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Design of cognitive radio system and comparison of modified whale optimization algorithm with whale optimization algorithm

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Abstract

Algorithms which are inspired from nature are gaining popularity because of their better convergence and simplicity. We use these algorithms to solve many technical as well as environmental problems. This paper proposes the Population based meta-heuristics optimization technique to fulfill the objectives of cognitive radio system (CR). To improve quality of service (QoS), various objectives of cognitive radio system are needed to be optimized by user. These objectives are bit error rate (BER), transmitting power, Throughput, Frequency spectral efficiency and signal interference. A modified whale optimization algorithm (MWOA) is proposed and applied to the design of cognitive radio system. This algorithm utilizes the random weight vector on location of humpback whales. It proposes exploration and exploitation phases in search space and balance between these two phases. Comparison of results has been carried out of Modified whale optimization algorithm with biogeography based optimization algorithm (BBO) and simulated annealing algorithm (SA). It is observed that the results obtained using MWOA are quite satisfying and it requires less number of iterations than that required in BBO and SA algorithms.

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  1. Department of Electronics and Communication Engineering, Guru Nanak Dev Engineering College Ludhiana, Ludhiana, Punjab, India

    Sumit Bansal & Munish Rattan

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  1. Sumit Bansal
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  2. Munish Rattan
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Correspondence to Sumit Bansal.

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Bansal, S., Rattan, M. Design of cognitive radio system and comparison of modified whale optimization algorithm with whale optimization algorithm. Int. j. inf. tecnol. 14, 999–1010 (2022). https://doi.org/10.1007/s41870-019-00346-2

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