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Adaptive beam formation and channel allocation using substance near multicast protocol and CS-iEHO

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Abstract

Multiple-input multiple-output (MIMO) systems invite many researchers to contribute more in channels selection for improving the performance for enhancing the throughput and quality of the received signal. It is important to notice that target channel selection will also improve the performance while decreasing the signal-interference-plus-noise ratio. In MIMO channel allocation, it is found that utilization of resources tends to be a dangerous issue which could be tackled by identifying secondary users in addition to primary user for disseminating the information. This paper focuses on allocating the dynamic channels effectively by applying a centralized heuristic algorithm which is referred as cuckoo search with improved elephant herding optimization. In the previous approach, poor resource allocation causes desperate issue in MIMO channel allocation while calculating the energy of each user available in the network. Substance near multicast protocol has been applied for optimizing the energy along with elephant herding optimization algorithm in order to allocate channels dynamically for global optimization process. An improved elephant herding optimization algorithm for multiuser MIMO framework is integrated in the overall remote region. This initiative signifies the greatest number of mutually legitimate clients and the feasible bit rates of clients in the overall remote region. The iEHO algorithm concurrently enhances energy proficiency and framework throughput by client assortment and power distribution. Our trial outcomes ascertained that the recommended method of working fundamentally excelled the essential EHO. Simulation has been done by using MATLAB which is assumed to be the best simulator to show the results without missing the clarity.

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Authors and Affiliations

  1. Department of BME, Sahrdaya College of Engineering and Technology, Kodakara, Kerala, India

    Yuvaraj Velusamy

  2. Department of Computer Science and Engineering, Sahrdaya College of Engineering and Technology, Kodakara, Kerala, India

    Rajeswari Manickam

  3. Department of Biomedical Engineering, Park College of Engineering and Technology, Coimbatore, India

    Sivamani Chinnaswamy

  4. Department of Computer Science and Engineering, Anna University Regional Campus, Tirunelveli, India

    Golden Julie Eanoch

  5. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India

    Harold Robinson Yesudhas

  6. Department of Computer Science and Engineering, GIET University, Gunupur, India

    Raghvendra Kumar

  7. Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hoang Viet Long

  8. Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hoang Viet Long

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  1. Yuvaraj Velusamy
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  2. Rajeswari Manickam
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  3. Sivamani Chinnaswamy
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  4. Golden Julie Eanoch
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  5. Harold Robinson Yesudhas
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  6. Raghvendra Kumar
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  7. Hoang Viet Long
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Correspondence to Hoang Viet Long.

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Communicated by V. Loia.

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Velusamy, Y., Manickam, R., Chinnaswamy, S. et al. Adaptive beam formation and channel allocation using substance near multicast protocol and CS-iEHO. Soft Comput 25, 4663–4676 (2021). https://doi.org/10.1007/s00500-020-05476-5

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  • DOI: https://doi.org/10.1007/s00500-020-05476-5

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