Improved HF cognitive multi-channel selection algorithm based on UCB

被引：1
|
作者：
Wang D. [1 ]
Wang Y. [1 ]
Sun Q. [1 ]
Zhang W. [1 ]
Wang Y. [1 ]
机构：
[1] College of Information and Navigation, Air Force Engineering University, Xi'an
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2019年 / 49卷 / 05期
关键词：
Cognitive radio; HF (high frequency) communication; Multi-channel selection; UCB (upper confidence bound);
D O I：
10.3969/j.issn.1001-0505.2019.05.012
中图分类号：
学科分类号：
摘要：
To improve the successful transmission rate of UCB (upper confidence bound) algorithm in HF (high frequency) multi-channel selection, combined with the background of HF broadband application, an improved HF cognitive multi-channel selection algorithm based on UCB is proposed. By regarding the HF radio station with cognitive radio technology as the cognitive user according to the principle of the cognitive radio, the UCB index in reinforcement learning is utilized to rank the HF channels, and the sequential sensing strategy is introduced to select multiple channels, until the number of idle channels required is selected to provide an equivalent broadband transmission for cognitive users. Simulation results show that compared with the original UCB multi-channel selection algorithm, the proposed algorithm appropriately increases the number of channel sensing times by the sequence sensing strategy: when the required number of channels is 4, the successful transmission rate can be improved by a maximum of 71.61%, the cumulative rewards can be improved by an average of 79.24%, and the cumulative data transmission time can be improved by an average of 3.67 times. © 2019, Editorial Department of Journal of Southeast University. All right reserved.
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页码：897 / 903
页数：6
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