We study downlink transmission in a multi-band heterogeneous network comprising unmanned aerial vehicle (UAV) small base stations and ground-based dual mode mmWave small cells within the coverage area of a microwave (μW) macro base station. We formulate a two-layer optimization framework to simultaneously find efficient coverage radius for the UAVs and energy efficient radio resource management for the network, subject to minimum quality-of-service (QoS) and maximum transmission power constraints. The outer layer derives an optimal coverage radius/height for each UAV as a function of the maximum allowed path loss. The inner layer formulates an optimization problem to maximize the system energy efficiency (EE), defined as the ratio between the aggregate user data rate delivered by the system and its aggregate energy consumption (downlink transmission and circuit power). We demonstrate that at certain values of the target SINR τ introducing the UAV base stations doubles the EE. We also show that an increase in τ beyond an optimal EE point decreases the EE.
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This content will become publicly available on October 1, 2024
Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction
In this paper, we delve into the domain of heterogeneous drone-enabled aerial base stations, each equipped with varying transmit powers, serving as downlink wireless providers for ground users. A central challenge lies in strategically selecting and deploying a subset from the available drone base stations (DBSs) to meet the downlink data rate requirements while minimizing the overall power consumption. To tackle this, we formulate an optimization problem to identify the optimal subset of DBSs, ensuring wireless coverage with an acceptable transmission rate in the downlink path. Moreover, we determine their 3D positions for power consumption optimization. Assuming DBSs operate within the same frequency band, we introduce an innovative, computationally efficient beamforming method to mitigate intercell interference in the downlink. We propose a Kalai–Smorodinsky bargaining solution to establish the optimal beamforming strategy, compensating for interference-related impairments. Our simulation results underscore the efficacy of our solution and offer valuable insights into the performance intricacies of heterogeneous drone-based small-cell networks.
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- NSF-PAR ID:
- 10496935
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Drones
- Volume:
- 7
- Issue:
- 10
- ISSN:
- 2504-446X
- Page Range / eLocation ID:
- 634
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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