RIS-Assisted Proactive Handover for Reliable mmWave Wireless Networks
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Abstract (arXiv)
Millimeter-wave (mmWave) networks are highly susceptible to line-of-sight (LoS) blockages. Vision-aided wireless communications (VAWC) enable proactive handovers (PHO) to mitigate such blockages; however, PHO becomes challenging when no nearby base station (BS) is available. In such cases, reconfigurable intelligent surfaces (RIS) can be used to restore connectivity. To ensure timely PHO, the RIS configuration time must be taken into account, as the large number of RIS elements can limit responsiveness in time-sensitive scenarios. This work proposes a novel RIS-assisted PHO approach that optimizes the number of allocated RIS elements to balance signal processing complexity and link quality under handover timing constraints, making the RIS-assisted link more energy-efficient. An optimization problem based on particle swarm optimization (PSO) is formulated to determine the optimal end-to-end RIS link setup that runs offline to bypass latency constraints. Results show that reducing the number of RIS elements by 12% leads to a 10% decrease in dissipated energy without compromising the signal-to-noise ratio (SNR). Moreover, the RIS-assisted link achieves a 15--30 dB improvement in blocked regions while maintaining accurate PHO timing.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 18 of its 47 references that are in the map. First posted on arXiv 25 Jun 2026.
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18 of 47 references.
References · 18
- 2020Reconfigurable Intelligent Surfaces: Principles and Opportunitiescited by 34
- 2019Millimeter Wave Base Stations with Cameras: Vision Aided Beam and Blockage Predictioncited by 29
- 2019ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communicationscited by 21
- 2021RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trialscited by 12
- 2020Channel Estimation for RIS-Aided mmWave MIMO Systems via Atomic Norm Minimizationcited by 9
- 2021Radar Aided Proactive Blockage Prediction in Real-World Millimeter Wave Systemscited by 6
- 2021Environment-Aware Beam Selection for IRS-Aided Communication with Channel Knowledge Mapcited by 4
- 2023Point Cloud-based Proactive Link Quality Prediction for Millimeter-wave Communicationscited by 4
- 2020Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfacescited by 3
- 2020Machine Learning Empowered Beam Management for Intelligent Reflecting Surface Assisted MmWave Networkscited by 3
- 2021Fast Beam Training and Alignment for IRS-Assisted Millimeter Wave/Terahertz Systemscited by 3
- 2019Hybrid beamforming with dynamic subarrays and low-resolution PSs for mmWave MU-MISO systemscited by 2
6 more
- 2020Fast Beam Training for IRS-Assisted Multiuser Communicationscited by 2
- 2022Designing, Building, and Characterizing RF Switch-based Reconfigurable Intelligent Surfacescited by 2
- 2023Enhancing Reliability in Federated mmWave Networks: A Practical and Scalable Solution using Radar-Aided Dynamic Blockage Recognitioncited by 2
- 2019Communicating with Large Intelligent Surfaces: Fundamental Limits and Modelscited by 1
- 2021High-Resolution Programmable Scattering for Wireless Coverage Enhancement: An Indoor Field Trial Campaigncited by 1
- 2024Blockage-Aware Robust Beamforming in RIS-Aided Mobile Millimeter Wave MIMO Systemscited by 1
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