Application-driven design of aerial communication networks

Andre, Torsten; Hummel, Karin Anna; Schoellig, Angela P.; Yanmaz, Evşen; Asadpour, Mahdi; Bettstetter, Christian; Grippa, Pasquale; Hellwagner, Hermann; Sand, Stephan; Zhang, Siwei

doi:10.1109/mcom.2014.6815903

Cited by 133 publications

(88 citation statements)

References 13 publications

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“…In the next few years a large number of UAVs will coexist which would require a high-throughput network for communication [1], [2]. However, the communication between the ground station (GS) and the UAVs involves many challenges.…”

Section: Introductionmentioning

confidence: 99%

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Massive MIMO as enabler for communications with drone swarms

Chandhar

Danev

Larsson

2016

2016 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Specifically, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV networks.

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Section: Introductionmentioning

confidence: 99%

“…20-30 small UAVs transmitting high-resolution videos to the GS). The list of such civilian and military applications for UAVs keeps growing [2], [5]- [7]. Therefore, a new breakthrough technology is required in order to support the multitude of applications of UAVs that need high throughput, low power consumption, and low latency.…”

Section: Introductionmentioning

confidence: 99%

Massive MIMO as enabler for communications with drone swarms

Chandhar

Danev

Larsson

2016

2016 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…Five key functionalities, namely commanding, surveying, swarming, collecting, and relaying that have proven to be fundamental to a wide range of civilian multi-UAV applications are identified [62]. Out of these five key functionalities, four key building blocks with communication requirements are identified.…”

Section: Unmanned Aerial Systems (Uas)mentioning

confidence: 99%

Cognitive Radio for Aeronautical Communications: A Survey

et al. 2016

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Novel Air Traffic Management (ATM) strategies are proposed through the Next Generation Air Transportation (NextGen) and Single European Sky for ATM Research (SESAR) projects to improve the capacity of the airspace and to meet the demands of the future air traffic. The implementation of the proposed solutions leads to increasing use of wireless data for aeronautical communications. Another emerging trend is the unmanned aerial vehicles. The unmanned aerial systems (UASs) need reliable wireless data link and dedicated spectrum allocation for its operation. On-board broadband connectivity also needs dedicated spectrum to satisfy the quality of service (QoS) requirements of the users. With the growing demand, the aeronautical spectrum is expected to be congested. However, the studies revealed that the aeronautical spectrum is underutilized due to the static spectrum allocation strategy. The aeronautical communication systems such as air-air and airground communication systems, inflight infotainment systems, wireless avionics intra-communications (WAIC), and UAS can benefit significantly from the introduction of cognitive radio based transmission schemes. This article summarizes the current trends in aeronautical spectrum management followed by the major applications and contributions of cognitive radio in solving the spectrum scarcity crisis in the aeronautical domain. Also, to cope with the evolving technological advancement, researchers have prioritized the issues in the case of cognitive radio that needs to be addressed depending on the domain of operation. The proposed cognitive aeronautical communication systems should also be compliant with the Aeronautical Radio Incorporated (AR-INC) and Aerospace Recommended Practice (ARP) standards. An overview of these standards and the challenges that need immediate attention to make the solution feasible for a largescale operation, along with the future avenues of research is also furnished.

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“…They fly routes in an autonomous manner, carry cameras for aerial photography, and transport goods from one place to another. The range of applications is broad, including aerial monitoring of plants and agricultural fields as well as support for first time responders in case of disasters (Andre et al 2014;Kovacina et al 2002;Lima et al 2014;Quaritsch et al 2008). Delivering goods with a fleet of drones (Grippa 2016;Grippa et al 2017) becomes an option if classical means of transportation-such as trucks, trains, and planes-are inappropriate.…”

Section: Introductionmentioning

confidence: 99%

Drone delivery systems: job assignment and dimensioning

et al. 2018

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This article studies how to dimension and control at the system level a fleet of autonomous aerial vehicles delivering goods from depots to customers. Customer requests (jobs) arrive according to a space-time stochastic process. We compute a lower bound for the infrastructure expenditure required to achieve a certain expected delivery time. It is shown that job assignment policies can exhibit a tipping point behavior: One vehicle makes the difference between almost optimal delivery time and instability. This phenomenon calls for careful dimensioning of the system. We thus demonstrate the trade-off between financial costs and service quality. We propose a policy that assigns each incoming job to the vehicle that will do the job faster than other ones, seeking to minimize the overall workload in the system in the long term. This policy is scalable with the number of depots and vehicles, performs optimal in low load, and works well up to high loads. Simulations suggest that it stabilizes the system for any load if the number of vehicles per depot is sufficient.

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Application-driven design of aerial communication networks

Cited by 133 publications

References 13 publications

Massive MIMO as enabler for communications with drone swarms

Massive MIMO as enabler for communications with drone swarms

Cognitive Radio for Aeronautical Communications: A Survey

Drone delivery systems: job assignment and dimensioning

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