Joint Altitude, Beamwidth, Location, and Bandwidth Optimization for UAV-Enabled Communications

Yang, Zhaohui; Pan, Cunhua; Shikh‐Bahaei, Mohammad; Xu, Wei; Chen, Ming; Elkashlan, Maged; Nallanathan, Arumugam · 2018 · OpenAlex-citations

DOI: 10.1109/lcomm.2018.2846241

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Summary

This paper addresses the optimization of uplink power consumption in unmanned aerial vehicle (UAV)-enabled wireless communication systems. Motivated by the need to fully exploit the design degrees of freedom offered by UAV mobility and antenna characteristics, the authors investigate a joint optimization problem involving the UAV’s flying altitude, antenna beamwidth, horizontal location, and the bandwidth and transmit power of ground terminals (GTs). The primary objective is to minimize the sum uplink transmit power of all GTs while satisfying minimal rate requirements and system constraints, such as maximum bandwidth and physical limits on UAV height and antenna beamwidth. The study formulates this as a nonconvex optimization problem due to the complex interactions between altitude, beamwidth, location, and bandwidth. To solve it, the authors propose an iterative algorithm with low computational complexity that decomposes the problem into three subproblems, each solvable optimally when other variables are fixed. First, the optimal altitude and beamwidth are determined; notably, for the common case where the pathloss exponent is two, the optimal beamwidth is found using a bisection method, while altitude is derived in closed form. Second, the optimal UAV location is obtained by solving a convex problem using standard interior point methods. Third, optimal bandwidth allocation is achieved via a closed-form solution derived from Karush-Kuhn-Tucker conditions and solved using a bisection method. The algorithm iterates through these steps until convergence. Numerical results demonstrate the effectiveness of the proposed approach in a scenario with 20 uniformly distributed GTs. The analysis reveals that the sum power initially decreases and then increases as the beamwidth varies, highlighting the importance of joint optimization. The proposed algorithm achieves performance very close to that of an exhaustive search method, which serves as a global optimum benchmark, but with significantly lower computational complexity. Specifically, the algorithm successfully minimizes sum power across various minimal rate demands and pathloss exponents, confirming that joint optimization of altitude, beamwidth, location, and bandwidth yields substantial power savings compared to fixed-parameter approaches. The significance of this work lies in providing a practical, low-complexity solution for energy-efficient UAV communications. By establishing that optimal beamwidth can be effectively computed via bisection and bandwidth allocation in closed form, the paper offers actionable insights for designing UAV-assisted networks. The findings underscore that neglecting any of these parameters—particularly beamwidth and altitude—can lead to suboptimal power usage, thereby validating the necessity of holistic optimization strategies in next-generation aerial communication systems.

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• v2x connected vehicle