TY  - JOUR
T1  - Optimizing Uplink MIMO Transmission for Model Uploadand Aggregation in Federated Learning
AU  - Yoo, Wonsik 
AU  - Park, Seok-Hwan 
JO  - The Journal of Korean Institute of Communications and Information Sciences
PY  - 2023
DA  - 2023/1/14
DO  - 10.7840/kics.2023.48.8.934
KW  - Federated learning
KW  - uplink
KW  - robust transmission
KW  - imperfect CSI
KW  - Optimization
AB  - This paper focuses on optimizing multi-antenna transmission to enhance the efficiency of model upload in digital federated learning systems. Unlike previous research that assumes perfect channel state information (CSI) for local model upload in federated learning, this work takes into consideration the imperfection of CSI and computes the achievable data rates accordingly. The problem of minimizing the mean squared error (MSE) of the global aggregated model is formulated, which is found to be non-convex. To address this non-convexity and obtain an efficient suboptimal solution, we propose an iterative algorithm based on Majorization Minimization. The advantages of the proposed algorithm are validated through numerical results.