The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam makalah ini, komunikasi koperasi teragih bagi kenderaan udara tanpa pemandu (UAV) dikaji, di mana nombor keadaan (CN) dan produk dalam (InP) digunakan untuk mengukur kualiti pautan komunikasi. Dengan mengoptimumkan kedudukan relatif UAV, kapasiti saluran yang besar dan pautan komunikasi yang stabil boleh diperolehi. Menggunakan model gelombang sfera di bawah saluran garis penglihatan (LOS), ungkapan CN matriks saluran diperoleh apabila terdapat Nt pemancar dan dua penerima dalam sistem. Untuk memaksimumkan kapasiti saluran, kami memperoleh persamaan kekangan kedudukan UAV (UAV-PCE), dan kekangan antara jarak elemen BS dan panjang gelombang pembawa dianalisis. Hasilnya menunjukkan terdapat kawasan di mana tidak kira bagaimana kedudukan UAV dilaraskan, CN masih sangat besar. Kemudian senario khas dipertimbangkan di mana UAV membentuk tatasusunan kekisi segi empat tepat, dan kekangan optimum antara jarak komunikasi dan jarak UAV diperolehi. Selepas itu, kami memperoleh InP matriks saluran dan ekspresi kecerunan InP berkenaan dengan kedudukan UAV. Algoritma pengoptimuman kawanan zarah (PSO) digunakan untuk meminimumkan CN dan algoritma keturunan kecerunan (GD) digunakan untuk meminimumkan InP dengan mengoptimumkan kedudukan UAV secara berulang. Kedua-dua algoritma ini memberikan potensi besar untuk mengoptimumkan CN dan InP masing-masing. Tambahan pula, algoritma hibrid bernama PSO-GD yang menggabungkan kelebihan kedua-dua algoritma dicadangkan untuk memaksimumkan kapasiti komunikasi dengan kerumitan yang lebih rendah. Simulasi menunjukkan bahawa PSO-GD lebih cekap daripada PSO dan GD. PSO membantu GD untuk melepaskan diri daripada ekstrem tempatan dan menyediakan kedudukan yang lebih baik untuk GD, dan GD boleh menumpu kepada penyelesaian optimum dengan cepat dengan menggunakan maklumat kecerunan berdasarkan kedudukan yang lebih baik. Simulasi juga mendedahkan bahawa saluran yang lebih baik boleh diperolehi apabila parameter tersebut memenuhi persamaan kekangan kedudukan UAV (UAV-PCE), sementara itu, analisis teori juga menerangkan fenomena abnormal dalam simulasi.
Zhaoyang HOU
Xidian University
Zheng XIANG
Xidian University
Peng REN
Xidian University
Qiang HE
Xidian University
Ling ZHENG
Xi'an University of Post and Telecommunications
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Salinan
Zhaoyang HOU, Zheng XIANG, Peng REN, Qiang HE, Ling ZHENG, "Distributed UAVs Placement Optimization for Cooperative Communication" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 6, pp. 675-685, June 2021, doi: 10.1587/transcom.2020EBP3117.
Abstract: In this paper, the distributed cooperative communication of unmanned aerial vehicles (UAVs) is studied, where the condition number (CN) and the inner product (InP) are used to measure the quality of communication links. By optimizing the relative position of UAVs, large channel capacity and stable communication links can be obtained. Using the spherical wave model under the line of sight (LOS) channel, CN expression of the channel matrix is derived when there are Nt transmitters and two receivers in the system. In order to maximize channel capacity, we derive the UAVs position constraint equation (UAVs-PCE), and the constraint between BS elements distance and carrier wavelength is analyzed. The result shows there is an area where no matter how the UAVs' positions are adjusted, the CN is still very large. Then a special scenario is considered where UAVs form a rectangular lattice array, and the optimal constraint between communication distance and UAVs distance is derived. After that, we derive the InP of channel matrix and the gradient expression of InP with respect to UAVs' position. The particle swarm optimization (PSO) algorithm is used to minimize the CN and the gradient descent (GD) algorithm is used to minimize the InP by optimizing UAVs' position iteratively. Both of the two algorithms present great potentials for optimizing the CN and InP respectively. Furthermore, a hybrid algorithm named PSO-GD combining the advantage of the two algorithms is proposed to maximize the communication capacity with lower complexity. Simulations show that PSO-GD is more efficient than PSO and GD. PSO helps GD to break away from local extremum and provides better positions for GD, and GD can converge to an optimal solution quickly by using the gradient information based on the better positions. Simulations also reveal that a better channel can be obtained when those parameters satisfy the UAVs position constraint equation (UAVs-PCE), meanwhile, theory analysis also explains the abnormal phenomena in simulations.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3117/_p
Salinan
@ARTICLE{e104-b_6_675,
