DYNAMIC SMART GRID COMMUNICATION PARAMETERS BASED COGNITIVE RADIO NETWORK

Authors

  • Haider Tarish Haider Department of Computer Engineering, University of Mustansiriyah, 10001 Baghdad, Iraq http://orcid.org/0000-0002-2569-0031
  • Dhiaa Halboot Muhsen
  • Haider Ismael Shahadi
  • Ong Hang See
  • Wilfried Elmenreich

DOI:

https://doi.org/10.14311/AP.2019.59.0248

Keywords:

Smart grid, Home area network, Cognitive radio, Decision engine, Differential evolution

Abstract

The demand for more spectrums in a smart grid communication network is a significant challenge in originally scarce spectrum resources. Cognitive radio (CR) is a powerful technique for solving the spectrum scarcity problem by adapting the transmission parameters according to predefined objectives in an active wireless communication network. This paper presents a cognitive radio decision engine that dynamically selects optimal radio transmission parameters for wireless home area networks (HAN) of smart grid applications via the multi-objective differential evolution (MODE) optimization method. The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. Simulation results highlight the superiority of the proposed system in terms of accuracy and convergence as compared with other evolution algorithms (genetic optimization, particle swarm optimization, and ant colony optimization) for different communication modes (power saving mode, high throughput mode, emergency communication mode, and balanced mode).

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Published

2019-07-01

Issue

Section

Articles

How to Cite

Haider, H. T., Muhsen, D. H., Shahadi, H. I., See, O. H., & Elmenreich, W. (2019). DYNAMIC SMART GRID COMMUNICATION PARAMETERS BASED COGNITIVE RADIO NETWORK. Acta Polytechnica, 59(3), 248-259. https://doi.org/10.14311/AP.2019.59.0248
Received 2018-11-29
Accepted 2019-04-16
Published 2019-07-01