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Cognitive Radio Engine Design Based on Ant Colony Optimization

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Abstract

In this letter, a mutated ant colony optimization (MACO) cognitive radio engine is proposed, and it is the first time to apply ACO algorithm to this problem. The cognitive radio is a promising technology nowadays to alleviate the apparent scarcity of available radio spectrum, and the cognitive radio engine determines the optimal radio transmission parameters for the system. The cognitive engine problem is usually solved by genetic algorithm (GA), however, the GA converges slowly and its performance can still be improved. Hence, MACO algorithm with excellent performance is applied to the cognitive engine in this letter. Simulation results show that the fitness scores obtained by the MACO engine are much better than the ACO and GA engines in different scenarios.

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Authors and Affiliations

  1. School of Information and Telecommunication Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China

    Nan Zhao

  2. School of Electronics and Information Technology, Harbin Institute of Technology, Harbin, Heilongjiang, 50001, China

    Shuying Li & Zhilu Wu

Authors
  1. Nan Zhao
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  2. Shuying Li
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  3. Zhilu Wu
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Correspondence to Nan Zhao.

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Zhao, N., Li, S. & Wu, Z. Cognitive Radio Engine Design Based on Ant Colony Optimization. Wireless Pers Commun 65, 15–24 (2012). https://doi.org/10.1007/s11277-011-0225-7

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  • DOI: https://doi.org/10.1007/s11277-011-0225-7

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