Kama Ramudu; Chavvakula Janaki Devi; Azmeera Srinivas; Manumula Srinubabu; Mudunuru Suneel

Energy-Efficient UAV-Assisted Post-Disaster Communications via WGSML-Based D2D Clustering and Optimal Trajectory Optimization

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Author(s)

Kama Ramudu ^1,* Chavvakula Janaki Devi ¹ Azmeera Srinivas ² Manumula Srinubabu ¹ Mudunuru Suneel ¹

1. Department of Electronics and Communication Engineering, Aditya University, Surampalem, Andhra Pradesh, India

2. Department of Electronics and Communication Engineering, Kakatiya Institute of Technology and Science, Warangal, Telangana, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijwmt.2026.03.24

Received: 4 Feb. 2026 / Revised: 1 Apr. 2026 / Accepted: 9 May 2026 / Published: 8 Jun. 2026

Index Terms

Disaster Management, Unmanned Aerial Vehicle (UAV), Device-to-Device (D2D) Communication, Weighted Global Search Matrix Level (WGSML), Energy Harvesting (EH), Hidden Markov Model (HMM), Cluster Head Selection, Trajectory Optimization, Deep Q-Network (DQN)

Abstract

Unmanned Aerial Vehicles (UAVs) have become an effective solution for establishing emergency communication in post-disaster environments where conventional infrastructure is damaged. However, limited UAV battery capacity and unstable connectivity significantly reduce communication reliability and operational coverage. To address these challenges, this paper proposes an energy-efficient UAV-assisted communication framework based on Weighted Global Search Matrix Level (WGSML) clustering and optimal trajectory optimization for device-to-device (D2D) communication. The proposed WGSML method performs energy-aware cluster formation and cluster-head selection using residual energy, signal-to-noise ratio, and neighbourhood density. A Hidden Markov Model (HMM) is employed for routing optimization, while Q-learning-based resource allocation is utilized to determine optimal UAV trajectories and maximize residual energy utilization. Simulation results demonstrate that the proposed approach improves energy harvesting performance, reduces outage probability, minimizes computational runtime, and enhances spectral efficiency compared with existing clustering methods. The proposed framework provides reliable and sustainable communication support for post-disaster emergency response scenarios.

Cite This Paper

Kama Ramudu, Chavvakula Janaki Devi, Azmeera Srinivas, Manumula Srinubabu, Mudunuru Suneel, "Energy-Efficient UAV-Assisted Post-Disaster Communications via WGSML-Based D2D Clustering and Optimal Trajectory Optimization", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.16, No.3, pp. 359-387, 2026. DOI:10.5815/ijwmt.2026.03.24

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