Adjusting Transmit Power in UAV-Enabled Heterogeneous Networks Using Social-Assisted Bipartite Graph Technique

The escalating demand for mobile data has driven the need to explore innovative solutions for enhancing the capacity of cellular networks beyond Fifth-Generation (5G) standards. One promising approach is the deployment of small cells, low-power base stations with limited coverage. Additionally, Unmanned Aerial Vehicles (UAVs) can serve as flying base stations, providing connectivity when terrestrial infrastructure is compromised during emergencies. Nonetheless, the uncontrolled transmit power of small cells and UAVs can cause increased interference and energy consumption, negatively impacting overall network performance. To address these challenges, efficient power control strategies are crucial for optimizing performance and ensuring a high-quality user experience. In this paper, we propose a social-assisted bipartite graph technique for managing macro user transmit power. Initially, we construct an interference-aware bipartite graph based on users' Signal-to-Aggregate Interference Ratio (SAIR). We then reduce interference by minimizing the number of edges through social connections, adjusting transmit power, and improving system throughput. Our simulation results demonstrate that this technique significantly enhances system throughput and energy efficiency compared to traditional techniques.

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Published
2025-01-10
DOI
https://doi.org/10.1109/ccnc54725.2025.10976213
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
4.99
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article

Adjusting Transmit Power in UAV-Enabled Heterogeneous Networks Using Social-Assisted Bipartite Graph Technique

Kanhu Charan Gouda, Rahul Thakur
1 citations
UAV Applications and Optimization
4.99
article

Adjusting Transmit Power in UAV-Enabled Heterogeneous Networks Using Social-Assisted Bipartite Graph Technique

Kanhu Charan Gouda, Rahul Thakur
article en
1 citations

Abstract

The escalating demand for mobile data has driven the need to explore innovative solutions for enhancing the capacity of cellular networks beyond Fifth-Generation (5G) standards. One promising approach is the deployment of small cells, low-power base stations with limited coverage. Additionally, Unmanned Aerial Vehicles (UAVs) can serve as flying base stations, providing connectivity when terrestrial infrastructure is compromised during emergencies. Nonetheless, the uncontrolled transmit power of small cells and UAVs can cause increased interference and energy consumption, negatively impacting overall network performance. To address these challenges, efficient power control strategies are crucial for optimizing performance and ensuring a high-quality user experience. In this paper, we propose a social-assisted bipartite graph technique for managing macro user transmit power. Initially, we construct an interference-aware bipartite graph based on users' Signal-to-Aggregate Interference Ratio (SAIR). We then reduce interference by minimizing the number of edges through social connections, adjusting transmit power, and improving system throughput. Our simulation results demonstrate that this technique significantly enhances system throughput and energy efficiency compared to traditional techniques.

Indian Institute of Technology Roorkee (IN)
Reduced inequalities
Openalex Percentile: Top 6%
UAV Applications and Optimization
4.99
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Adjusting Transmit Power in UAV-Enabled Heterogeneous Networks Using Social-Assisted Bipartite Graph Technique — Kanhu Charan Gouda, Rahul Thakur · (2025) | TGRS Research Map | TGRS