Joint Holographic Beamforming and User Scheduling With Individual QoS Constraints

January 1, 2025·
Chandan Kumar Sheemar
,
Christo Kurisummoottil Thomas
,
George C. Alexandropoulos
,
Jorge Querol
,
Symeon Chatzinotas
,
Walid Saad
· 1 min read
DOI
Abstract
Reconfigurable holographic surfaces (RHS) have emerged as a transformative material technology, enabling dynamic control of electromagnetic waves to generate versatile holographic beam patterns. This paper addresses the problem of joint hybrid holographic beamforming and user scheduling under per-user minimum quality-of-service (QoS) constraints, a critical challenge in resource-constrained networks. However, such a problem results in mixed- integer non-convex optimization, making it difficult to identify feasible solutions efficiently. To overcome this challenge, we propose a novel iterative optimization framework that jointly solves the problem to maximize the RHS-assisted network sum-rate, efficiently managing holographic beamforming patterns, dynamically scheduling users, and ensuring the minimum QoS requirements for each scheduled user. The proposed framework relies on zero-forcing digital beamforming, gradient-ascent-based holographic beamformer optimization, and a greedy user selection principle. Our extensive simulation results validate the effectiveness of the proposed scheme, demonstrating their superior performance compared to the benchmark algorithms in terms of sum-rate performance, while meeting the minimum per-user QoS constraints.
Type
Publication
IEEE Transactions on Vehicular Technology
publication

Abstract & Overview

Reconfigurable holographic surfaces (RHS) have emerged as a transformative material technology, enabling dynamic control of electromagnetic waves to generate versatile holographic beam patterns. This paper addresses the problem of joint hybrid holographic beamforming and user scheduling under per-user minimum quality-of-service (QoS) constraints, a critical challenge in resource-constrained networks. However, such a problem results in mixed- integer non-convex optimization, making it difficult to identify feasible solutions efficiently. To overcome this challenge, we propose a novel iterative optimization framework that jointly solves the problem to maximize the RHS-assisted network sum-rate, efficiently managing holographic beamforming patterns, dynamically scheduling users, and ensuring the minimum QoS requirements for each scheduled user. The proposed framework relies on zero-forcing digital beamforming, gradient-ascent-based holographic beamformer optimization, and a greedy user selection principle. Our extensive simulation results validate the effectiveness of the proposed scheme, demonstrating their superior performance compared to the benchmark algorithms in terms of sum-rate performance, while meeting the minimum per-user QoS constraints.

Publication Metadata

  • Authors: Chandan Kumar Sheemar, Christo Kurisummoottil Thomas, George C. Alexandropoulos, Jorge Querol, Symeon Chatzinotas, Walid Saad
  • Venue: IEEE Transactions on Vehicular Technology (2025)
  • Research Areas: AI & Neuromorphic SatCom, Beamforming & MIMO
  • DOI: 10.1109/tvt.2025.3569401
AI & Neuromorphic SatCom Beamforming & MIMO