Holographic Education in 6G Era: Network Slicing Technology for Ultra High Bandwidth Multi-Sensory XR Consumer Learning Experience

As the globe moves into the 6G era, desire for immersive, ultra-high bandwidth learning experiences grows, resulting in the emergence of holographic education. However, the basic problems of providing these experiences, such as low latency, high bandwidth, and adaptability to changing network circumstances, provide significant impediments to scalable adoption. This research investigates the possibilities of 6G network slicing technologies for multi-sensory Extended Reality (XR) learning environments tailored to consumer needs. The research uses an Artificial Intelligence (AI)-based model that utilizes the Dynamic Radial Movement Optimized Intelligent Long Short-Term Memory (DRMO-IntelliLSTM) method and real-time data to dynamically allocate network resources via slicing, resulting in an optimum consumer-centric learning experience. The dataset contains network slicing parameters, 6G-based holographic education experiences. Data pre-processing entails dealing with missing data via imputation and Min-Max scaling to standardize continuous variables and model training. The Fourier Transform (FT) extracts frequency-domain information from time series data, and real-time processing. Simulation results are used to compare the suggested model's performance to that of traditional networks. The importance of the XR learning advances the prospects (outcomes), the DRMO- earnings, the network performance indicators attained by the DRMO- The IntelliLSTM model relatively, when compared with the traditional techniques, were tested by statistical analysis, t-tests among them. The findings show that DRMO-IntelliLSTM-assisted 6G network slicing has the potential to provide seamless, high-quality XR education by significantly improving throughput, latency, and consumer user experience. Finally, this research suggests that network slicing technology, enabled by AI, presents a solution for improving consumer-focused holographic education in the 6G period.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2025-10-08
DOI
https://doi.org/10.1109/tce.2025.3619103
Primary Topic
Cloud Computing and Remote Desktop Technologies
Type
article
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article

Holographic Education in 6G Era: Network Slicing Technology for Ultra High Bandwidth Multi-Sensory XR Consumer Learning Experience

Wanjuan Yin
IEEE Transactions on Consumer Electronics
Cloud Computing and Remote Desktop Technologies
article

Holographic Education in 6G Era: Network Slicing Technology for Ultra High Bandwidth Multi-Sensory XR Consumer Learning Experience

Wanjuan Yin
article en

Abstract

As the globe moves into the 6G era, desire for immersive, ultra-high bandwidth learning experiences grows, resulting in the emergence of holographic education. However, the basic problems of providing these experiences, such as low latency, high bandwidth, and adaptability to changing network circumstances, provide significant impediments to scalable adoption. This research investigates the possibilities of 6G network slicing technologies for multi-sensory Extended Reality (XR) learning environments tailored to consumer needs. The research uses an Artificial Intelligence (AI)-based model that utilizes the Dynamic Radial Movement Optimized Intelligent Long Short-Term Memory (DRMO-IntelliLSTM) method and real-time data to dynamically allocate network resources via slicing, resulting in an optimum consumer-centric learning experience. The dataset contains network slicing parameters, 6G-based holographic education experiences. Data pre-processing entails dealing with missing data via imputation and Min-Max scaling to standardize continuous variables and model training. The Fourier Transform (FT) extracts frequency-domain information from time series data, and real-time processing. Simulation results are used to compare the suggested model's performance to that of traditional networks. The importance of the XR learning advances the prospects (outcomes), the DRMO- earnings, the network performance indicators attained by the DRMO- The IntelliLSTM model relatively, when compared with the traditional techniques, were tested by statistical analysis, t-tests among them. The findings show that DRMO-IntelliLSTM-assisted 6G network slicing has the potential to provide seamless, high-quality XR education by significantly improving throughput, latency, and consumer user experience. Finally, this research suggests that network slicing technology, enabled by AI, presents a solution for improving consumer-focused holographic education in the 6G period.

IEEE Transactions on Consumer ElectronicsVol. 71(4)
Hangzhou Normal University (CN)
Openalex Percentile: Top 70%
Cloud Computing and Remote Desktop Technologies
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Holographic Education in 6G Era: Network Slicing Technology for Ultra High Bandwidth Multi-Sensory XR Consumer Learning Experience — Wanjuan Yin · IEEE Transactions on Consumer Electronics (2025) | TGRS Research Map | TGRS