MUET logo

Power Efficient Mathematical Model for UAV Communication Networks

Authors

  • Haque Nawaz

    Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan
    Author

  • Muhammad Haroon Yousaf

    Department of Computer Engineering, UET Taxila, Taxila, Pakistan
    Author

  • Imtiaz Hussain

    Department of AI & Mathematics, Sindh Madressatul Islam University, Karachi, Pakistan
    Author

  • Husnain Mansoor Ali

    Department of Computer Science, SZABIST, Karachi, Pakistan
    Author

DOI:

https://doi.org/10.22581/0574

Keywords:

UAV Communication, UAV (Unmanned Aerial Vehicle) , Efficient Power, Mathematic Model, Power Efficient Mathematical Model

Abstract

The recent development in unmanned aerial vehicles (UAVs) plays an imperative role in the field of wireless communication networks. These UAVs communicate with each other in the air for various substantial applications. However, after a certain duration, this network faces power issues due to inadequate power resources. Hence, a power-efficient mechanism is required for routing the information in UAV communication. However, in this research study, we propose a power-efficient mathematical model for UAV communication networks. By using a power-efficient mathematical model, the UAVs can determine the power information and route the data packets efficiently. The implementation has been carried out by using the simulator tool OPNET modeler. We have run the EPOLSR routing protocol, as well as the prevailing routing protocols OLSR using this model. The performance of the network has been significantly improved, and the results show that the EPOLSR outperforms OLSR, enhancing the lifetime and performance of UAVs' communication networks in terms of increased throughput and minimized delay by utilizing the proposed power-efficient mathematical model environment. Furthermore, the protocol EPOLSR was compared with OLSR, DSR, and AODV, and the results were observed. Consequently, EPOLSR outperforms OLSR, DSR, and AODV in terms of throughput and delay by utilizing a power-efficient mathematical model.

Downloads

References

[1] M. J. Almansor et al., “Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues,” Alex. Eng. J., vol. 109, pp. 553–577, Dec. 2024, doi: 10.1016/j.aej.2024.09.032.

[2] Y. Tan et al., “Intelligent inspection of building exterior walls using UAV and mixed reality based on man-machine-environment system engineering,” Autom. Constr., vol. 177, p. 106344, Sep. 2025, doi: 10.1016/j.autcon.2025.106344.

[3] L. Zhen, Z. Yang, G. Laporte, W. Yi, and T. Fan, “Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management,” Engineering, vol. 36, pp. 223–239, May 2024, doi: 10.1016/j.eng.2023.10.014.

[4] S. O. de Macedo, M. Caetano, and R. M. da Costa, “Drone detection in airport environments: A literature review,” Array, vol. 28, p. 100511, Dec. 2025, doi: 10.1016/j.array.2025.100511.

[5] D. R. Sarkar, K. R. Rao, and N. Chatterjee, “Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic,” Transp. Res. Rec., vol. 2679, no. 2, pp. 1274–1290, Feb. 2025, doi: 10.1177/03611981241266838.

[6] P. Shukla and S. Shukla, “Unmanned Aerial Vehicle (UAV) Based Disaster Detection and Crowd Sensing Using Deep Learning Models,” in Proceedings of the 26th International Conference on Distributed Computing and Networking, in ICDCN ’25. New York, NY, USA: Association for Computing Machinery, Jan. 2025, pp. 414–419. doi: 10.1145/3700838.3703685.

[7] Z. Zhang and L. Zhu, “A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications,” Drones, vol. 7, no. 6, p. 398, Jun. 2023, doi: 10.3390/drones7060398.

[8] S. Boubaker, C. Vacca, C. Rosales, S. Kamel, F. S. Alsubaei, and F. Rossomando, “UAV Formation for Cargo Transport by PID Control with Neural Compensation,” Mathematics, vol. 13, no. 16, p. 2650, Jan. 2025, doi: 10.3390/math13162650.

[9] M. Tavakol Sadrabadi, J. Peiró, M. S. Innocente, and G. Rein, “Conceptual design of a wildfire emergency response system empowered by swarms of unmanned aerial vehicles,” Int. J. Disaster Risk Reduct., vol. 124, p. 105493, Jun. 2025, doi: 10.1016/j.ijdrr.2025.105493.

[10] J. Agrawal and M. Y. Arafat, “Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture,” Drones, vol. 8, no. 11, p. 664, Nov. 2024, doi: 10.3390/drones8110664.

[11] A. Tsellou et al., “A UAV Intelligent System for Greek Power Lines Monitoring,” Sensors, vol. 23, no. 20, p. 8441, Oct. 2023, doi: 10.3390/s23208441.

[12] W. Chen, D. Wang, and X. Xie, “An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery,” Animals, vol. 15, no. 12, p. 1794, Jan. 2025, doi: 10.3390/ani15121794.

[13] M. Aljohani, R. Mukkamala, and S. Olariu, “Delivery of Medical Supplies to Remote Locations via Unmanned Aerial Vehicles: Approaches, Challenges, and Solutions,” Transp. Res. Procedia, vol. 84, pp. 73–80, Jan. 2025, doi: 10.1016/j.trpro.2025.03.047.

