Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e., interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the $l_{2}$ and the Schatten- $p$ norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions.

中文翻译：

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具有非协调干扰的一跳和两跳 MIMO 系统的干扰校准

提供更高的数据速率是无线通信系统的一个重要目标，而干扰是实现这一目标的重要障碍。为了解决这个问题，已经提出了干扰对齐（IA）。在本文中，我们提出了两种秩最小化方法，以在存在不协调干扰的情况下提高 IA 的性能，IE，无法与网络的其余部分正确对齐的干扰，因此是一个关键问题。在这种情况下，考虑了完美和不完美的信道状态信息 (CSI) 情况。我们提出的方法采用 $l_{2}$ 和 Schatten- $p$ 由于其非凸性，因此可以使用范数来逼近秩函数。此外，我们提出了一种新的凸松弛来扩展我们优化问题的可行集，与文献中的其他 IA 方法相比，提供了较低等级的解决方案。此外，我们提出了一种改进的加权和方法来处理中继辅助 MIMO 干扰信道中的干扰，该方法采用一组加权参数以找到更多解决方案。