UAV-Aided NOMA Networks with Optimization of Trajectory and Precoding

Xiaowei Pang, Zan Li, Xiaoming Chen, Yang Cao, Nan Zhao, Yunfei Chen, Zhiguo Ding

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The explosive data traffic and connections in 5G networks require the use of non-orthogonal multiple access (NOMA) to accommodate more users. Unmanned aerial vehicle (UAV) can be exploited with NOMA to improve the situation further. In this paper, we propose a UAV-Assisted NOMA network, in which the UAV and base station (BS) cooperate with each other to serve ground users simultaneously. First, the sum rate of the UAV-served users is maximized via alternate user scheduling and UAV trajectory, with its interference to the BS-served users below a threshold. Then, the optimal NOMA precoding vectors are obtained to cancel the interference from the BS to the UAV-served user. Numerical results are provided to evaluate the effectiveness of the proposed algorithms for the hybrid NOMA and UAV network.

Original languageBritish English
Title of host publication2018 10th International Conference on Wireless Communications and Signal Processing, WCSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538661192
DOIs
StatePublished - 30 Nov 2018
Event10th International Conference on Wireless Communications and Signal Processing, WCSP 2018 - Hangzhou, China
Duration: 18 Oct 201820 Oct 2018

Publication series

Name2018 10th International Conference on Wireless Communications and Signal Processing, WCSP 2018

Conference

Conference10th International Conference on Wireless Communications and Signal Processing, WCSP 2018
Country/TerritoryChina
CityHangzhou
Period18/10/1820/10/18

Keywords

  • Interference avoidance
  • NOMA
  • precoding
  • trajectory optimization
  • UAV

Fingerprint

Dive into the research topics of 'UAV-Aided NOMA Networks with Optimization of Trajectory and Precoding'. Together they form a unique fingerprint.

Cite this