@inproceedings{251e50f5f12948a685d64162d1816a8e,
title = "Artificial Bee Colony DLMS Beyond Mean Square Error Boundary in Ad-hoc WSN",
abstract = "A new Diffusion Artificial Bee Colony (DABC) heuristic algorithm is developed to estimate system parameters in Wireless Sensor Networks (WSNs). The main contribution is the incorporation of ABC algorithm in the traditional Diffusion Least Mean Square (DLMS) algorithm which leads to a better Mean Square Error (MSE) performance. The DABC algorithm shows excellent convergence beyond the noise variance boundary. In the diffusion stage, each node shares the local best cost function and corresponding local best particle position to immediate neighboring nodes. The extensive simulations show that the proposed DABC approach achieves excellent MSE improvement (MSD deterioration) in comparison to existing DLMS algorithms.",
keywords = "artificial bee colony (abc), channel estimation, diffusion least mean square (dlms), mean square error (mse), wireless sensor network (wsn)",
author = "Almohammedi, \{Ali M.\} and Azzedine Zerguine and Mohamed Deriche and Sait, \{Sadiq M.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022 ; Conference date: 04-12-2022 Through 06-12-2022",
year = "2022",
doi = "10.1109/CICN56167.2022.10008253",
language = "English",
series = "Proceedings - 2022 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "572--576",
booktitle = "Proceedings - 2022 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022",
address = "United States",
}