TY - JOUR
T1 - Unmanned Aircraft System Aided Adaptive Video Streaming
T2 - A Joint Optimization Approach
AU - Zhan, Cheng
AU - Hu, Han
AU - Wang, Zhi
AU - Fan, Rongfei
AU - Niyato, Dusit
N1 - Publisher Copyright:
© 1999-2012 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - Due to the coverage constraint of a wireless base station, mobile users suffer from the unstable network connection and poor service quality, especially for the prevalent video services. As an alternative solution, an unmanned aerial vehicle (UAV) is able to reach the cell edge and serve ground users (GUs). In this paper, we extend the UAV applications to the more challenging adaptive streaming service over fading channel. First, we decompose the system into different modules, and present mathematical models for each of them, including a trajectory model of the UAV, fading channels between the UAV and GUs, and video streaming utility. Second, we formulate the problem as a non-convex optimization problem by optimizing the UAV trajectory and transmit power allocation, jointly with transmission schedule and rate allocation for multiple users. The objective is to maximize the overall utility while guaranteeing the fairness among multiple users under the UAV energy budget and rate-outage probability constraints. Third, to tackle this problem, we first analyze the relationship between transmission rate and rate-outage probability over the fading channel, and then divide the original problem into three subproblems, which can be solved by leveraging the successive convex approximation technique. Furthermore, an overall iterative algorithm over the three subproblems is proposed to obtain a locally optimal solution by applying the block coordinate descent technique. Finally, through extensive experiments, we demonstrate that the proposed design can achieve almost 30\% performance gain in terms of max-min streaming utility for all users, compared with other benchmark schemes.
AB - Due to the coverage constraint of a wireless base station, mobile users suffer from the unstable network connection and poor service quality, especially for the prevalent video services. As an alternative solution, an unmanned aerial vehicle (UAV) is able to reach the cell edge and serve ground users (GUs). In this paper, we extend the UAV applications to the more challenging adaptive streaming service over fading channel. First, we decompose the system into different modules, and present mathematical models for each of them, including a trajectory model of the UAV, fading channels between the UAV and GUs, and video streaming utility. Second, we formulate the problem as a non-convex optimization problem by optimizing the UAV trajectory and transmit power allocation, jointly with transmission schedule and rate allocation for multiple users. The objective is to maximize the overall utility while guaranteeing the fairness among multiple users under the UAV energy budget and rate-outage probability constraints. Third, to tackle this problem, we first analyze the relationship between transmission rate and rate-outage probability over the fading channel, and then divide the original problem into three subproblems, which can be solved by leveraging the successive convex approximation technique. Furthermore, an overall iterative algorithm over the three subproblems is proposed to obtain a locally optimal solution by applying the block coordinate descent technique. Finally, through extensive experiments, we demonstrate that the proposed design can achieve almost 30\% performance gain in terms of max-min streaming utility for all users, compared with other benchmark schemes.
KW - Adaptive video streaming
KW - UAV trajectory
KW - fading channel
KW - transmission rate allocation
KW - unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85080949081&partnerID=8YFLogxK
U2 - 10.1109/TMM.2019.2931441
DO - 10.1109/TMM.2019.2931441
M3 - Article
AN - SCOPUS:85080949081
SN - 1520-9210
VL - 22
SP - 795
EP - 807
JO - IEEE Transactions on Multimedia
JF - IEEE Transactions on Multimedia
IS - 3
M1 - 8777128
ER -