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SCIENCE CHINA Information Sciences, Volume 64 , Issue 4 : 140304(2021) https://doi.org/10.1007/s11432-020-3060-4

Resource and trajectory optimization in UAV-powered wireless communication system

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  • ReceivedMar 7, 2020
  • AcceptedSep 24, 2020
  • PublishedMar 5, 2021

Abstract


Acknowledgment

This work was supported in part by National Natural Science Foundation of China (Grant No. 61871348), Project Founded by China Postdoctoral Science Foundation (Grant No. 2019T120531), and Fundamental Research Funds for the Provincial Universities of Zhejiang (Grant No. RFA2019001).


References

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  • Figure 1

    (Color online) System model.

  • Figure 2

    Two cases of time allocation.

  • Figure 3

    (Color online) Trajectory of UAV with symmetric user location.

  • Figure 4

    (Color online) Trajectory of UAV with asymmetric GN location.

  •   

    Algorithm 1 The proposed successive optimization algorithm

    Input: $w_k,~q_i[0],~q_i[N],~T,~P,~V_{\rm~max},~d_{\rm~min}$;

    Initialize: $~q_i[n],~Q_i[n]$;

    Set $\delta_E[n]\ge~\delta_I[n]$;

    Let $\hat{\delta}_E^1[n]=\delta_E[n],~\hat{\delta}_I^1[n]=\delta_I[n],\hat{q}_i^1[n]=q_i[n],~\hat{Q}_i^1[n]=Q_i[n]$;

    Repeat

    Solve problem (P2.2) by using CVX for given $\{\hat{q}_i^1[n],~\hat{Q}_i^1[n]\}$, and denote the obtained time allocation as $\{\delta_E^1[n],\delta_I^1[n]\}$;

    Solve problem (P2.3) by using CVX for given $\{\delta_E^1[n],~\delta_I^1[n],~\hat{Q}_i^1[n]\}$, and denote the obtained UAV trajectory as $~q_i^1[n]$;

    Solve problem (P2.4) by using CVX for given $\{\delta_E^1[n],~\delta_I^1[n],~q_i^1[n]\}$, and denote the obtained power allocation as $Q_i^1[n]$;

    Calculate minimum uplink throughput $R^1$ according to $\{\delta_E^1[n],\delta_I^1[n],q_i^1[n],Q_i^1[n]\}$;

    Update $\hat{\delta}_E^1[n]=\delta_E^1[n],~\hat{\delta}_I^1[n]=\delta_I^1[n],\hat{q}_i^1[n]=q_i^1[n],~\hat{Q}_i^1[n]=Q_i^1[n]$;

    Until the fractional increase of the objective value is below a threshold $\epsilon~>~0~$.

    Set $\delta_E[n]<~\delta_I[n]$

    Let $\hat{\delta}_E^2[n]=\delta_E[n],~\hat{\delta}_I^2[n]=\delta_I[n],\hat{q}_i^2[n]=q_i[n],~\hat{Q}_i^2[n]=Q_i[n]$;

    Repeat

    Solve problem (P3.2) by using CVX for given $\{\hat{q}_i^2[n],~\hat{Q}_i^2[n]\}$, and denote the obtained time allocation as $\{\delta_E^2[n],\delta_I^2[n]\}$;

    Solve problem (P3.3) by using CVX for given $\{\delta_E^2[n],~\delta_I^2[n],~\hat{Q}_i^2[n]\}$, and denote the obtained UAV trajectory as $~q_i^2[n]$;

    Solve problem (P3.4) by using CVX for given $\{\delta_E^2[n],~\delta_I^2[n],~q_i^2[n]\}$, and denote the obtained power allocation as $Q_i^2[n]$;

    Calculate minimum uplink throughput $R^2$ according to $\{\delta_E^2[n],\delta_I^2[n],q_i^2[n],Q_i^2[n]\}$;

    Update $\hat{\delta}_E^2[n]=\delta_E^2[n],~\hat{\delta}_I^2[n]=\delta_I^2[n],\hat{q}_i^2[n]=q_i^2[n],~\hat{Q}_i^2[n]=Q_i^2[n]$

    Until the fractional increase of the objective value is below a threshold $\epsilon~>~0~$.

    If $R^1~\ge~R^2$

    $R=R^1,~\delta_E[n]=\hat{\delta}_E^1[n],~\delta_I[n]=\hat{\delta}_I^1[n],~q_i[n]=\hat{q}_i^1[n],~Q_i[n]=\hat{Q}_i^1[n]$;

    Else

    $R=R^2,~\delta_E[n]=\hat{\delta}_E^2[n],~\delta_I[n]=\hat{\delta}_I^2[n],~q_i[n]=\hat{q}_i^2[n],~Q_i[n]=\hat{Q}_i^2[n]$;

    Output $R,\delta_E[n],~\delta_I[n],~q_i[n],~Q_i[n]$.

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