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Power allocation in cognitive radio networks over Rayleigh-fading channels with hybrid intelligent algorithms

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Abstract

In this paper, we introduce a hybrid strategy which combines pattern search (PS) optimization and genetic algorithm (GA) to address the problem of power allocation in cognitive radio networks. Considering the fluctuating interference thresholds in cognitive networks, an approach for promoting the coexistence of licensed users and cognitive users is designed. Secondly, based on the analysis of transmission outage probability, a corresponding objective function with regard to the power allocation over Rayleigh fading channels is obtained. It is a difficult task to obtain this objective function directly by using traditional methods, such as common mathematical deduction or linear programming, due to the nonlinearity and complexity of the underlying optimization problem. Inspired by the concept of intelligent algorithms, we employ the scheme of combining PS optimization and GA method, which are both efficient intelligent algorithms to address this challenge. The advantage of this hybrid strategy is that it can overcome the instability problem of GA as well as the local convergency problem of PS method. Thus, the hybrid intelligent method can attain a global and steady outcome. We improve the performance of power allocation strategy with an acceptable increase in computation overhead. The numerical results are encouraging and show that the proposed approach is worthy of consideration in achieving complicated power optimization. Hence, we achieve steady and rational outcomes by applying the proposed hybrid strategy when traditional method is to be ineffective in addressing the nonlinear objective.

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Acknowledgements

The authors would like to thank the editor and the reviewers whose constructive comments will help improve the presentation of this paper. This work was supported by the National Natural Science Foundation of China under Grant 51404211 and Natural Science Foundation of Zhejiang Province under Grant LY14F010009.

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Authors and Affiliations

  1. College of Information Engineering, Zhejiang University of Technology, No. 288 Liuhe Road, Xihu District, Hangzhou, China

    Feng Li & Li Wang

  2. School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Kwok-Yan Lam

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  1. Feng Li
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Correspondence to Feng Li.

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Li, F., Lam, KY. & Wang, L. Power allocation in cognitive radio networks over Rayleigh-fading channels with hybrid intelligent algorithms. Wireless Netw 24, 2397–2407 (2018). https://doi.org/10.1007/s11276-017-1476-3

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