Beamforming Design Toward Sum-Rate Maximization for Holographic Active RIS-Aided Uplink Near-Field Communications

Holographically driven active reconfigurable intelligent surface (HARIS), leveraging densely packed subwavelength elements, overcomes the limitations of conventional RIS in signal processing, unlocking advanced capabilities for next-generation networks. Thus, to exploit its full potential, this work proposes the integration of HARIS into an Internet of Things (IoT) multiuser uplink near-field-driven wireless communication system. A sum-rate maximization problem is formulated to provide efficient resource utilization by jointly optimizing the equalizer design, power allocation at each IoT user, and the HARIS phase shift, while satisfying strict constraints of Quality-of-Service (QoS) requirement and limited power budget at each IoT user and HARIS. Due to the nonconvex nature of the problem, we propose an alternating optimization (AO)-based algorithm, incorporating techniques, such as minimum-mean-square error (MMSE), convex upper bound approximation, and semidefinite relaxation (SDR). Then, extensive simulations validate the algorithm’s efficacy and convergence, demonstrating up to 63% higher performance with HARIS than passive RIS. Additionally, we highlight that near-field communication yields up to 90% higher sum-rate than hybrid 76% and far-field model 73%. Moreover, we demonstrate the impact of imperfect channel state information (iCSI) on the system performance.