用于干扰环境下遥感的基于群体阵列的无标度波束成形
Scale-Free Beamforming using Swarm Arrays for Remote Sensing under Interference
AI总结：
研究利用自主中继的群体阵列在消除干扰器时将期望信号以最大保真度转发到融合中心的问题，提出分布式算法计算最优迫零波束成形权重，算法无标度，计算和带宽开销与阵列大小无关。
摘要：
我们考虑一个自主中继的群体阵列，其试图在消除多个干扰器的同时，以最大可能的保真度将期望信号协同转发到融合中心。我们提出一种分布式算法，用于在中继处计算最优迫零波束成形权重，而无需先验信道知识。关键的是，我们的算法在计算和带宽开销完全独立于阵列大小的意义上是“无标度”的。我们基于最近引入集体阵列概念的工作，通过施加阵列必须始终作为一个“群体”运行的约束来实现这种“无标度”计算，即阵列元素只能集体与外部节点通信，而不能单独通信。虽然这是一个非常严格的限制，但我们表明它允许进行诸如迫零波束成形等有用的计算，同时对噪声和信道时变具有鲁棒性。
英文摘要：
We consider a swarm array of autonomous relays that seek to cooperatively forward a desired signal to a fusion center with the maximum possible fidelity while canceling out a number of interferers. We present a distributed algorithm for computing the optimal zero-forcing beamforming weights at the relays without requiring prior channel knowledge. Crucially, our algorithm is {\it scale-free} in the sense that the computational and bandwidth overheads are completely independent of the size of the array. We build on recent work that introduced the concept of a Collective Array that enables such {\it scale-free} computation by imposing a constraint that the array must always function as a {\it swarm} i.e. array elements can only ever communicate with external nodes collectively and never individually. While this is a very severe restriction, we show that it allows useful computations such as zero-forcing beamforming while being robust to noise and channel time-variations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
