AI-Based Data Compression for Real-Time Holographic Communication in 7G Networks

Abstract

Holographic communication is emerging as a transformative technology for next-generation immersive interaction, enabling real-time three-dimensional (3D) visualization of people, objects, and environments with full depth, parallax, and multi-view perspectives. However, holographic systems generate extremely large volumes of data because they capture not only spatial information but also depth maps, phase, amplitude, and light-field components. Transmitting such raw holographic data in real time results in severe bandwidth consumption, high latency, and network congestion. Even future 7G networks, despite their anticipated terabit-per-second capacity and ultra-low latency, cannot efficiently support continuous uncompressed holographic streaming. Moreover, traditional compression techniques reduce data size at the cost of visual fidelity and perceptual realism, making real-time holographic communication impractical. This study proposes an Artificial Intelligence (AI)-based data compression framework designed specifically for real-time holographic communication in 7G networks. The proposed model leverages deep learning architectures including convolutional neural networks, transformer-based attention mechanisms, and generative reconstruction models to identify perceptually significant holographic features while eliminating redundant or predictable data. Instead of transmitting full holographic content, the system encodes essential information into a compact latent representation and reconstructs high-fidelity holograms at the receiver using AI-driven generative models. The proposed approach significantly reduces data transmission requirements while preserving realistic visual quality, achieving high compression ratios with minimal perceptual distortion. The framework demonstrates strong potential to enable scalable, low-latency, and bandwidth-efficient holographic communication over 7G networks, thereby advancing the feasibility of immersive telepresence, remote collaboration, and next-generation metaverse applications.