author={Zhaoyang HOU, Zheng XIANG, Peng REN, Qiang HE, Ling ZHENG, },
journal={IEICE TRANSACTIONS on Communications},
title={Distributed UAVs Placement Optimization for Cooperative Communication},
year={2021},
volume={E104-B},
number={6},
pages={675-685},
abstract={In this paper, the distributed cooperative communication of unmanned aerial vehicles (UAVs) is studied, where the condition number (CN) and the inner product (InP) are used to measure the quality of communication links. By optimizing the relative position of UAVs, large channel capacity and stable communication links can be obtained. Using the spherical wave model under the line of sight (LOS) channel, CN expression of the channel matrix is derived when there are Nt transmitters and two receivers in the system. In order to maximize channel capacity, we derive the UAVs position constraint equation (UAVs-PCE), and the constraint between BS elements distance and carrier wavelength is analyzed. The result shows there is an area where no matter how the UAVs' positions are adjusted, the CN is still very large. Then a special scenario is considered where UAVs form a rectangular lattice array, and the optimal constraint between communication distance and UAVs distance is derived. After that, we derive the InP of channel matrix and the gradient expression of InP with respect to UAVs' position. The particle swarm optimization (PSO) algorithm is used to minimize the CN and the gradient descent (GD) algorithm is used to minimize the InP by optimizing UAVs' position iteratively. Both of the two algorithms present great potentials for optimizing the CN and InP respectively. Furthermore, a hybrid algorithm named PSO-GD combining the advantage of the two algorithms is proposed to maximize the communication capacity with lower complexity. Simulations show that PSO-GD is more efficient than PSO and GD. PSO helps GD to break away from local extremum and provides better positions for GD, and GD can converge to an optimal solution quickly by using the gradient information based on the better positions. Simulations also reveal that a better channel can be obtained when those parameters satisfy the UAVs position constraint equation (UAVs-PCE), meanwhile, theory analysis also explains the abnormal phenomena in simulations.},
keywords={},
doi={10.1587/transcom.2020EBP3117},
ISSN={1745-1345},
month={June},}
Salinan
TY - JOUR
TI - Distributed UAVs Placement Optimization for Cooperative Communication
T2 - IEICE TRANSACTIONS on Communications
SP - 675
EP - 685
AU - Zhaoyang HOU
AU - Zheng XIANG
AU - Peng REN
AU - Qiang HE
AU - Ling ZHENG
PY - 2021
DO - 10.1587/transcom.2020EBP3117
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2021
AB - In this paper, the distributed cooperative communication of unmanned aerial vehicles (UAVs) is studied, where the condition number (CN) and the inner product (InP) are used to measure the quality of communication links. By optimizing the relative position of UAVs, large channel capacity and stable communication links can be obtained. Using the spherical wave model under the line of sight (LOS) channel, CN expression of the channel matrix is derived when there are Nt transmitters and two receivers in the system. In order to maximize channel capacity, we derive the UAVs position constraint equation (UAVs-PCE), and the constraint between BS elements distance and carrier wavelength is analyzed. The result shows there is an area where no matter how the UAVs' positions are adjusted, the CN is still very large. Then a special scenario is considered where UAVs form a rectangular lattice array, and the optimal constraint between communication distance and UAVs distance is derived. After that, we derive the InP of channel matrix and the gradient expression of InP with respect to UAVs' position. The particle swarm optimization (PSO) algorithm is used to minimize the CN and the gradient descent (GD) algorithm is used to minimize the InP by optimizing UAVs' position iteratively. Both of the two algorithms present great potentials for optimizing the CN and InP respectively. Furthermore, a hybrid algorithm named PSO-GD combining the advantage of the two algorithms is proposed to maximize the communication capacity with lower complexity. Simulations show that PSO-GD is more efficient than PSO and GD. PSO helps GD to break away from local extremum and provides better positions for GD, and GD can converge to an optimal solution quickly by using the gradient information based on the better positions. Simulations also reveal that a better channel can be obtained when those parameters satisfy the UAVs position constraint equation (UAVs-PCE), meanwhile, theory analysis also explains the abnormal phenomena in simulations.
ER -