Publication detail

Robust Incremental Least Mean Square Algorithm With Dynamic Combiner

QADRI, S. ARIF, M. NASEEM, I. MOINUDDIN, M.

Original Title

Robust Incremental Least Mean Square Algorithm With Dynamic Combiner

Type

journal article in Web of Science

Language

English

Original Abstract

In distributed wireless networks, the adaptation process depends on the information being shared between various nodes. The global minimum, is therefore, likely to be affected when the information shared between the nodes gets corrupted. This could happen due to several reasons namely link failure, noisy environment and erroneous data etc. In this research, we propose a computationally efficient robust incremental least mean square (RILMS) algorithm to resolve the aforementioned issues. Essentially, a fusion step is introduced in the framework of the incremental least mean square (ILMS). Prior to adaptation at a node, the information shared by the neighbouring node is fused with the temporally preceding information of the node using an efficient combiner. An adaptive fusion strategy is proposed resulting in dynamic weight assignment for the fusion step. Closed form expression for the steady-state excess mean square error (EMSE) is derived and the performance of the proposed algorithm is evaluated for the noisy link environments and compared to the existing algorithms. Extensive experiments show the efficacy of the proposed approach compared to the contemporary methods. The proposed algorithm is found to be robust against the link failure and local node divergence problems. The improved performance of the proposed RILMS algorithm comes with a significant reduction in computational complexity compared to the convex combination based ILMS (CILMS) approach.

Keywords

Distributed networks, incremental least mean squares algorithm, decentralized estimation, steady-state analysis, noisy link

Authors

QADRI, S.; ARIF, M.; NASEEM, I.; MOINUDDIN, M.

Released

18. 7. 2022

ISBN

2169-3536

Periodical

IEEE Access

Year of study

10

Number

10

State

United States of America

Pages from

75135

Pages to

75143

Pages count

9

URL

https://ieeexplore.ieee.org/document/9832595

BibTex

@article{BUT179080,
  author="Syed Safi Uddin {Qadri} and Muhammad {Arif} and Imran {Naseem} and Muhammad {Moinuddin}",
  title="Robust Incremental Least Mean Square Algorithm With Dynamic Combiner",
  journal="IEEE Access",
  year="2022",
  volume="10",
  number="10",
  pages="75135--75143",
  doi="10.1109/ACCESS.2022.3192018",
  issn="2169-3536",
  url="https://ieeexplore.ieee.org/document/9832595"
}