UAV-Assisted Heterogeneous Networks for Capacity Enhancement

By Vishal Sharma, Medhi Bennis, Rajesh Kumar. IEEE Communications Letters, 2016

297 citations recorded by the source corpus.

Modern day wireless networks have tremendously evolved driven by a sharp increase in user demands, continuously requesting more data and services. This puts significant strain on infrastructure-based macro cellular networks due to the inefficiency in handling these traffic demands, cost effectively. A viable solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial nodes between the macro and small cell tiers for improving coverage and boosting capacity. This letter investigates the problem of user-demand-based UAV assignment over geographical areas subject to high traffic demands. A neural-based cost function approach is formulated, in which UAVs are matched to a particular geographical area. It is shown that leveraging multiple UAVs not only provides long-range connectivity but also better load balancing and traffic offload. Simulation study demonstrates that the proposed approach yields significant improvements in terms of fifth percentile spectral efficiency up to 38% and reduced delays up to 37.5% compared with a ground-based network baseline without UAVs.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0ecc815408e86122829388de57ad73c78b0fc48f

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Citations in the corpus

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey (2018, background): “[247] H, Exp several drones communication constraints (eg, signal-to-noise ratio depends on transmission power, distance between source and sink of the transmission and interferences from other transmissions) telecommunications”
UAV Communications for 5G and Beyond: Recent Advances and Future Trends (2019, background): “As a further advance, the problem of user-demand-based UAV assignment in HetNets was investigated in [99], a neuralbased cost function framework was formulated to strike the appropriate user demand areas and UAVs to enhance the network capacity.”
Trajectory Design for Completion Time Minimization in UAV-Enabled Multicasting (2018, background): “In the former case, one typical application is UAV-enabled ubiquitous coverage, where UAVs are deployed to assist the existing ground BSs, if any, to ensure seamless wireless coverage for the GTs within a service area [6], [7].”
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial (2017, methodology): “The authors in [91] studied the use of ANNs for UAV assignment to meet the high traffic demands of ground users.”
A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems (2018, background): “For example, in [133], the authors investigated the optimal user-UAV assignment for capacity enhancement in UAV-assisted heterogeneous wireless networks.”
Securing UAV Communications via Joint Trajectory and Power Control (2018, background): “For example, UAV-mounted BSs can be used to enable rapid wireless communication service recovery after ground infrastructure damages, or provide offloading service for terrestrial BSs in extremely crowded areas [7]– [15].”
Wireless Communication Using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization (2017, background): “The work in [17] investigated the area-to-UAV assignment for capacity enhancement of heterogeneous wireless networks.”
Multi-Tier Drone Architecture for 5G/B5G Cellular Networks: Challenges, Trends, and Prospects (2017, background): “The authors in [7] study the UAV deployment problem focusing on trafﬁc ofﬂoading in a heterogeneous network composed of macro and small cells.”
Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks (2017, methodology): “re has studied a number of problems related to using ANNs for UAVs [91]–[98]. In [91], the authors used a deep RL algorithm to efﬁciently control the coverage and connectivity of UAVs. The authors in [92] studied the use of ANNs for UAV assignment to meet the high trafﬁc demands of ground users. The”
Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network (2018, background): “The work in [16] studied the optimal userUAV association for capacity improvement in UAV-enabled heterogeneous wireless networks.”