Energy-efficient communication in mobile aerial relay-assisted networks using predictive control

Faqir, Omar J.; Nie, Yuanbo; Kerrigan, Eric C.; Gündüz, Deniz

doi:10.1016/j.ifacol.2018.11.013

Cited by 12 publications

(15 citation statements)

References 11 publications

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“…2 shows the set {(P, v) | D ∞,1 = M} of admissible powers and velocities that successfully transmit M bits of data. (P, v) may then be chosen from this set to achieve alternative operating points, such as energy efficiency [1]. Since many transmitters operate at a single, or finite set of power levels, v may often be found as an explicit function of (P, M).…”

Section: Characterization For General α In 1dmentioning

confidence: 99%

“…2: D ∞,1 as a function of speed v and transmit power P in the 1D case (z 0 = 0) for parameters from Table I. 1 For the sake of relatability all data is plotted in MB, not nats.…”

Section: Characterization For General α In 1dmentioning

confidence: 99%

“…We consider dynamic deployment scenarios (e.g. [1]- [4]) where UAVs, spacecraft, or other agents are transmitting while moving, and are interested in characterising the total data transfer as a function of mobility dynamics and design parameters, such as transmit power. We do not consider transmitter power control as a function of distance as this is challenging to implement in practice, especially at higher speeds.…”

Section: Introductionmentioning

confidence: 99%

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Information Transmission Bounds Between Moving Terminals

2020

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In networks of mobile autonomous agents, e.g. for data acquisition, we may wish to maximize data transfer or to reliably transfer a minimum amount of data, subject to quality of service or energy constraints. These requirements can be guaranteed through both offline node design/specifications and online trajectory/communications design. Regardless of the distance between them, for a stationary point-to-point transmitter-receiver pair communicating across a single link under average power constraints, the total data transfer is unbounded as time tends to infinity. In contrast, we show that if the transmitter/receiver is moving at any constant speed away from each other, then the maximum transmittable data is bounded. Although general closed-form expressions as a function of communication and mobility profile parameters do not yet exist, we provide closed-form expressions for particular cases, such as ideal free space path loss. Under more general scenarios we instead give lower bounds on the total transmittable information across a single link between mobile nodes.

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Section: Characterization For General α In 1dmentioning

confidence: 99%

“…2: D ∞,1 as a function of speed v and transmit power P in the 1D case (z 0 = 0) for parameters from Table I. 1 For the sake of relatability all data is plotted in MB, not nats.…”

Section: Characterization For General α In 1dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Information Transmission Bounds Between Moving Terminals

2020

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“…The current literature on UAV-assisted wireless communications can be split into two categories according to the dynamics of UAVs during the data transmission. The static frameworks assume that the geometric locations of all the network nodes (involving UAVs) remain unchanged during the data transmission [7], [8], while the dynamic scenarios assume that UAVs can be mobile in any phase of the data transmission [9]- [12]. In [7], the optimal deployment of a static UAV is considered to improve the average data rate between two obstructed access points under a symbol error rate constraint.…”

Section: Introductionmentioning

confidence: 99%

Interference Avoidance in UAV-Assisted Networks: Joint 3D Trajectory Design and Power Allocation

Rahmati

Hosseinalipour

Yapıcı

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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The use of the unmanned aerial vehicle (UAV) has been foreseen as a promising technology for the next generation communication networks. Since there are no regulations for UAVs deployment yet, most likely they form a network in coexistence with an already existed network. In this work, we consider a transmission mechanism that aims to improve the data rate between a terrestrial base station (BS) and user equipment (UE) through deploying multiple UAVs relaying the desired data flow. Considering the coexistence of this network with other established communication networks, we take into account the effect of interference, which is incurred by the existing nodes. Our primary goal is to optimize the three-dimensional (3D) trajectories and power allocation for the relaying UAVs to maximize the data flow while keeping the interference to existing nodes below a predefined threshold. An alternating-maximization strategy is proposed to solve the joint 3D trajectory design and power allocation for the relaying UAVs. To this end, we handle the information exchange within the network by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. Simulation results show that our approach can considerably improve the information flow while the interference threshold constraint is met.

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“…between a set of sensors and a ground node or as a relay node between a pair of transmitter and receiver, is developed [11]- [21]. In [11], the optimal position of a set of UAV relays is studied to improve the network connectivity and communication performance of a team of ground nodes/vehicles, where there is no communications among the UAVs themselves.…”

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confidence: 99%

Interference Avoidance Position Planning in Dual-hop and Multi-hop UAV Relay Networks

Hosseinalipour,

Rahmati,

Dai

2019

Preprint

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We consider unmanned aerial vehicle (UAV)-assisted wireless communication employing UAVs as relay nodes to increase the throughput between a pair of transmitter and receiver. We focus on developing effective methods to position the UAV(s) in the sky in the presence of interference in the environment, the existence of which makes the problem non-trivial and our methodology different from the current art. We study the optimal position planning, which aims to maximize the (average) SIR of the system, in the presence of: i) one major source of interference, ii) stochastic interference. For each scenario, we first consider utilizing a single UAV in the dual-hop relay mode and determine its optimal position. Afterward, multiple UAVs in the multihop relay mode are considered, for which we investigate two novel problems concerned with determining the optimal number of required UAVs and developing an optimal fully distributed position alignment method. Subsequently, we propose a costeffective method that simultaneously minimizes the number of UAVs and determines their optimal positions so as to guarantee a certain (average) SIR of the system. Alternatively, for a given number of UAVs, we develop a fully distributed placement algorithm along with its performance guarantee. Numerical simulations are provided to evaluate the performance of our proposed methods.

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Energy-efficient communication in mobile aerial relay-assisted networks using predictive control

Cited by 12 publications

References 11 publications

Information Transmission Bounds Between Moving Terminals

Information Transmission Bounds Between Moving Terminals

Interference Avoidance in UAV-Assisted Networks: Joint 3D Trajectory Design and Power Allocation

Interference Avoidance Position Planning in Dual-hop and Multi-hop UAV Relay Networks

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