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Energy Efficient Transmission of 3D Meshes Over MMWave-Based Massive MIMO Systems

Many mixed reality applications are based on the real-time compression and streaming of three-dimensional (3D) models. Thus, they demand very high-bandwidth and ultra-low latency from network specifications. The next-generation wireless networks will employ promising technologies to significantly improve the communication data rates. However, due to implementation complexity and thus increased energy consumption of these technologies, a trade-off between the quality-of-user-experience (QoE) and the hardware specifications is necessary. To overcome these limitations low-resolution quantizers have been of interest, which provide a trade-off between quality and complexity. In this paper, we propose a complexity-aware perceptual coding scheme that minimizes the reconstruction losses of the 3D models. Extensive simulations assuming different 3D models show that the proposed scheme achieves plausible reconstruction output offering significantly higher energy efficiency gains, as compared to a context unaware coding approaches.