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A Novel Immune Optimization Algorithm for Fairness Resource Allocation in Cognitive Wireless Network

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Abstract

Cognitive wireless network (CWN) is a novel concept for improving the utilization of scarce wireless spectrum resources. Dynamic resource allocation is an important task in such systems. In this paper, a novel resource allocation algorithm for multi-user OFDM-based CWN is presented. It is formulated into a constraint problem, and an optimization algorithm based on novel immune clonal is proposed. The proposed algorithm fully takes into account the maximum tolerable interferences of primary user and the proportional fairness for secondary user. The suitable operators for solving the problem are designed, such as clonal, mutation, Baldwin learning, selection and so on. The simulation results show that the proposed algorithm achieves high system throughput with proportional fairness among the secondary users.

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Authors and Affiliations

  1. School of Computer Science and Technology, Xidian University, Xi’an, 710071, China

    Zheng-Yi Chai, Fang Liu & Yu-Tao Qi

  2. School of Information Science and Engineering, Hennan University of Technology, ZhengZhou, 450001, China

    Zheng-Yi Chai

  3. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, 710071, China

    Jian-She Wu

Authors
  1. Zheng-Yi Chai
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  2. Fang Liu
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  3. Yu-Tao Qi
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  4. Jian-She Wu
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Correspondence to Zheng-Yi Chai.

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Chai, ZY., Liu, F., Qi, YT. et al. A Novel Immune Optimization Algorithm for Fairness Resource Allocation in Cognitive Wireless Network. Wireless Pers Commun 69, 1671–1687 (2013). https://doi.org/10.1007/s11277-012-0657-8

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  • DOI: https://doi.org/10.1007/s11277-012-0657-8

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