Blind Federated Edge Learning
Blind Federated Edge Learning
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DOI：
10.1109/twc.2021.3065920
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发表时间：
2020-10
影响因子：
10.4
通讯作者：
M. Amiri;T. Duman;Deniz Gündüz;S. Kulkarni;H. Poor
中科院分区：
文献类型：
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作者：
M. Amiri;T. Duman;Deniz Gündüz;S. Kulkarni;H. Poor
我们研究联合边缘学习(Feel)，其中每个无线边缘设备都有自己的数据集，在作为参数服务器(PS)的无线接入点的帮助下协作学习全局模型。在每次迭代中，无线设备使用其本地数据和从PS接收的最新全局模型来执行本地更新，并通过无线衰落多址信道(MAC)将其本地更新发送到PS。PS然后根据通过无线MAC接收的信号更新全局模型，并将其与设备共享。受无线MAC的加性特性的启发，我们提出了一种模拟的空中聚合方案，在该方案中，设备以未编码的方式传输其本地更新。然而，与最近关于空中感受的文献不同，这里我们假设设备没有信道状态信息(CSI)，而PS具有不完美的CSI。另一方面，PS配备了多个天线，以缓解由于缺乏完美的CSI而加剧的信道破坏性影响。我们在PS处设计了一种接收波束形成方案，并证明了当PS上有足够多的天线时，该方案可以弥补理想CSI的不足。我们还推导了算法的收敛速度，突出了缺乏完美CSI的影响，以及PS天线的数量。实验结果和收敛分析都表明，随着PS天线数目的增加，该算法的性能得到改善，当PS天线数目足够多时，尽管没有理想的CSI，无线衰落MAC仍然是确定的。
We study federated edge learning (FEEL), where wireless edge devices, each with its own dataset, learn a global model collaboratively with the help of a wireless access point acting as the parameter server (PS). At each iteration, wireless devices perform local updates using their local data and the most recent global model received from the PS, and send their local updates to the PS over a wireless fading multiple access channel (MAC). The PS then updates the global model according to the signal received over the wireless MAC, and shares it with the devices. Motivated by the additive nature of the wireless MAC, we propose an analog ‘over-the-air’ aggregation scheme, in which the devices transmit their local updates in an uncoded fashion. However, unlike recent literature on over-the-air FEEL, here we assume that the devices do not have channel state information (CSI), while the PS has imperfect CSI. On the other hand, the PS is equipped with multiple antennas to alleviate the destructive effect of the channel, exacerbated due to the lack of perfect CSI. We design a receive beamforming scheme at the PS, and show that it can compensate for the lack of perfect CSI when the PS has a sufficient number of antennas. We also derive the convergence rate of the proposed algorithm highlighting the impact of the lack of perfect CSI, as well as the number of PS antennas. Both the experimental results and the convergence analysis illustrate the performance improvement of the proposed algorithm with the number of PS antennas, where the wireless fading MAC becomes deterministic despite the lack of perfect CSI when the PS has a sufficiently large number of antennas.