A Variable Step-size Diffusion LMS Algorithm With MSD-based Event-triggered Method for Low Communication Cost
摘要
This paper proposes a variable step-size diffusion least-mean-square algorithm based on an event-triggered combination method. While much of the existing research in distributed system estimation focuses on improving the convergence rate and accuracy, relatively little attention has been paid to energy efficiency in communications. Thus, this paper proposes an algorithm that aims to reduce communication cost with minimal performance degradation. A variable step size is proposed to achieve stable convergence and accurate estimation, and an event-triggered strategy is designed based on the derived mean square deviation. The dynamic triggering threshold is set to respond adaptively to abrupt decreases in the mean square deviation. The simulation results demonstrate that the proposed algorithm maintains desirable performance with significantly reduced communication cost.