  A challenge for rescue teams when fighting against wildfire in remote areas
is the lack of information, such as the size and images of fire areas. As such,
live streaming from Unmanned Aerial Vehicles (UAVs), capturing videos of
dynamic fire areas, is crucial for firefighter commanders in any location to
monitor the fire situation with quick response. The 5G network is a promising
wireless technology to support such scenarios. In this paper, we consider a
UAV-to-UAV (U2U) communication scenario, where a UAV at a high altitude acts as
a mobile base station (UAV-BS) to stream videos from other flying UAV-users
(UAV-UEs) through the uplink. Due to the mobility of the UAV-BS and UAV-UEs, it
is important to determine the optimal movements and transmission powers for
UAV-BSs and UAV-UEs in real-time, so as to maximize the data rate of video
transmission with smoothness and low latency, while mitigating the interference
according to the dynamics in fire areas and wireless channel conditions. In
this paper, we co-design the video resolution, the movement, and the power
control of UAV-BS and UAV-UEs to maximize the Quality of Experience (QoE) of
real-time video streaming. To learn the Deep Q-Network (DQN) and Actor-Critic
(AC) to maximize the QoE of video transmission from all UAV-UEs to a single
UAVBS. Simulation results show the effectiveness of our proposed algorithm in
terms of the QoE, delay and video smoothness as compared to the Greedy
algorithm.
