,并且基于最小化干扰泄漏功率,同时保留了预期接收器处所需信号空间的维数。通过使用蒙特卡洛模拟将它们与现有的IA算法进行比较,可以说明算法的改进性能。

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