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20112025
most citedEfficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage

1.2k citations · 9.5k across the 261 of their papers we have counts for

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Showing 2018Show all

41 papers · 1 filter

eess.SP2018★ 47 cited

Wireless Communications and Control for Swarms of Cellular-Connected UAVs

Tengchan Zeng, Mohammad Mozaffari, Omid Semiari +3

By using wireless connectivity through cellular base stations (BSs), swarms of unmanned aerial vehicles (UAVs) can provide a plethora of services ranging from delivery of goods to…

cs.NI2018★ 448 cited

Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing

Chen-Feng Liu, Mehdi Bennis, Merouane Debbah +1

To overcome devices' limitations in performing computation-intense applications, mobile edge computing (MEC) enables users to offload tasks to proximal MEC servers for faster task…

gr-qc2018★ 47 cited

Hairy black holes, boson stars and non-minimal coupling to curvature invariants

Y. Brihaye, L. Ducobu

The Einstein-Klein-Gordon Lagrangian is supplemented by a non-minimal coupling of the scalar field to specific geometric invariants : the Gauss-Bonnet term and the Chern-Simons ter…

cs.IT2018

Wireless Network Intelligence at the Edge

Jihong Park, Sumudu Samarakoon, Mehdi Bennis +1

Fueled by the availability of more data and computing power, recent breakthroughs in cloud-based machine learning (ML) have transformed every aspect of our lives from face recognit…

cs.NI2018★ 54 cited

Ultra-Reliable Low-Latency Vehicular Networks: Taming the Age of Information Tail

Mohamed K. Abdel-Aziz, Chen-Feng Liu, Sumudu Samarakoon +2

While the notion of age of information (AoI) has recently emerged as an important concept for analyzing ultra-reliable low-latency communications (URLLC), the majority of the exist…

cs.LG2018★ 434 cited

Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Eunjeong Jeong, Seungeun Oh, Hyesung Kim +3

On-device machine learning (ML) enables the training process to exploit a massive amount of user-generated private data samples. To enjoy this benefit, inter-device communication o…