Iterative-Promoting Variable Step Size Least Mean Square Algorithm for Accelerating Adaptive Channel Estimation
Abstract
Invariable step size based least-mean-square error (ISS-LMS) was considered as a very simple adaptive filtering algorithm and hence it has been widely utilized in many applications, such as adaptive channel estimation. It is well known that the convergence speed of ISS-LMS is fixed by the initial step-size. In the channel estimation scenarios, it is very hard to make tradeoff between convergence speed and estimation performance. In this paper, we propose an iterative-promoting variable step size based least-mean-square error (VSS-LMS) algorithm to control the convergence speed as well as to improve the estimation performance. Simulation results show that the proposed algorithm can achieve better estimation performance than previous ISS-LMS while without sacrificing convergence speed.
Cite
@article{arxiv.1501.07107,
title = {Iterative-Promoting Variable Step Size Least Mean Square Algorithm for Accelerating Adaptive Channel Estimation},
author = {Beiyi Liu and Guan Gui and Li Xu and Nobuhiro Shimoi},
journal= {arXiv preprint arXiv:1501.07107},
year = {2015}
}
Comments
6 pages, 8 figures, conference