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Nature Inspired Optimization Algorithms Based Adaptation of Transmission Parameters in CR Based IoTs

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Abstract

Cognitive radio (CR) is a promising technology to overcome the challenge of additional spectrum requirement posed by internet of things (IoT) supported applications. This paper brings out the comparative performance analysis of different optimization techniques for adapting the transmission parameters in five distinct transmission scenarios for a multicarrier based CR-IoT network. Parameter adaptation problem is rather complex to be solved for a multicarrier system with large number of transmission variables. Inspired by the efficient exploration and exploitation abilities of recently proposed nature inspired meta-heuristic optimization algorithms, the application of these techniques has been investigated for solving the proposed multiobjective optimization problem.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Avneet Kaur, Surbhi Sharma & Amit Mishra

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  1. Avneet Kaur
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  2. Surbhi Sharma
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  3. Amit Mishra
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Correspondence to Avneet Kaur.

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Kaur, A., Sharma, S. & Mishra, A. Nature Inspired Optimization Algorithms Based Adaptation of Transmission Parameters in CR Based IoTs. Wireless Pers Commun 108, 2517–2540 (2019). https://doi.org/10.1007/s11277-019-06536-2

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  • DOI: https://doi.org/10.1007/s11277-019-06536-2

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