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IRS-Aided Cyclostationary Spectrum Sensing in Dynamic Spectrum Access Networks

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Artificial Intelligence for Sustainable Energy (GENCITY 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1142))

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Abstract

Green wireless communications aim to reduce the environmental impact of wireless communication systems while maintaining or improving their performance. One technique used in wireless communication systems is spectrum sensing which is an enabling technique that provides information on spectrum availability for cognitive radio. Cyclostationary spectrum sensing is a particular sensing approach that takes use of the built-in periodicities characteristic to most man-made signals. However, when channel fading conditions are severe, the interference can affect primary users and the wireless communication systems consume a significant amount of energy and generate greenhouse gas emissions, leading to various environmental and health impacts to maintain quality. To combat this issue, intelligent reflecting surface aided cyclostationary spectrum sensing is proposed. Cases where the line of sight between the primary user and its destination is known, were investigated. Receiver Output Characteristic curves were produced with and without the use of intelligent reflecting surfaces in cyclostationary spectrum sensing to determine if it retains the information from the primary user in severe channel fading conditions. Simulation results verify that the use of intelligent reflecting surfaces can improve the performance of cyclostationary detection for spectrum sensing.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of the West Indies, St. Augustine Campus., St. Augustine, Trinidad and Tobago

    Sanjeev Raghoonath & Sean Rocke

Authors
  1. Sanjeev Raghoonath
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  2. Sean Rocke
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Corresponding author

Correspondence to Sanjeev Raghoonath .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Jimson Mathew

  2. Department of Electrical and Electronic Engineering, University of Southampton Malaysia, Iskandar Puteri, Johor, Malaysia

    Lenin Gopal

  3. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China

    Filbert H. Juwono

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Raghoonath, S., Rocke, S. (2024). IRS-Aided Cyclostationary Spectrum Sensing in Dynamic Spectrum Access Networks. In: Mathew, J., Gopal, L., Juwono, F.H. (eds) Artificial Intelligence for Sustainable Energy. GENCITY 2023. Lecture Notes in Electrical Engineering, vol 1142. Springer, Singapore. https://doi.org/10.1007/978-981-99-9833-3_11

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  • DOI: https://doi.org/10.1007/978-981-99-9833-3_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9832-6

  • Online ISBN: 978-981-99-9833-3

  • eBook Packages: EnergyEnergy (R0)

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