Joint Holographic Beamforming and User Scheduling with Individual QoS Constraints

TL;DR

This paper introduces an iterative optimization framework for joint holographic beamforming and user scheduling in RHS-assisted networks, maximizing sum-rate while satisfying individual QoS constraints.

Contribution

It presents a novel method combining zero-forcing, gradient ascent, and greedy user selection to efficiently solve a complex non-convex optimization problem.

Findings

Outperforms benchmark algorithms in sum-rate performance.

Effectively meets per-user QoS constraints.

Validates approach through extensive simulations.

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