Aerial Access and Backhaul in mmWave B5G Systems: Performance Dynamics and Optimization The use of unmanned aerial vehicle (UAV) based communication in millimeterwave (mmWave) frequencies to provide ondemand radio access is a promising approach to improve capacity and coverage in beyond5G (B5G) systems. There are several design aspects to be addressed when optimizing for the deployment of such UAV base stations. As traffic demand of mobile users varies across time and space, dynamic algorithms that correspondingly adjust the UAV locations are essential to maximize performance. In addition to careful tracking of spatiotemporal usertraffic activity, such optimization needs to account for realistic backhaul constraints. In this work, we first review the latest 3GPP activities behind integrated access and backhaul system design, support for UAV base stations, and mmWave radio relaying functionality. We then compare static and mobile UAVbased communication options under practical assumptions on the mmWave system layout, mobility and clusterization of users, antenna array geometry, and dynamic backhauling. We demonstrate that leveraging the UAV mobility to serve moving users may improve the overall system performance even in the presence of backhaul capacity limitations.

EnergyEfficient UAVAssisted Communication with Spectrum optimization In traditional ground cellular systems, ground terminals (GTs) in marginal areas are often faced with performance bottlenecks due to they are too far from the macro base station (MBS). For some temporary and unexpected communication service requirements, it is uneconomical to deploy femtocell access points (FAPs) on the edge of cell. In this paper, we investigate a cellular system that utilizes a unmanned aerial vehicles (UAVs) with base station module unit as an airborne mobile base station to provide communication channel for the celledge users offloaded by the MBS. Compared with FAPs, UAV is cheaper and flexible which can provide better communication quality for the celledge GTs with better channel condition. Based on the theoretical model, we proposed plausible optimal algorithm to maximize the energyefficiency (EE) of the UAV by jointly optimizing the spectrum allocation, flying speed and user partition between the UAV and MBS. Numerical results indicate that our design could achieve relatively higher energyefficiency by exploiting optimal flight strategy and spectrum allocation strategy.