Common Throughput Maximization in UAV-Enabled OFDMA Systems With Delay Consideration

By Qingqing Wu, Rui Zhang. IEEE Transactions on Communications, 2018

400 citations recorded by the source corpus.

The use of unmanned aerial vehicles (UAVs) as communication platforms is of great significance in future wireless networks, especially for on-demand deployment in temporary events and emergency situations. Although prior works have shown the performance improvement by exploiting the UAV’s mobility, they mainly focus on delay-tolerant applications. As delay requirements fundamentally limit the UAV’s mobility, it remains unknown whether the UAV is able to provide any performance gain in delay-constrained communication scenarios. Motivated by the above, we study, in this paper, an UAV-enabled orthogonal frequency-division multiple access (OFDMA) network where an UAV is dispatched as the mobile base station (BS) to serve a group of users on the ground. We consider a minimum-rate ratio (MRR) for each user, defined as the minimum instantaneous rate required over the average achievable throughput, to flexibly adjust the percentage of its delay-constrained data traffic. Under a given set of constraints on the users’ MRRs, we aim to maximize the minimum average throughput of all users by jointly optimizing the UAV trajectory and OFDMA resource allocation. First, we show that the max–min throughput in general decreases as the users’ MRRs become larger, which reveals a fundamental throughput-delay tradeoff in UAV-enabled communications. Next, we propose an iterative parameter-assisted block coordinate descent method to optimize the UAV trajectory and OFDMA resource allocation alternately, by applying the successive convex optimization and the Lagrange duality, respectively. Furthermore, an efficient and systematic UAV trajectory initialization scheme is proposed based on the simple circular trajectory. Finally, simulation results are provided to verify our theoretical findings and demonstrate the effectiveness of our proposed designs.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6afe0547271a2261f6e503e3fed43d150660b3dc

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Citations in the corpus

UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices (2020, methodology): “In [23], the authors applied SCA and the Lagrange duality to maximize the minimum average rate by optimizing the trajectory of UAV and spectrum allocation.”
Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, background): “In fact, for UAV platforms serving multiple users, there exists a new tradeoff between communication throughput and access delay, which was firstly studied in [101] for a UAV flying with fixed trajectory, and was later extended in [157,158] via joint design of UAV trajectory and communication resour”
3D Trajectory Optimization in Rician Fading for UAV-Enabled Data Harvesting (2019, positive): “Besides UAV-enabled WSNs, UAV trajectory design has been widely investigated in other wireless networks, such as UAV-assisted terrestrial communication [13]–[16], relay systems [17], cellular networks [18], radio access networks [19], and wireless power transfer networks [20].”
Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming (2019, background): “Owing to their high mobility, line-of-sight (LoS) transmission, and low cost, UAVs have been widely used in various scenarios to enhance communication quality via jointly optimizing UAV trajectory and communication resource allocation, including the common throughput, average secrecy rate, and energ”
Trajectory Design and Power Control for Multi-UAV Assisted Wireless Networks: A Machine Learning Approach (2018, methodology): “In [33], a simple circular trajectory was used along with maximizing the minimum average throughput of all users.”
A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, background): “Moreover, non-trivial tradeoffs may exist in leveraging these advantages [20], [24]– [26].”
Throughput Maximization for UAV-Enabled Integrated Periodic Sensing and Communication (2022, methodology): “Also, the complexity of the trajectory discretization-based method will become intractable in practical scenarios with long mission periods [34].”
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (2019, neutral): “Although some existing works have been done to engineer MEC-UAV systems, there are still several challenges to address.”
Optimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems (2018, background): “In fact, according to field measurements, reflection and scattering of the UAV transmit signal occurs in air-to-ground communication links [26], [27] although this is often neglected in the literature [5]–[7], [28]–[30].”
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 [5]–[11].”