Optimal positioning of flying relays for wireless networks: A LOS map approach

This paper considers the exploitation of unmanned aerial vehicles (UAVs) in wireless networking, with which communication-enabled robots operate as flying wireless relays to help fill coverage or capacity gaps in the network. We focus on the particular problem of (automatic) UAV positioning, which is known to crucially affect performance. Existing methods typically rely on statistical models of the air-to-ground channel, and thus, they fail to exploit the fine-grained information of line-of-sight (LOS) conditions at some locations. This paper develops an efficient algorithm to find the best position of the UAV based on the fine-grained LOS information. In spite of the complex terrain topology, the algorithm is able to converge to the optimal UAV position to maximize the end-to-end throughput without a global exploration of a signal strength radio map. Numerical results demonstrate that in a dense urban area, the UAV-aided wireless system with the optimal UAV position can almost double the end-to-end capacity from the base station (BS) to the user as compared to that of a direct BS to user link.

[1]  Dan Keun Sung,et al.  Low-complexity maneuvering control of a UAV-based relay without location information of mobile ground nodes , 2014, 2014 IEEE Symposium on Computers and Communications (ISCC).

[2]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[3]  Walid Saad,et al.  Optimal transport theory for power-efficient deployment of unmanned aerial vehicles , 2016, 2016 IEEE International Conference on Communications (ICC).

[4]  Yimin Zhang,et al.  Joint optimization of relay position and power allocation in cooperative broadcast wireless networks , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[5]  Andrew R. Nix,et al.  Path Loss Models for Air-to-Ground Radio Channels in Urban Environments , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[6]  Walid Saad,et al.  Drone Small Cells in the Clouds: Design, Deployment and Performance Analysis , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[7]  Abbas Jamalipour,et al.  Modeling air-to-ground path loss for low altitude platforms in urban environments , 2014, 2014 IEEE Global Communications Conference.

[8]  Jia Liu,et al.  Optimization of beamforming and path planning for UAV-assisted wireless relay networks , 2014 .

[9]  Kandeepan Sithamparanathan,et al.  Optimal LAP Altitude for Maximum Coverage , 2014, IEEE Wireless Communications Letters.

[10]  David Gesbert,et al.  Learning radio maps for UAV-aided wireless networks: A segmented regression approach , 2017, 2017 IEEE International Conference on Communications (ICC).

[11]  Tor Arne Johansen,et al.  Performance evaluation of cooperative relay and Particle Swarm Optimization path planning for UAV and wireless sensor network , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).