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Enhancing Spectrum Efficiency and Energy Harvesting Selection for Cognitive Using a Hybrid Technique

  • M. BalasubramanianEmail author
  • V. Rajamani
  • S. Puspha
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 98)

Abstract

Cognitive Radio Networks (CRN) is one of the evolving technologies for detecting available channels automatically in a wireless spectrum in which several researchers have developing new concepts and algorithms to improve its efficiency. Two main issues that are considered to be important in wireless communications are energy effectiveness and spectrum efficiency in which the performance is increased by using CRN as it is compact with both primary user (PU) and secondary user (SU). Both PU and SU are recognized by the licensed and unlicensed bands. In this paper, the hybrid combination of dynamic Genetic Algorithm (GA) with Token Passing Algorithm (TPA) is proposed to enhance the efficiency for accessing the given spectrum for PU and SU. In this proposed work, maximum throughput is achieved by increasing the efficiency of spectrum and improving energy harvesting in channel selection. The collision constraints, energy causality constraints, efficient resource allocation. And sensing occupied channels are considered for average channel capacity for improving throughput performance. The main motivation of this paper is to avoid adjacent channel interference and co-channel interference using the proposed method by achieving energy harvesting and maximum spectrum efficiency for CRN.

Keywords

Cognitive Radio Networks (CRN) Genetic Algorithm (GA) Token Passing Algorithm (TPA) Energy harvesting Spectrum efficiency 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of CSESPIHER AvadiChennaiIndia
  2. 2.Veltech Multitech Dr. Rangarajan Dr. Sakunthala Engineering CollegeChennaiIndia
  3. 3.SPIHER AvadiChennaiIndia

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