The rapid increase in the number of wireless devices in modern communication networks has significantly increased the number of interference sources, which severely impacts communication reliability. Adaptive interference cancellation is rapidly becoming a necessity for modern wireless networks. For interference cancellation, a digital beamformer adaptively adjusts its weight vector using an array processing algorithm. This, in turn, shapes the radiation pattern in a manner that minimizes interference power and maximizes the desired signal power. In this letter, we propose two atomic-norm-minimization-based methods to design a weight vector that can be used to cancel interference. We present numerical and experimental studies and compare with the minimum variance distortionless response beamformer, which outputs the highest possible signal-to-interference-plus-noise ratio (SINR). We show that our approach is robust to signal corruptions arising from carrier frequency offsets. Uniquely, our algorithm extracts the offset frequencies, thus enabling interference cancellation with maximum SINR.

中文翻译：

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使用原子范数最小化和去噪的自适应干扰消除

现代通信网络中无线设备数量的迅速增加，显着增加了干扰源的数量，严重影响了通信可靠性。自适应干扰消除正迅速成为现代无线网络的必需品。对于干扰消除，数字波束成形器使用阵列处理算法自适应地调整其权重向量。这反过来又以最小化干扰功率和最大化所需信号功率的方式对辐射图进行整形。在这封信中，我们提出了两种基于原子范数最小化的方法来设计可用于消除干扰的权重向量。我们提出了数值和实验研究，并与最小方差无失真响应波束形成器进行比较，它输出可能的最高信号干扰加噪声比 (SINR)。我们表明我们的方法对于由载波频率偏移引起的信号损坏具有鲁棒性。独特的是，我们的算法提取偏移频率，从而以最大 SINR 实现干扰消除。