4.8 Article

UAV-Assisted Data Collection With Nonorthogonal Multiple Access

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 1, Pages 501-511

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3005271

Keywords

NOMA; Power control; Data collection; Uplink; Internet of Things; Protocols; Resource management; Data collection; hypergraph; nonorthogonal multiple access (NOMA); unmanned aerial vehicle (UAV)

Funding

  1. National Key Research and Development Project [2019YFB2102300, 2019YFB2102301]
  2. National Natural Science Foundation of China [61936014, 61901302]
  3. Scientific Research Project of Shanghai Science and Technology Committee [19511103302]
  4. Fundamental Research Funds for the Central Universities
  5. Shandong Provincial Key Laboratory of Wireless Communication Technologies [SDKLWCT-2019-02]
  6. Shenzhen Research Institute of Big Data [2019ORF01014]
  7. National Science Foundation [CPS-1932413, ECCS-1935915]

Ask authors/readers for more resources

This article proposes a general NOMA-enabled UAV-assisted data collection (NUDC) protocol to maximize the sum rate of a wireless sensor network (WSN) by considering the UAV location, sensor grouping, and power control. A joint signal-to-interference ratio (SIR) hypergraph-based grouping and power control (SHG-PC) NOMA scheme is provided to efficiently obtain appropriate sensor grouping and optimal power control solutions, utilizing hypergraph and greedy coloring algorithm to find optimized group relationships. Extensive simulation results demonstrate the efficiency of the proposed protocol.
Unmanned aerial vehicles (UAVs) facilitate information collection greatly in the Internet-of-Things (IoT) systems due to their superior flexibility and mobility. On the other hand, nonorthogonal multiple access (NOMA) is regarded as a promising technology to provide high spectral efficiency and support massive connectivity in fifth-generation networks. The integration of NOMA into UAV-assisted wireless networks shows great potential, but how to determine the user grouping and power allocation in NOMA according to the high mobility of UAV is challenging. In this article, we propose a general NOMA-enabled UAV-assisted data collection (NUDC) protocol to maximize the sum rate of a wireless sensor network (WSN), where the location of UAV, sensor grouping, and power control are jointly considered. Moreover, a joint signal-to-interference ratio (SIR) hypergraph-based grouping and power control (SHG-PC) NOMA scheme is provided to obtain the appropriate sensor grouping and the optimal power control solutions efficiently, in which the hypergraph and the greedy coloring algorithm are exploited to find out the optimized group relationships. Extensive simulation results demonstrate the efficiency of our proposed protocol.

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