Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer

LIU Zhixin; ZHAO Songhan; YANG Yi; YUAN Yazhou

doi:10.11999/JEIT220195

Volume 44 Issue 7

Jul. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(7): 2325-2331

LIU Zhixin, ZHAO Songhan, YANG Yi, YUAN Yazhou. Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195

Citation:

LIU Zhixin, ZHAO Songhan, YANG Yi, YUAN Yazhou. Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195

Citation:

LIU Zhixin, ZHAO Songhan, YANG Yi, YUAN Yazhou. Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195

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Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer

doi: 10.11999/JEIT220195 cstr: 32379.14.JEIT220195

School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

Funds: The National Natural Science Foundation of China (61873223)

Received Date: 2022-02-28
Rev Recd Date: 2022-04-05

Available Online: 2022-04-15

Publish Date: 2022-07-25

Abstract

Abstract

In order to mitigate the adverse effect of blockages between the Unmanned Aerial Vehicle (UAV) and Ground Users (GUs), a throughput maximization algorithm for an Intelligent Reflecting Surface (IRS)-aided UAV communication network is proposed. First, considering the constraints of the energy causality, the IRS phase-shift, the UAV mobility, etc, a multi-variable coupling optimization problem is proposed with jointly optimizing the phase-shift of the IRS, the resource allocation of GUs, and the UAV trajectory. Second, the original non-convex problem is decomposed into three simpler sub-problems via the Block Coordinate Descent (BCD), which are tackled by the triangle inequality, introducing the slack variables and Successive Convex Approximation (SCA). Numerical results show that the proposed algorithm has a desirable convergence, as well as improves effectively the system sum-throughput.
- Unmanned Aerial Vehicle (UAV) communications,
- Intelligent Reflecting Surface (IRS),
- Wireless resource allocation

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References(15)

References

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