1. Federated learning-based user access strategy and energy consumption optimization in cell-free massive MIMO network
- Author
-
Yuanyuan YAO, Yiqiu LIU, Sai HUANG, Chunyu PAN, Xuehua LI, and Xin YUAN
- Subjects
cell-free massive MIMO ,user access ,intelligent sensing ,AP selection ,energy consumption optimization ,Telecommunication ,TK5101-6720 - Abstract
To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output (CF-mMIMO) network, a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First, users were evaluated and ranked for their channel quality and stability after channel sensing, and suitable access points were selected in sequence according to the order of the channel state information.Second, considering issues such as users' energy consumption and data security, a federal learning framework was used to enhance user's data privacy and security.Meanwhile, an alternating optimization variables algorithm based on energy consumption optimization was proposed to optimize the multi-dimensional variables, for the purpose of minimizing the total energy consumption of the system.Simulation results show that compared with the traditional user-centric in massive MIMO, the proposed access strategy can improve the average uplink reachable rate of users by 20%, and the uplink rate of users with poor channels can be double improved; in terms of energy consumption optimization, the total energy consumption can be reduced by much more than 50% after optimization.
- Published
- 2023
- Full Text
- View/download PDF