CoMP in the Sky: UAV Placement and Movement Optimization for Multi-User Communications

Liang Liu; Rui Zhang; Shuowen Zhang

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CoMP in the Sky: UAV Placement and Movement Optimization for Multi-User Communications

Liang Liu, Shuowen Zhang, Rui Zhang

Information Theory · Submitted 28 Feb 2018

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Interestingly, it is shown that the optimized location of each UAV at any particular episode is the weighted average of the ground user locations at the current episode as well as its own location at the previous and/or next episode.

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arXiv ID1802.10371 (version 1)

Pith IDXHTMFUEB, Pith's permanent record of this paper and its review

CitationLiang Liu, Rui Zhang, Shuowen Zhang. "CoMP in the Sky: UAV Placement and Movement Optimization for Multi-User Communications." arXiv:1802.10371 (2018). https://pith.science/paper/XHTMFUEB

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What the abstract itself states, as probabilities: claims first 0.08 · states limitation 0.14 · human participants 0.02 · controlled comparison 0.17 · randomized assignment 0.02 · states quantitative result 0.36 · compares with prior results 0.38 · mentions code or data availability 0.02.

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arXiv listing abstract v1. Results and the main claim are underlined; show every role.

Driven by the recent advancement in unmanned aerial vehicle (UAV) technology, this paper proposes a new wireless network architecture of \emph{coordinate multipoint (CoMP) in the sky} to harness both the benefits of interference mitigation via CoMP and high mobility of UAVs. Specifically, we consider uplink communications in a multi-UAV enabled multi-user system, where each UAV forwards its received signals from all ground users to a central processor (CP) for joint decoding. Moreover, we consider the case where the users may move on the ground, thus the UAVs need to adjust their locations in accordance with the user locations over time to maximize the network throughput. Utilizing random matrix theory, we first characterize in closed-form a set of approximated upper and lower bounds of the user's achievable rate in each time episode under a realistic line-of-sight (LoS) channel model with random phase, which are shown very tight both analytically and numerically. UAV placement and movement over different episodes are then optimized based on the derived bounds to maximize the minimum of user average achievable rates over all episodes for both cases of full information (of current and future episodes) and current information on the user's movement. Interestingly, it is shown that the optimized location of each UAV at any particular episode is the weighted average of the ground user locations at the current episode as well as its own location at the previous and/or next episode. Finally, simulation results are provided to validate and compare the performance of the proposed UAV placement and movement designs under different practical application scenarios.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Driven by the recent advancement in unmanned aerial vehicle (UAV) technology, this paper proposes a new wireless network architecture of \emph{coordinate multipoint (CoMP) in the sky} to harness both the benefits of interference mitigation via CoMP and high mobility of UAVs.	contribution 0.97	0.74	0.07	asserted 0.98
s1	Specifically, we consider uplink communications in a multi-UAV enabled multi-user system, where each UAV forwards its received signals from all ground users to a central processor (CP) for joint decoding.	method 0.68	0.44	0.03	asserted 0.98
s2	Moreover, we consider the case where the users may move on the ground, thus the UAVs need to adjust their locations in accordance with the user locations over time to maximize the network throughput.	contribution 0.59	0.32	0.03	hedged possibility 0.72
s3	Utilizing random matrix theory, we first characterize in closed-form a set of approximated upper and lower bounds of the user's achievable rate in each time episode under a realistic line-of-sight (LoS) channel model with random phase, which are shown very tight both analytically and numerically.	method 0.49	0.96	0.05	asserted 1.00
s4	UAV placement and movement over different episodes are then optimized based on the derived bounds to maximize the minimum of user average achievable rates over all episodes for both cases of full information (of current and future episodes) and current information on the user's movement.	method 0.80	0.95	0.15	asserted 0.99
s5	Interestingly, it is shown that the optimized location of each UAV at any particular episode is the weighted average of the ground user locations at the current episode as well as its own location at the previous and/or next episode.	result 0.96	0.95	0.41	asserted 1.00
s6	Finally, simulation results are provided to validate and compare the performance of the proposed UAV placement and movement designs under different practical application scenarios.	result 0.41	0.95	0.08	asserted 0.92

What kind of paper the classifier reports this is: method or tool 0.91 · evidence from proof or derivation 0.64.

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arXiv listing abstract v1

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full text
figures and tables
references and citing sentences
relations to other papers

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P abstract

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S sections
T body sentences
C citations
R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper

Original abstract

Driven by the recent advancement in unmanned aerial vehicle (UAV) technology, this paper proposes a new wireless network architecture of \emph{coordinate multipoint (CoMP) in the sky} to harness both the benefits of interference mitigation via CoMP and high mobility of UAVs. Specifically, we consider uplink communications in a multi-UAV enabled multi-user system, where each UAV forwards its received signals from all ground users to a central processor (CP) for joint decoding. Moreover, we consider the case where the users may move on the ground, thus the UAVs need to adjust their locations in accordance with the user locations over time to maximize the network throughput. Utilizing random matrix theory, we first characterize in closed-form a set of approximated upper and lower bounds of the user's achievable rate in each time episode under a realistic line-of-sight (LoS) channel model with random phase, which are shown very tight both analytically and numerically. UAV placement and movement over different episodes are then optimized based on the derived bounds to maximize the minimum of user average achievable rates over all episodes for both cases of full information (of current and future episodes) and current information on the user's movement. Interestingly, it is shown that the optimized location of each UAV at any particular episode is the weighted average of the ground user locations at the current episode as well as its own location at the previous and/or next episode. Finally, simulation results are provided to validate and compare the performance of the proposed UAV placement and movement designs under different practical application scenarios.

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13 arXiv papers cite this in 24 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 15 sentences without a confident label

Cites it as background 7 papers

For instance, the 3D placement of multiple UAVs [ref] , the interference elimination [ref] , energy efficiency optimization [ref] , trajectory/movement design [ref] , air-ground channel modeling [ref] , antenna design [ref] , power/bandwidth allocation [ref] and the compatibility between aerial wireless networks and the existing cellular networks.

Reinforcement Learning in Multiple-UAV Networks: Deployment and Movement Design · Related Works · 0.87
Besides the works considering single UAV only, references [ref] studied more complicated scenarios with multiple UAVs.

Multi-UAV Interference Coordination via Joint Trajectory and Power Control · Related Work · 0.96
A related problem is to optimize the UAV trajectories subject to speed constraints [ref] .

Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach · Introduction · 0.94

What it cites · 3 sentences without a confident label

Cites as background 1 paper

On the other hand, unmanned aerial vehicles (UAVs) have recently found wide applications in wireless communication systems for coverage extension [ref] and capacity enhancement [ref] , driven by the pioneering efforts of Google (Project Loon) and Facebook (Project Aquila).

Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks · Introduction · 0.82

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