Abstract
In this paper, we study the transmission power allocation of the secondary base station to the secondary user in cognitive radio networks when multiple primary users (PU) and multiple secondary users (SU) adopt NOMA. In the proposed Underlay communication scheme, the communication quality of the primary user should be greater than the preset threshold, otherwise the secondary user communication will be interrupted. The signal-to-noise ratio of the secondary user should be greater than the preset threshold and meet the minimum communication quality requirements of the secondary user. Otherwise, the communication of the secondary user is interrupted. Finally, on the premise of ensuring the quality of service (QoS) of primary and secondary users, the cumulative total interference of secondary users to primary users should not exceed the Interference temperature threshold. Therefore, the convex optimization algorithm is used to maximize the power coefficient of downlink allocation of radio cognitive network, considering the constraints of mutual interference between secondary users, interference between secondary users and primary users, signal-to-noise ratio of secondary users, and interference temperature. This power distribution method is easy to be implemented in practical systems because of its low implementation complexity. Simulation results show that compared with the traditional orthogonal multiple access (OFDMA) scheme and the cooperative OMA scheme, the proposed scheme can better allocate the power coefficients in the downlink, better allocate the system spectrum resources, and lower the probability of secondary user outage.
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Acknowledgement
The authors would like to thank the anonymous reviewers for their selfless reviews and valuable comments, which have improved the quality of our original manuscript.
Funding
This work was partially supported by the National Natural Science Foundation of China (No.61876089, No. 61771410), by the Talent Introduction Project of Sichuan University of Science & Engineering (No. 2020RC22), by the Zigong City Key Science and Technology Program (No. 2019YYJC16), by the Teaching Reform Research Project of Sichuan University of Science & Engineering (JG-2121), by the Enterprise Informatization and Internet of Things Measurement and Control Technology Sichuan Provincial Key Laboratory of universities (No.2020WZY01).
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Li, H. et al. (2022). Sub-base Station Power Optimization Based on QoS and Interference Temperature Constraints for Multi-user Input and Output. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13338. Springer, Cham. https://doi.org/10.1007/978-3-031-06794-5_7
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DOI: https://doi.org/10.1007/978-3-031-06794-5_7
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