<p>The multi-UAV relay system can rapidly deploy a temporary communication network in disaster emergency communication scenarios to enhance communication coverage and stability in the affected area and ensure the efficient transmission of rescue information. Aiming at the problems of insufficient real-time performance, low user fairness, and low utilization of communication resources in multi-UAV relay systems, this paper proposes a joint optimization method of communication rate based on Lexicographic Optimization (LO). The multi-UAV relay scenario using multi-carrier non-orthogonal multiple access (MC-NOMA) technology is modeled as a multi-objective optimization problem and solved in stages using the LO method. Specifically, the first stage maximizes the minimum user communication rate by jointly optimizing the user association, relay UAV transmit power and flight trajectory; the second stage optimizes the modulation order of the relay UAVs to maximize the communication rate between UAV base stations. Finally, the proposed algorithm is compared under different optimization schemes and different optimization algorithms. The simulation results show that the user communication rate of the proposed algorithm is <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40747_2025_1910_Article_IEq1.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="107" /> </InlineMediaObject> <EquationSource Format="TEX">$6.8\times {10}^5bps/s$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>6.8</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mn>5</mn> </msup> <mi>b</mi> <mi>p</mi> <mi>s</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation> higher than that of the static user association scheme, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40747_2025_1910_Article_IEq2.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="107" /> </InlineMediaObject> <EquationSource Format="TEX">$6.7\times {10}^6bps/s$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>6.7</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mn>6</mn> </msup> <mi>b</mi> <mi>p</mi> <mi>s</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation> higher than that of the static UAV trajectory scheme, and <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40747_2025_1910_Article_IEq3.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="107" /> </InlineMediaObject> <EquationSource Format="TEX">$2.0\times {10}^5bps/s$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>2.0</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mn>5</mn> </msup> <mi>b</mi> <mi>p</mi> <mi>s</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation> higher than that of the traditional Jara algorithm, and <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40747_2025_1910_Article_IEq2.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="107" /> </InlineMediaObject> <EquationSource Format="TEX">$6.7\times {10}^6bps/s$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>6.7</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mn>6</mn> </msup> <mi>b</mi> <mi>p</mi> <mi>s</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation> higher than that of the K-mean based optimization algorithm. Moreover, this algorithm performs well in convergence and stability, effectively improves the user communication rate, the communication rate between UAV base stations, and the energy utilization of relay UAV, and enhances the adaptability of the system to the dynamic environment.</p>

Joint optimization of communication rates for multi-UAV relay systems

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2025年5月13日

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Chenghua Wen,
Guifen Chen,
Xinglong Gu,
Wenzhe Wang

摘要

The multi-UAV relay system can rapidly deploy a temporary communication network in disaster emergency communication scenarios to enhance communication coverage and stability in the affected area and ensure the efficient transmission of rescue information. Aiming at the problems of insufficient real-time performance, low user fairness, and low utilization of communication resources in multi-UAV relay systems, this paper proposes a joint optimization method of communication rate based on Lexicographic Optimization (LO). The multi-UAV relay scenario using multi-carrier non-orthogonal multiple access (MC-NOMA) technology is modeled as a multi-objective optimization problem and solved in stages using the LO method. Specifically, the first stage maximizes the minimum user communication rate by jointly optimizing the user association, relay UAV transmit power and flight trajectory; the second stage optimizes the modulation order of the relay UAVs to maximize the communication rate between UAV base stations. Finally, the proposed algorithm is compared under different optimization schemes and different optimization algorithms. The simulation results show that the user communication rate of the proposed algorithm is $6.8\times {10}^5bps/s$ $6.8 \times 10^{5} b p s / s$ higher than that of the static user association scheme, $6.7\times {10}^6bps/s$ $6.7 \times 10^{6} b p s / s$ higher than that of the static UAV trajectory scheme, and $2.0\times {10}^5bps/s$ $2.0 \times 10^{5} b p s / s$ higher than that of the traditional Jara algorithm, and $6.7\times {10}^6bps/s$ $6.7 \times 10^{6} b p s / s$ higher than that of the K-mean based optimization algorithm. Moreover, this algorithm performs well in convergence and stability, effectively improves the user communication rate, the communication rate between UAV base stations, and the energy utilization of relay UAV, and enhances the adaptability of the system to the dynamic environment.