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Weighted Sum Rate Maximization for NOMA-Based UAV Networks

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 352)

Abstract

The unmanned aerial vehicle (UAV) based aerial base station (BS) has emerged as a feasible solution to the high traffic demands of the future wireless networks. It is essential that UAV can integrat with non-orthogonal multiple access (NOMA) to support the massive connection service. In this paper, we study the problem of weighted sum rate maximization in the downlink for NOMA-based UAV networks. This is a non-convex optimization problem, which is intractable to be directly solved using the convex optimization method. To deal with the problem, we propose an efficient iterative algorithm via variable substitution and relaxation methods, then construct the framework of alternating optimization to solve the problem joint placement and power allocation optimization. The simulation results show that the proposed algorithm performs better than other schemes.

Keywords

  • Unmanned aerial vehicle
  • Non-orthogonal multiple access
  • Power allocation
  • Placement optimization
  • Weighted sum rate

This work was partially supported by the National Natural Science Foundation of P. R. China(No.61701064), Basic Research and Frontier Exploration Project of Chongqing (cstc2019jcyj-msxmX0264).

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  • DOI: 10.1007/978-3-030-67720-6_4
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Correspondence to Xiaona Yang .

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Wang, Z., Zhang, H., Wan, X., Fan, Z., Yang, X., Ji, Y. (2021). Weighted Sum Rate Maximization for NOMA-Based UAV Networks. In: Gao, H., Fan, P., Wun, J., Xiaoping, X., Yu, J., Wang, Y. (eds) Communications and Networking. ChinaCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-030-67720-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-67720-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67719-0

  • Online ISBN: 978-3-030-67720-6

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