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Spectrum Allocation in Cognitive Radio Networks Using Gene Therapy-Based Evolutionary Algorithms

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Abstract

Cognitive radio technology can be utilized to make optimal use of spectrum. Spectrum allocation is a critical operation for assigning appropriate idle-free frequency bands to the unlicensed users while reducing interference among all the users. The goal is to maximize the utilization of the available spectrum, and this problem is shown to be NP-hard which needs to be solved in real time. Accordingly, many evolutionary methods have been employed in the past to tackle the spectrum assignment problem, including genetic algorithm (GA) and differential evolution (DE). In this paper, a gene therapy method is proposed and applied to the genetic algorithm and differential evolution algorithm. The proposed algorithms’ effectiveness is evaluated using three utilization functions, namely max–sum reward (MSR), max–min reward (MMR), and max proportional fair (MPF). Gene therapy-based GA and DE outperform conventional GA and DE in terms of high convergence speed and quality of solution, according to the extensive simulation results.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Assam University, Silchar, 788011, Assam, India

    Wangjam Niranjan Singh

  2. Department of Computer Science and Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, 791109, Arunachal Pradesh, India

    Ningrinla Marchang

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  1. Wangjam Niranjan Singh
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Correspondence to Wangjam Niranjan Singh.

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Singh, W.N., Marchang, N. Spectrum Allocation in Cognitive Radio Networks Using Gene Therapy-Based Evolutionary Algorithms. Arab J Sci Eng 47, 10277–10293 (2022). https://doi.org/10.1007/s13369-021-06543-1

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