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A Low-Complexity Power Allocation Method in Ultra-dense Network

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Abstract

This paper considers the downlink power allocation in the ultra-dense network. To acquire the maximum sum rate of all the users, we first make the appropriate approximate hypothesis on the interference, and then adopt the Lagrangian Multiplier method and Karush-Kuhn-Tucker condition to obtain the expression of the optimum power allocation. Finally, the iteratively searching water filling algorithm is used to allocate power for each access node, when the total power is limited. Due to the consideration of the computation complexity of the iteratively searching algorithm, we applied the low-complexity water filling algorithm into the power allocation to reduce the iteration times. The simulation results have shown that the performance of the both two water filling algorithms are close, and can improve the sum rate of the users in the ultra-dense network, and the low-complexity water filling algorithm can converge to the optimum solution more quickly.

This work was supported by the China’s 863 Project (No. 2015AA01A709), the National S&T Major Project (2014ZX03004003), Science and Technology Program of Beijing (No. D161100001016002), S&T Cooperation Projects (No. 2015DFT10160B), State Key Laboratory of Wireless Mobile Communications, China Academy of Telecommunications Technology (CATT), and Beijing Samsung Telecom R&D Center.

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Correspondence to Jie Zeng .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Su, X., Liu, B., Zeng, J., Wang, J., Xu, X. (2018). A Low-Complexity Power Allocation Method in Ultra-dense Network. In: Huang, M., Zhang, Y., Jing, W., Mehmood, A. (eds) Wireless Internet. WICON 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 214. Springer, Cham. https://doi.org/10.1007/978-3-319-72998-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-72998-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72997-8

  • Online ISBN: 978-3-319-72998-5

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