Rendering Delay Minimization in RIS-Assisted Edge Computing for IIoT with VR Streaming

The end-users who are subjected to inadequate wireless network coverage sometimes experience a lack of ef-ficient utilization of available bandwidth due to low channel gain. The circumstance mentioned above has a negative impact on the overall virtual reality (VR) streaming efficiency in the industrial Internet of Things (IIoT) with VR add-ons. This study focuses on examining a wireless network that utilizes a reconfigurable intelligent surface (RIS) to assist in improving the channel efficiency for end-user devices located at weak signal reception zones. The optimization problem formulation related to the allocation of rendering resources in edge servers and the distribution of downlink bandwidth for VR content from the edge server can be expressed as a quadratically constrained quadratic problem. The non-convex optimization problem has been solved by dividing the problem into three sub-problems and solved using the block coordinate descent (BCD) method. Based on our comprehensive simulation findings, we demonstrate a significant enhancement in reducing delays, including rendering and transmission delays, when employing RIS compared to other reference scenarios. This improvement is observed through an increase in the number of end-users, including those suffering from suboptimal signal reception conditions.