Unmanned aerial vehicles (UAVs) facilitate information collection greatly in Internet of Things (IoT) systems. On the other hand, non-orthogonal multiple access (NOMA) is regarded as a promising technology to provide high spectral efficiency and support massive connectivity in 5G 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 different locations of UAV is challenging. In this paper, we propose a general NOMA-enabled UAV-assisted data collection (NUDC) protocol to solve the formulated sum rate maximization problem such that 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. Extensive simulation results demonstrate the effectiveness of our proposed protocol.
|Original language||English (US)|
|Title of host publication||2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - May 2020|
|Event||2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Seoul, Korea, Republic of|
Duration: May 25 2020 → May 28 2020
|Name||IEEE Wireless Communications and Networking Conference, WCNC|
|Conference||2020 IEEE Wireless Communications and Networking Conference, WCNC 2020|
|Country/Territory||Korea, Republic of|
|Period||5/25/20 → 5/28/20|
Bibliographical noteFunding Information:
Fig. 7: Sum rate comparison with different number of sensors. V. CONCLUSION In this paper, we have investigated a UAV-assisted uplink NOMA system that the UAV is employed to collect data from multiple sensors with NOMA. A general NOMA-enabled UAV-assisted data collection (NUDC) protocol has been proposed for solving the formulated sum rate maximization problem. We decoupled the formulated problem into three sub-problems of the placement of UAV, sensor grouping, and power control, and then solved them separately. Extensive performance evaluations have demonstrated that our NUDC protocol not only provides the optimal location for the UAV in data collection, but also effectively reduces the inter-sensor interference and forms appropriate NOMA groups, thereby achieving the performance gains. VI. ACKNOWLEDGMENT This work was supported in part by the National Natural Science Foundation of China under Grants 61936014 and 61901302, in part by the National Key Research and Development Project under Grant 2019YFB2102300, 2019YFB2102301, and 2017YFE0119300. This work was also supported in part by the open research fund of National Mobile Communications Research Laboratory, Southeast University (No. 2020D01), in part by the Scientific Research Project of Shanghai Science and Technology Committee under Grant 19511103302, and in part by the National Science Foundation under Grant CPS-1932413 and ECCS-1935915. REFERENCES
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