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Analysis of Multi-User-Based UAV System With Outdated CSI

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submitted on 2025-07-02, 11:03 and posted on 2025-07-02, 11:05 authored by Parvez Shaik, Cihat Keçeci, Kamal K. Garg, Muhammad Ismail, Erchin Serpedin
<p dir="ltr">In this paper, we investigate the performance of multiple-input and multiple-output (MIMO) unmanned air vehicle (UAV) based multi-user communication systems over generalized Nakagami- m fading channels subject to channel feedback delays. The impact of decode-and-forward (DF) based relaying and outdated channel state information is assessed at the receiver nodes. To reduce the complexity and retain the MIMO gains, the transmit antenna selection (TAS) strategy is used to select the best antenna at the source and UAV nodes. A generic framework in the form of closed-form analytical expressions for outage probability (OP), asymptotic OP, and the average symbol error rate of higher-order quadrature amplitude modulation (QAM) schemes such as hexagonal QAM, rectangular QAM, and cross QAM are derived. In addition, energy efficiency analysis is also performed for the considered system model. In this framework, altitude and location-dependent path loss modeling are considered for the air-to-ground links. Optimization of UAV location and altitude is performed through a limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm to attain minimum OP (MOP). Results illustrate optimal performance dependent on the channel correlation parameters, antenna elements, and fading conditions. Monte-Carlo simulations are performed to validate the derived analytical results and compared with the existing works.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Open Journal of the Communications Society<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/ojcoms.2023.3347388" target="_blank">https://dx.doi.org/10.1109/ojcoms.2023.3347388</a></p>

Funding

Open Access funding provided by the Qatar National Library.

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Language

  • English

Publisher

IEEE

Publication Year

  • 2024

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Texas A&M University at Qatar