Link Connectivity-Based Access Selection Method for Multi-UAV Heterogeneous Networks

Author:

Wen Shaojie1ORCID,Deng Lianbing1,Liu Zengliang2

Affiliation:

1. Zhuhai Da Hengqin Science and Technology Development Co., Ltd., Zhuhai, P. R. China

2. Institute of Information Operation, National Defence University of PLA, Beijing, P. R. China

Abstract

While UAV ad hoc networks have made significant progress, implementing it in most of real-application scenarios is challenging due to data explosion. Instead of only ad hoc mode, this work simultaneously considers non-orthogonal multiple access technique (NOMA) and ad hoc mode to handle the problem. We further propose an effective framework to seamlessly integrate these two techniques, namely Multi-UAV heterogeneous networks. Specifically, we formulate the framework as a mixed integer nonlinear programming, in which original problem can be decomposed into two sub-problems, e.g., access mode selection for UAV to UAV mode (U2U) and UAV to Ground Base mode (U2G), and transmission rate optimization. For the access mode selection, to reduce the computational complexity at each UAV, a candidate set is constructed based on the connection time and link quality. After that, the component in candidate set that maximizes the objective function is selected as the access point. Due to the different communication techniques in U2U mode and U2G mode, we can obtain the optimal rate for each UAV by using the NOMA technique in U2G mode and channel prediction method with local information in U2U mode, respectively. For the transmission rate optimization, an effective algorithm is proposed for U2G mode and U2U mode, which considers the effects of the network connectivity and link quality on the optimization performance. Simulation results show that our method can reduce the outage rate and improve the network throughput effectively.

Funder

Postdoctoral Research Foundation of China

Guangdong-Macau Joint STI Project intelligent target detecting and tracking on electronic fence

Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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