International Journal of Electronic Devices and Networking
2025, Vol. 6, Issue 2, Part A
Adaptive beamforming algorithms for reconfigurable intelligent surfaces in IoT networks
Author(s): Ali Hassan Al-Jubouri, Layla Ibrahim Al-Samarrai and Ahmed Kadhim Al-Mustafa
Abstract: The rapid expansion of Internet of Things (IoT) networks has intensified the demand for high data throughput, energy efficiency, and reliable connectivity under resource-limited and interference-prone conditions. This research presents a comprehensive study on adaptive beamforming algorithms integrated with Reconfigurable Intelligent Surfaces (RIS) to optimize wireless communication performance in IoT environments. The proposed adaptive framework combines model-based and data-driven optimization, jointly adjusting base station beamforming weights and RIS reflection parameters to achieve dynamic control of the propagation environment. A simulation model with varying RIS element densities was implemented to evaluate system performance in terms of sum-rate, energy efficiency, convergence time, and robustness under channel uncertainty and mobility. Results demonstrate that the adaptive algorithm achieves near-optimal throughput comparable to full semidefinite programming (SDP) methods while substantially reducing computational complexity and signaling overhead. Energy efficiency improved by more than 20%, and convergence speed increased fourfold relative to conventional optimization techniques. The system maintained stability under imperfect channel state information and mobility conditions, confirming the robustness of the proposed framework for practical IoT deployment. Statistical analysis validated the significance of performance differences among methods, with p-values <0.001 and large effect sizes. The integration of adaptive beamforming and RIS effectively transforms static wireless channels into intelligent, reconfigurable environments capable of self-optimization. Based on these findings, the study recommends incorporating RIS-assisted adaptive control in future IoT network designs, developing low-complexity learning-based algorithms for edge devices, and standardizing RIS control protocols to ensure interoperability. The proposed approach paves the way for energy-efficient, scalable, and resilient communication systems in next-generation IoT ecosystems, supporting sustainable connectivity for diverse real-world applications such as smart cities, industrial automation, and wireless sensor networks.
DOI: 10.22271/27084477.2025.v6.i2a.84
Pages: 45-50 | Views: 277 | Downloads: 41
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How to cite this article:
Ali Hassan Al-Jubouri, Layla Ibrahim Al-Samarrai, Ahmed Kadhim Al-Mustafa. Adaptive beamforming algorithms for reconfigurable intelligent surfaces in IoT networks. Int J Electron Devices Networking 2025;6(2):45-50. DOI: 10.22271/27084477.2025.v6.i2a.84
