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Optimizing Resource Allocation of Wireless Networks with Carrier Aggregation Using Evolutionary Programming

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Advances in Nature-Inspired Computing and Applications

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

In this chapter, we propose a resource allocation scheme for wireless networks that aims to maximize the total data rate and attain certain Quality of Service (QoS) parameters using an Evolutionary Programming (EP) heuristic. The performance of the resource allocation algorithm is verified and compared to others in the literature using computational simulations. In these simulations, we also consider current and candidate techniques for next-generation networks such as f-OFDM (filtered-Orthogonal Frequency Division Multiplexing ) and carrier aggregation in order to show that is possible to provide higher data rate in relation to 4G networks and other algorithms in the literature.

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Acknowledgements

I would like to express my special thanks of gratitude to my parents and friends who helped me a lot in finalizing this project.

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Authors and Affiliations

  1. Institute of Informatics, Federal University of Goiás, Alameda Palmeiras, Quadra D, Câmpus Samambaia, Goiânia, Goiás, CEP 74690-900, Brazil

    Marcus Vinícius Gonzaga Ferreira & Flávio Henrique Teles Vieira

Authors
  1. Marcus Vinícius Gonzaga Ferreira
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  2. Flávio Henrique Teles Vieira
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Corresponding author

Correspondence to Marcus Vinícius Gonzaga Ferreira .

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Editors and Affiliations

  1. VIT Bhopal University, Bhopal, Madhya Pradesh, India

    Shishir Kumar Shandilya

  2. Sagar Institute of Research, Technology and Science, Bhopal, Madhya Pradesh, India

    Smita Shandilya

  3. Liverpool Hope University, Liverpool, UK

    Atulya K. Nagar

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Ferreira, M.V.G., Vieira, F.H.T. (2019). Optimizing Resource Allocation of Wireless Networks with Carrier Aggregation Using Evolutionary Programming. In: Shandilya, S., Shandilya, S., Nagar, A. (eds) Advances in Nature-Inspired Computing and Applications. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-96451-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-96451-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96450-8

  • Online ISBN: 978-3-319-96451-5

  • eBook Packages: EngineeringEngineering (R0)

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