4.8 Article

Dynamic Resource Allocation in UAV-Enabled mmWave Communication Networks

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 12, Pages 9920-9933

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3027476

Keywords

Antenna arrays; Interference; Resource management; Wireless communication; Downlink; Unmanned aerial vehicles; Internet of Things; Millimeter wave (mmWave); nonconvex optimization; resource allocation; subcarrier (SC) assignment; unmanned aerial vehicle (UAV)

Funding

  1. Department of Science and Technology [INT/Korea/P-46]
  2. Department of Telecommunication [4-23/5G-test-bed/2017-NT]

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The study proposes a sectoring approach for area coverage using UAV-enabled cellular architecture in the mmWave frequency band, taking into account the antenna array sidelobe gain and formulating a resource allocation problem to maximize sum rate while ensuring minimum rate guarantee.
Unmanned aerial vehicle (UAV)-enabled cellular architecture over the millimeter-wave (mmWave) frequency band is likely to be the best solution for on-demand high data rate service provisioning in the next generation communication networks. The beam formed by the mmWave antenna array is highly directional and requires multiple-beam scans to cover the entire area. This work presents a novel sectoring approach to ensure coverage of the whole area. The side lobe gain of the antenna array is taken into consideration, which generates substantial interference in other sectors. The expression for the probability distribution of the signal-to-interference-plus-noise ratio due to simultaneous transmissions in different sectors is derived in the downlink communication scenario. To limit interference in the concurrent transmission strategy, a threshold on power spillage from adjacent sectors is placed. For this topology, a resource allocation problem is formulated aiming to maximize the sum rate while ensuring a minimum rate guarantee to each user. It is observed that sum-rate variation with height is unimodal. The sum power and backhaul capacity constraints are accounted. This optimization problem is mixed-integer nonconvex programming. Hence, it is solved using the Lagrangian dual decomposition method, which provides an asymptotic global optimal solution. Since this method is computationally intensive, a suboptimal solution is proposed. Simulation results demonstrate convergence to an optimal solution, and it is observed that backhaul link capacity restricts the sum rate. Numerical results are presented for multiple representative field environments consisting of different types of built-up areas. It is observed that the transmitter antenna array sidelobe has a strong impact on the performance as compared to the ideal scenario without sidelobe, which overestimates the total sum rate by a factor of 3.

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