Adaptive Encoding Rate and Clustering Assisted Probabilistic Edge Caching Optimization for Video Transmission in Dense D2D Networks

In this paper, we propose an offloading system for video transmission in dense device-to-device (D2D) networks. The system is able to offload the videos to the mobile users (MU) over D2D communications. This way can also mitigate the workload of the macro base stations and the congestion situation at the backhaul links of B5G/6G networks. Particularly, we formulate an adaptive encoding rate and clustering assisted probabilistic edge caching (RCC) optimization problem under the resource constraints on the storage of mobile devices and the throughput of system. The RCC problem is solved for the optimal encoding rate and caching probability of each video and optimal clustering radius for offloading the requested videos. As a result, the proposed RCC method gains a higher performance in terms of playback quality of received videos and resource utilization compared to the other conventional ones.