Flying Rebots: First Results on an Autonomous UAV-Based LTE Relay Using Open Airinterface

Gangula, Rajeev; Esrafilian, Omid; Gesbert, David; Roux, Cedric; Kaltenberger, Florian; Knopp, Raymond

doi:10.1109/spawc.2018.8445947

Cited by 36 publications

(26 citation statements)

References 15 publications

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“…They have been widely used for cellular coverage extension, wireless backhaul, and emergency response, etc. A few experiments have been conducted to validate the superiorities of UAVenabled aerial relay [88][89][90].…”

Section: Uav-enabled Aerial Relaymentioning

confidence: 99%

A survey of prototype and experiment for UAV communications

Song

Zeng

et al. 2021

Sci. China Inf. Sci.

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Unmanned aerial vehicle (UAV) communications have attracted significant attention from both academia and industry. To facilitate the large-scale usage of UAVs for various applications in practice, we provide a comprehensive survey on the prototype and experiment for UAV communications. To this end, we first provide an overview on the general architecture of the prototype and experiment for UAV communications, and then present experimental verification for air-to-ground channel models and UAV energy consumption models. Next, we discuss measurement experiments on two promising paradigms of UAV communications, namely cellular-connected UAVs and UAV-enabled aerial communication platforms. For the former, we focus on the feasibility study and address the interference mitigation issue. For UAV-enabled aerial communication platforms, we present three scenarios, namely UAV-enabled aerial base stations, UAVenabled aerial relays and UAV-enabled aerial data collection/dissemination. Finally, we point out some promising future directions for prototype and experimental measurements of UAV communications.

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Section: Uav-enabled Aerial Relaymentioning

confidence: 99%

A survey of prototype and experiment for UAV communications

Song

Zeng

et al. 2021

Sci. China Inf. Sci.

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“…Lime Microsystems demonstrate a 3G call for a drone-mounted lightweight base station with a weight less than 2 kg [23]. In [12], the results of a UAV relaying a user using an existing long term evolution (LTE) network are presented. The increase in user throughput when the flying relay is in operation is shown.…”

Section: Uav Serving Ground Usersmentioning

confidence: 99%

“…We proposed a general architecture for UAV-aided networks as illustrated in Figure 1. It is based on the architectures described in [7,10,12,15,21]. The access network, indicated in orange, uses the 2.6 GHz frequency and connects the users to the UABSs through 3G LTE femtocell base station technology.…”

Section: The Architecture Of Backhaul For Uabs In Emergency Networkmentioning

confidence: 99%

“…These challenges could be divided into two groups related to (i) the access network where the UABSs provide a connection to the users and (ii) the backhaul link between the UABSs and the core network (CN). Although several studies have addressed the access network [10,11,12,13,14,15] as will be discussed in Section 2, limited work has been done on the backhauling.…”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks

Castellanos

Deruyck

Martens

et al. 2019

Sensors

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Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users—access network—and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul networks; however, full coverage was difficult to achieve. Finally, we discuss the influence of the flight height and the number of requesting users concerning the network performance and propose an optimal configuration and new mechanisms to improve the network capacity, based on realistic restrictions.

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“…However, the focus in [12]- [14] is on the airborne to terrestrial coverage problems. Trajectory optimization to maximize data rate from specific ground nodes is considered in [15], [16]. The coexistence of UAV communication system arXiv:1810.08035v2 [cs.NI] 31 May 2019 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2 with current systems is discussed in [17], [18].…”

Section: Introductionmentioning

confidence: 99%

Aeronautical Data Aggregation and Field Estimation in IoT Networks: Hovering and Traveling Time Dilemma of UAVs

Bushnaq

Çelik

ElSawy

et al. 2019

IEEE Trans. Wireless Commun.

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The next era of information revolution will rely on aggregating big data from massive numbers of devices that are widely scattered in our environment. Most of these devices are expected to be of low-complexity, low-cost, and limited power supply, which impose stringent constraints on the network operation. In this regard, this paper investigates aerial data aggregation and field estimation from a finite spatial field via an unmanned aerial vehicle (UAV). Instead of fusing, relaying, and routing the data across the wireless nodes to fixed locations access points, a UAV flies over the field and collects the required data for two prominent missions; data aggregation and field estimation. To accomplish these tasks, the field of interest is divided into several subregions over which the UAV hovers to collect samples from the underlying nodes. To this end, we formulate and solve an optimization problem to minimize total hovering and traveling time of each mission. While the former requires the collection of a prescribed average number of samples from the field, the latter ensures for a given field spatial correlation model that the average mean-squared estimation error of the field value is no more than a predetermined threshold at any point. These goals are fulfilled by optimizing the number of subregions, the area of each subregion, the hovering locations, the hovering time at each location, and the trajectory traversed between hovering locations. The proposed formulation is shown to be NP-hard mixed integer problem, and hence, a decoupled heuristic solution is proposed. The results show that there exists an optimal number of subregions that balance the tradeoff between hovering and traveling times such that the total time for collecting the required samples is minimized.

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Flying Rebots: First Results on an Autonomous UAV-Based LTE Relay Using Open Airinterface

Cited by 36 publications

References 15 publications

A survey of prototype and experiment for UAV communications

A survey of prototype and experiment for UAV communications

Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks

Aeronautical Data Aggregation and Field Estimation in IoT Networks: Hovering and Traveling Time Dilemma of UAVs

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