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 s...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/10/634 |
| _version_ | 1797574037827747840 |
|---|---|
| author | Nima Namvar Fatemeh Afghah Ismail Guvenc |
| author_facet | Nima Namvar Fatemeh Afghah Ismail Guvenc |
| author_sort | Nima Namvar |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T21:18:37Z |
| format | Article |
| id | doaj.art-69d44db7b0b644eaa39da7d81a919fa6 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-10T21:18:37Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-69d44db7b0b644eaa39da7d81a919fa62023-11-19T16:15:43ZengMDPI AGDrones2504-446X2023-10-0171063410.3390/drones7100634Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate SatisfactionNima Namvar0Fatemeh Afghah1Ismail Guvenc2School of Informatics, Computing and Cyber Systems (SICSS), Northern Arizona University, Flagstaff, AZ 86011, USADepartment of Electrical & Computer Engineering, Clemson University, Clemson, SC 29634, USADepartment Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USAIn 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.https://www.mdpi.com/2504-446X/7/10/634beamformingdrone base station (DBS)power efficiencyresource optimization3D deployment |
| spellingShingle | Nima Namvar Fatemeh Afghah Ismail Guvenc Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction Drones beamforming drone base station (DBS) power efficiency resource optimization 3D deployment |
| title | Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction |
| title_full | Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction |
| title_fullStr | Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction |
| title_full_unstemmed | Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction |
| title_short | Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction |
| title_sort | heterogeneous drone small cells optimal 3d placement for downlink power efficiency and rate satisfaction |
| topic | beamforming drone base station (DBS) power efficiency resource optimization 3D deployment |
| url | https://www.mdpi.com/2504-446X/7/10/634 |
| work_keys_str_mv | AT nimanamvar heterogeneousdronesmallcellsoptimal3dplacementfordownlinkpowerefficiencyandratesatisfaction AT fatemehafghah heterogeneousdronesmallcellsoptimal3dplacementfordownlinkpowerefficiencyandratesatisfaction AT ismailguvenc heterogeneousdronesmallcellsoptimal3dplacementfordownlinkpowerefficiencyandratesatisfaction |