With the explosive growth of data and wireless devices, federated learning (FL) has emerged as a promising technology for large-scale intelligent systems. Utilizing the analog superposition of electromagnetic waves, over-the-air computation is an appealing approach to reduce the burden of communication in the FL model aggregation. However, with the urgent demand for intelligent systems, the training of multiple tasks with over-the-air computation further aggravates the scarcity of communication resources. This issue can be alleviated to some extent by training multiple tasks simultaneously with shared communication resources, but the latter inevitably brings about the problem of inter-task interference. In this paper, we study over-the-air multi-task FL (OA-MTFL) over the multiple-input multiple-output (MIMO) interference channel. We propose a novel model aggregation method for the alignment of local gradients for different devices, which alleviates the straggler problem that exists widely in over-the-air computation due to the channel heterogeneity. We establish a unified communication-computation analysis framework for the proposed OA-MTFL scheme by considering the spatial correlation between devices, and formulate an optimization problem of designing transceiver beamforming and device selection. We develop an algorithm by using alternating optimization (AO) and fractional programming (FP) to solve this problem, which effectively relieves the impact of inter-task interference on the FL learning performance. We show that due to the use of the new model aggregation method, device selection is no longer essential to our scheme, thereby avoiding the heavy computational burden caused by implementing device selection. The numerical results demonstrate the correctness of the analysis and the outstanding performance of the proposed scheme.
翻译:随着数据和无线设备的爆炸性增长,联合学习(FL)已成为大规模智能系统的有希望的技术。利用电磁波的模拟叠加,超空计算是减少FL模型集成中通信负担的一个诱人的方法。然而,随着智能系统的迫切需要,培训多重任务和超空计算使通信资源更加稀缺。通过培训多种任务和共享通信资源,这一问题可以在某种程度上得到缓解,但后者不可避免地带来跨任务干扰问题。在本文中,我们研究了超空计算多任务和多任务选择FL(OA-MTFL)的模拟叠加。我们提出了一个新的模型集成方法,用于调整本地的梯度,从而缓解了由于频道异质性而广泛存在的超空计算问题。我们为拟议的OA-MTFL系统创建了一个统一的通信转换分析框架,我们通过考虑空间-MTFL系统增量计算法的模拟模型, 从而有效地开发了这个系统平流成本分析, 从而展示了这个系统平流分析的系统化模型, 并优化了这个模型的升级的系统化模型, 展示了我们系统平流路端选择的系统结构的系统,从而展示了一个不平流分析结果。