Wifi-VLC dual connectivity streaming system for 6DOF multi-user virtual reality

We investigate a future WiFi-VLC dual connectivity streaming system for 6DOF multi-user virtual reality that enables reliable high-fidelity remote scene immersion. The system integrates an edge server that uses scalable 360° tiling to adaptively split the present 360° view of a VR user into a panoramic baseline content layer and a viewport-specific enhancement content layer. The user is then served the two content layers over complementary WiFi and VLC wireless links such that the delivered viewport quality is maximized for the given WiFi and VLC transmission resources. We formally characterize the actions of the server using rate-distortion optimization that we solve at low complexity. To account for the users' mobility as they explore different 360° viewpoints of the 6DOF remote scene content and maintain reliable high-quality VLC connectivity, we explore dynamic VLC transmitter steering and assignment in the system as graph bottleneck matching that aims to maximize the received VLC SNR across all users. We formulate an effective low-complexity solution to this discrete combinatorial optimization problem of high complexity. The paper also contributes a first actual 6DOF body and head movement VR navigation dataset that we collected and facilitate to assess the performance of our system via simulation experiments. These demonstrate enhanced VLC transmission performance and an up to 7 dB gain in viewport quality over a state-of-the-art VLC cellular system (LiFi), and an up to 10 dB gain in viewport quality over a state-of-the-art traditional wireless streaming method, for 12K-120fps 360° 6DOF VR content. Moreover, the synergistic WiFi-VLC dual connectivity of the proposed system augments its reliability over the reference method LiFi that comprises only VLC links. These outcomes motivate further exploration and prototype implementation of our system.