This work studies the task of device coordination in wireless networks for over-the-air federated learning (OTA-FL). For conventional metrics of aggregation error, the task is shown to describe the zero-forcing (ZF) and minimum mean squared error (MMSE) schemes and reduces to the NP-hard problem of subset selection. We tackle this problem by studying properties of the optimal scheme. Our analytical results reveal that this scheme is found by searching among the leaves of a tree with favorable monotonic features. Invoking these features, we develop a low-complexity algorithm that approximates the optimal scheme by tracking a dominant path of the tree sequentially. Our numerical investigations show that the proposed algorithm closely tracks the optimal scheme.
翻译:这项工作研究无线网络设备协调的任务, 以便进行超空联合学习( OTA- FL ) 。 对于常规的总和错误衡量标准, 任务显示描述零力( ZF) 和最小平均正方差( MMSE) 计划, 并减少子集选择的NP- 硬问题 。 我们通过研究最佳办法的属性来解决这个问题 。 我们的分析结果表明, 这个方案是通过在树叶中搜索有利的单调特性来找到的。 引用这些特点, 我们开发了一种低兼容性算法, 通过跟踪树的主导路径, 从而接近最佳办法 。 我们的数字调查显示, 提议的算法非常接近最佳办法 。