With the recent adoption of millimeter-wave spectrum in cellular communications, deployment of active antenna arrays and use of beamforming become vital to compensate for the increased path loss. However, directional high-frequency signals may suffer heavy attenuations due to blockage effects. Therefore, blockage modelling that adequately incorporates the effects of beamforming becomes increasingly relevant. We propose a Four Knife-Edge Diffraction with antenna Gain (4KED-G) model, a deterministic approach to model blockage with broad applicability. The 4KED-G model advances upon the existing models in its inclusion of both angular antenna gains and the diffraction from all the four edges of a rectangular screen blocker, leading to a more general and flexible blockage modelling approach compared to existing widely accepted blockage models. We theoretically show that the proposed generalised model incorporates the strengths of these existing models, while overcoming their shortcomings in establishing applicability to wider range of blockage scenarios. We validate the generalised model against known knife-edge diffraction blockage models for specific scenarios.

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One of the most challenging applications targeted by evolving (beyond-)5G technology is virtual reality (VR). Particularly, 'Social VR' applications provide a fully immersive experience and sense of togetherness to users residing at different locations. To support such applications the network must deal with huge traffic demands, while keeping end-to-end latencies low. Moreover, the radio access network must deal with the volatility and vulnerability of mmWave radio channels, where even small movements of the users may have substantial effects on the Quality of Experience. We present an integral modelling framework for feasibility assessment and performance optimization of the radio access network for Social VR applications in indoor office scenarios. Using the presented modelling approach, we conduct an extensive simulation-based assessment to determine the performance impact of head motion, the frequency band (3.5 GHz, 26 GHz) and radio network configurations, and derive the required carrier bandwidth for a range of 'Social VR' scenarios. Insights into these issues are a prerequisite for setting up guidelines for network deployment and configuration as well as for the development of (AI/ML-based) methods for dynamic resource management to optimally support Social VR applications. @en