Joint Beamforming and 3D Location Optimization for Multi-User Holographic UAV Communications

January 1, 2026·
Chandan Kumar Sheemar
,
Asad Mahmood
,
Christo Kurisummoottil Thomas
,
George C. Alexandropoulos
,
Jorge Querol
,
Symeon Chatzinotas
,
Walid Saad
· 1 min read
DOI
Abstract
This paper pioneers the domain of multi-user holographic unmanned aerial vehicle (UAV) communications, establishing a robust foundation for future advancements in next-generation aerial wireless networks. It investigates the joint design of hybrid holographic beamforming and three-dimensional (3D) positioning for a UAV equipped with a reconfigurable holographic surface (RHS), with the objective of maximizing the network’s sum rate. To tackle this inherently complex and non-convex optimization problem, a novel alternating optimization framework is proposed. The solution leverages zero-forcing (ZF) digital beamforming and a gradient ascent strategy to iteratively update the holographic beamforming weights and the UAV’s 3D location, while satisfying key system constraints. This framework is tailored to efficiently navigate the trade-offs between hybrid transceiver design and UAV mobility limitations, ensuring both adaptability and performance scalability. Simulation results confirm that the proposed approach achieves substantial gains in sum rate and system robustness compared to conventional methods, validating its effectiveness under diverse channel and deployment conditions.
Type
Publication
IEEE Transactions on Communications
publication

Abstract & Overview

This paper pioneers the domain of multi-user holographic unmanned aerial vehicle (UAV) communications, establishing a robust foundation for future advancements in next-generation aerial wireless networks. It investigates the joint design of hybrid holographic beamforming and three-dimensional (3D) positioning for a UAV equipped with a reconfigurable holographic surface (RHS), with the objective of maximizing the network’s sum rate. To tackle this inherently complex and non-convex optimization problem, a novel alternating optimization framework is proposed. The solution leverages zero-forcing (ZF) digital beamforming and a gradient ascent strategy to iteratively update the holographic beamforming weights and the UAV’s 3D location, while satisfying key system constraints. This framework is tailored to efficiently navigate the trade-offs between hybrid transceiver design and UAV mobility limitations, ensuring both adaptability and performance scalability. Simulation results confirm that the proposed approach achieves substantial gains in sum rate and system robustness compared to conventional methods, validating its effectiveness under diverse channel and deployment conditions.

Publication Metadata

  • Authors: Chandan Kumar Sheemar, Asad Mahmood, Christo Kurisummoottil Thomas, George C. Alexandropoulos, Jorge Querol, Symeon Chatzinotas, Walid Saad
  • Venue: IEEE Transactions on Communications (2026)
  • Research Areas: Beamforming & MIMO
  • DOI: 10.1109/tcomm.2026.3663285
Beamforming & MIMO