Massive MIMO for Communications With Drone Swarms

Chandhar, Prabhu; Danev, Danyo; Larsson, Erik G.

doi:10.1109/twc.2017.2782690

Cited by 140 publications

(89 citation statements)

References 34 publications

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“…In this section we derive a lower-bound for the Rayleigh product channel model (3). A similar analysis can be carried out for multi-tier connections through UAVs, that is, the product channel comprises more than two components.…”

Section: A Lower-bound On Ergodic Capacitymentioning

confidence: 99%

Unmanned Aerial Vehicle Assisted Cellular Communication

Flordelis

Rusek

et al. 2018

2018 IEEE Globecom Workshops (GC Wkshps)

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In this paper, we consider unmanned aerial vehicle (UAV) assisted cellular communications where UAVs are used as amplify-and-forward (AF) relays. The effective channel with UAV-assisted communication is modeled as a Rayleigh product channel, for which we derive a tight lower-bound of the ergodic capacity in closed-form. With the obtained lower-bound, tradeoffs between the transmit power and the equipped number of antennas of the UAVs can be analyzed. Alternatively, for a given setting of users and the base-transceiver station (BTS), the needed transmit power and number of antennas for the UAVs can be derived in order to have a higher ergodic capacity with the UAVassisted communication than that without it.

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Section: A Lower-bound On Ergodic Capacitymentioning

confidence: 99%

Unmanned Aerial Vehicle Assisted Cellular Communication

Flordelis

Rusek

et al. 2018

2018 IEEE Globecom Workshops (GC Wkshps)

View full text Add to dashboard Cite

show abstract

“…This information can be subsequently exploited to facilitate handovers. Ultimately, it is expected that the 3GPP continues its work on the UAV space in the future, possibly through the definition of a new WI focused on 5G-based solutions like massive MIMO [39], [40], [68]- [70].…”

Section: B 3gpp Work Item: Main Outcomes and Way Forwardmentioning

confidence: 99%

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Fotouhi

Qiang

Ding

et al. 2019

IEEE Commun. Surv. Tutorials

858

485

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The rapid growth of consumer Unmanned Aerial Vehicles (UAVs) is creating promising new business opportunities for cellular operators. On the one hand, UAVs can be connected to cellular networks as new types of user equipment, therefore generating significant revenues for the operators that can guarantee their stringent service requirements. On the other hand, UAVs offer the unprecedented opportunity to realize UAVmounted flying base stations that can dynamically reposition themselves to boost coverage, spectral efficiency, and user quality of experience. Indeed, the standardization bodies are currently exploring possibilities for serving commercial UAVs with cellular networks. Industries are beginning to trial early prototypes of flying base stations or user equipments, while academia is in full swing researching mathematical and algorithmic solutions to address interesting new problems arising from flying nodes in cellular networks. In this article, we provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks. Specifically, we survey (i) the types of consumer UAVs currently available off-the-shelf, (ii) the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial base stations, (iii) the challenges and opportunities for assisting cellular communications with UAV-based flying relays and base stations, (iv) the ongoing prototyping and test bed activities, (v) the new regulations being developed to manage the commercial use of UAVs, and (vi) the cyber-physical security of UAV-assisted cellular communications.

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“…Furthermore, an interference-aware path planning design was proposed in [28] for a cellular-enabled multi-UAV communication system, which aimed to achieve a trade-off between energy efficiency, latency, and interference caused by the UAV to the ground network. In [29], [30], massive multiple-input multiple-output (MIMO) was studied as a promising solution to enhance the 3D coverage range and support the simultaneous operation of multiple UAVs, by employing a large size of arrays at the GBSs. Specifically, the uplink capacity of a massive MIMO GBS enabled multi-UAV communication system was derived in [29], based on which the optimal antenna spacing at the GBS was determined.…”

Section: B Literature Reviewmentioning

confidence: 99%

Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective

Zhang

Zeng

Zhang

2019

IEEE Trans. Commun.

368

282

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Integrating the unmanned aerial vehicles (UAVs) into the cellular network is envisioned to be a promising technology to significantly enhance the communication performance of both UAVs and existing terrestrial users. In this paper, we first provide an overview on the two main paradigms in cellular UAV communications, namely, cellular-enabled UAV communication with UAVs as new aerial users served by the ground base stations (GBSs), and UAV-assisted cellular communication with UAVs as new aerial communication platforms serving the terrestrial users. Then, we focus on the former paradigm and study a new UAV trajectory design problem subject to practical communication connectivity constraints with the GBSs. Specifically, we consider a cellular-connected UAV in the mission of flying from an initial location to a final location that are given, during which it needs to maintain reliable communication with the cellular network by associating with one of the available GBSs at each time instant that has the best line-of-sight (LoS) channel (or shortest distance) with it. We aim to minimize the UAV's mission completion time by optimizing its trajectory, subject to a quality-of-connectivity constraint of the GBS-UAV link specified by a minimum receive signal-to-noise ratio (SNR) target, which needs to be satisfied throughout its mission. To tackle this challenging non-convex optimization problem, we first propose an efficient method to verify its feasibility via checking the connectivity between two given vertices on an equivalent graph. Next, by examining the GBS-UAV association sequence over time, we obtain useful structural results on the optimal UAV trajectory, based on which two efficient methods are proposed This work will be presented in part at stations (GBSs). On the other hand, thanks to the continuous improvement in UAV payload weight and communication device miniaturization, it becomes more feasible for UAVs (such as drones, helikites, balloons) to carry communication equipments in the sky, to provide or enhance the communication services for the terrestrial users in the cellular networks (see e.g.[8], [9] for initial trials made by Facebook and Google). Generally speaking, the interplay between UAVs and the cellular network can be fully exploited to improve the communication performance of both UAVs and existing cellular users on the ground, which calls for a new research paradigm to investigate their joint design and performance optimization.In the rest of this section, we first give an overview on the promising technologies for integrating UAVs into the cellular network. Next, we provide a review of related prior work, and discuss a new and critical communication-aware trajectory design problem in cellular-enabled UAV communication, which motivates the main research in this work. Last, we summarize the main results and contributions of this paper for solving this problem. A. UAV Meets Cellular Network: An OverviewAs briefly introduced above, there are two main paradigms for integrating UAVs into the cellular n...

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Massive MIMO for Communications With Drone Swarms

Cited by 140 publications

References 34 publications

Unmanned Aerial Vehicle Assisted Cellular Communication

Unmanned Aerial Vehicle Assisted Cellular Communication

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective

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