Jul 2026· Signal Processing and Communications Applications Conference· pp. 1-4· 0 citations· 20 references
Abstract
In this study, subband assignment to base stations (BS) and simultaneous optimization of the three-dimensional positions of unmanned aerial vehicles (UAVs) in a multi-cell network supported by UAVs were performed using a genetic algorithm (GA). The aim of the optimization is to maximize a total speed metric that prioritizes edge users (UEs) (based on max-min fairness) at the cell edge. The proposed GA was compared with improved greedy and greedy+local lookup methods. Simulations for different cell radii show that the GA outperforms both methods in terms of total speed and max-min fairness; it improves service quality, especially in large cells, by more effectively directing edge users to UAVs.
Simulation of three typical UAV dispatching problems shows that greedy algorithm has better optimization in resource utilization and the convergence of the simulated annealing algorithm is better under the complex constraints.
Jiaming Wang, Jing Guo, Ning Du et al.· SAE technical paper series· 0 citations
— Unmanned Aerial Vehicles (UAVs) have emerged as flexible relay platforms capable of enhancing wireless connectivity in beyond-5G and 6G networks. This paper investigates the joint optimization of UAV trajectory and power allocation to maximize end-to-end throughput under practical mobility and power constraints. The problem is highly non-convex due to the strong coupling between trajectory variables and transmission power. To address this challenge, we develop a penalty-based metaheuristic framework that incorporates a constraint-handling mechanism into the Bat Algorithm (BAT). Simulation results show that the proposed BAT-based approach achieves significant throughput improvement, efficient power allocation, and fast convergence compared with baseline convex optimization and heuristic schemes. These findings highlight the potential of BAT for reliable and energy-efficient UAV-assisted communication in future wireless networks.
Pham Thi Quynh Trang· Journal of Communications· 0 citations
This paper focuses on the coverage deployment optimization of self-organizing UAV networks in three-dimensional space and proposes an improved Hippopotamus Optimization Algorithm. Latin hypercube initialization, an adaptive convergence factor, and a tangential flight strategy are introduced to improve the uniformity of the initial population, enhance the balance between global exploration and local exploitation, and strengthen the ability to avoid local optima. Network connectivity constraints are further incorporated into the model to ensure the communication feasibility of the deployment scheme. Simulation results demonstrate that the proposed method can achieve higher coverage, a more uniform node distribution, and better convergence and stability while satisfying connectivity constraints.
Guifen Chen, Guoxing Lang· Digital Signal and Computer...· 0 citations
In temporary emergency communication coverage scenarios where terrestrial communication infrastructure is damaged or lacks sufficient capacity, UAVs equipped with base stations have emerged as an effective solution due to their flexible deployment and rapid response capability. However, in multi-UAV networks, the three-dimensional deployment of UAVs significantly affects air-to-ground link quality, while power allocation further determines the level of system interference and throughput performance. To address this issue, this paper considers a multi-UAV communication system and jointly takes into account user link reliability and service requirement satisfaction, thereby establishing a joint optimization model for QoS-constrained coverage and network throughput. To address the non-convex joint optimization problem, a problem-tailored dual-population cooperative NSGA-II framework, termed IDPC-NSGA-II, is developed. By coupling dual-population evolution, adaptive mutation, uncovered-user-guided local search, and interference-aware repair with the characteristics of multi-UAV emergency communications, the proposed method improves the trade-off between QoS-constrained coverage and network throughput. Simulation results in a representative emergency communication scenario show that the proposed method achieves a favorable trade-off between QoS-constrained coverage and throughput, and outperforms the compared algorithms under the considered network setting.
Guifen Chen, Ruiyang Liu· Digital Signal and Computer...· 0 citations
Findings prove that SBOA is an effective and scalable clustering platform that can be applied to real-time FANET deployments during disaster recovery, surveillance, and monitoring operations in large regions.
Zaheer Aslam, Taj Rahman, G. Husnain et al.· Telecommunications Systems· 0 citations
This letter investigates resource allocation for a generalized coordinated direct and relay transmission (CDRT) framework assisted by an amplify-and-forward unmanned aerial vehicle (UAV), where the considered UAV simultaneously forwards the base station’s signals and delivers its own local information, yielding a unified transmission architecture well aligned with practical sensing and control applications. To manage the highly coupled interference topology among direct, forwarded, and relay-originated streams, we adopt the rate-splitting multiple access (RSMA) strategy. We formulate a joint optimization of precoding vectors, the UAV amplification matrix, and rate-splitting parameters to maximize the system sum rate. A penalty-based alternating optimization algorithm that combines semidefinite relaxation and successive convex approximation is customized to tackle the intertwined non-convex fractional terms. Simulation results demonstrate substantial sum-rate gains over the pure-forwarding, NOMA, and SDMA schemes in most considered cases, with the advantage becoming more pronounced under full-load and moderately overloaded conditions.
Dan Jiang, Yuanyuan Gao, Qiao Su et al.· IEEE Wireless Communications...· 0 citations