[14] L.-C. Chen, C.-J. Huang, Y.-S. Cheng, K.-W. Hu, and M.-E. Jian, “UAV-Enabled Video Streaming Architecture for Urban Air Mobility: A 6G-Based Approach Toward Low-Altitude 3D Transportation,” Drones, vol. 9, no. 6, p. 448, Jun. 2025, doi: 10.3390/drones9060448.

[15] F. Wan, M. B. Yaseen, M. B. Riaz, A. Shafiq, A. Thakur, and M. O. Rahman, “Advancements and challenges in UAV-based communication networks: A comprehensive scholarly analysis,” Results Eng., vol. 24, p. 103271, Dec. 2024, doi: 10.1016/j.rineng.2024.103271.

[16] A. Kwasiborska, A. Stelmach, and I. Jabłońska, “Quantitative and Comparative Analysis of Energy Consumption in Urban Logistics Using Unmanned Aerial Vehicles and Selected Means of Transport,” Energies, vol. 16, no. 18, p. 6467, Jan. 2023, doi: 10.3390/en16186467.

[17] H. Li, R. Jia, Z. Zheng, and M. Li, “Energy-Efficient UAV Trajectory Design and Velocity Control for Visual Coverage of Terrestrial Regions,” Drones, vol. 9, no. 5, p. 339, May 2025, doi: 10.3390/drones9050339.

[18] H. V. Abeywickrama, B. A. Jayawickrama, Y. He, and E. Dutkiewicz, “Empirical Power Consumption Model for UAVs,” in 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), Aug. 2018, pp. 1–5. doi: 10.1109/VTCFall.2018.8690666.

[19] J. Shi, Z. Li, W. Sun, Z. Bai, F. Wang, and T. Q. S. quek, “Multi-agent SAC approach aided joint trajectory and power optimization for multi-UAV assisted wireless networks with safety constraints,” Chin. J. Aeronaut., vol. 38, no. 10, p. 103368, Oct. 2025, doi: 10.1016/j.cja.2024.103368.

[20] X. Wu, C. Yang, G. Han, Z. Ye, and Y. Hu, “Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method,” Energies, vol. 15, no. 15, p. 5453, Jan. 2022, doi: 10.3390/en15155453.

[21] G. Aiello, R. Inguanta, G. D’Angelo, and M. Venticinque, “Energy Consumption Model of Aerial Urban Logistic Infrastructures,” Energies, vol. 14, no. 18, p. 5998, Jan. 2021, doi: 10.3390/en14185998.

[22] J. Carvajal-Rodríguez, D. Vega-Sánchez, C. Tipantuña, L. F. Urquiza, F. Grijalva, and X. Hesselbach, “Optimization of Transmission Power in a 3D UAV-Enabled Communication System,” Drones, vol. 9, no. 7, p. 485, Jul. 2025, doi: 10.3390/drones9070485.

[23] J. Zhang, S. Maimaiti, W. Gao, and K. Zhang, “Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area,” Drones, vol. 9, no. 3, p. 178, Mar. 2025, doi: 10.3390/drones9030178.

[24] T. Zhao, Y. Zhang, M. Wang, W. Feng, S. Cao, and G. Wang, “A Critical Review on the Battery System Reliability of Drone Systems,” Drones, vol. 9, no. 8, p. 539, Aug. 2025, doi: 10.3390/drones9080539.

[25] X. Jian et al., “High-Reliability Low-Latency Intelligent Geographic Routing Protocol for Vehicle Road Cooperation System,” IEEE Internet Things J., vol. 12, no. 2, pp. 1774–1788, Jan. 2025, doi: 10.1109/JIOT.2024.3465519.

[26] A. K. Obaid, M. Ezanee Bin Rusli, and S. Yussof, “Toward Intelligent Caching in DSR Protocols: Route Compression, Hierarchical Structures, and Link-Aware Optimization in MANETs,” IEEE Access, vol. 13, pp. 145071–145087, 2025, doi: 10.1109/ACCESS.2025.3599779.

[27] H. Nawaz, H. M. Ali, and G. Nabi, “Simulation based analysis of Reactive Protocols Metrics in MANET Using OPNET,” Sindh Univ. Res. J. - SURJ Sci. Ser., vol. 46, no. 4, pp. 531–538, Dec. 2014, doi: https://sujo.usindh.edu.pk/index.php/SURJ/article/view/5455.

[28] H. Nawaz and H. Mansoor Ali, “Implementation of Cross Layer Design for Efficient Power and Routing in UAV Communication Networks,” Stud. Inform. Control, vol. 29, no. 1, pp. 111–120, Mar. 2020, doi: 10.24846/v29i1y202011.

Published

2026-04-01

Issue

Vol. 45 No. 2 (2026): April Issue

Section

Articles

License

Copyright (c) 2026 Mehran University Research Journal of Engineering and Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Power Efficient Mathematical Model for UAV Communication Networks . (2026). Mehran University Research Journal of Engineering and Technology, 45(2), 102-109. https://doi.org/10.22581/0574

Similar Articles

1-10 of 79

You may also start an advanced similarity search for this article.