Name
Title | ||
|---|---|---|
Reflections in the Sky - Millimeter Wave Communication with UAV-Carried Intelligent Reflectors. |
Abstract | ||
|---|---|---|
In this paper, a novel approach that uses an unmanned aerial vehicle (UAV)-carried intelligent reflector (IR) is proposed to enhance the performance of millimeter wave (mmW) networks. In particular, the UAV-IR is used to intelligently reflect mmW beamforming signals from a base station towards a mobile outdoor user, while harvesting energy from mmW signals to power the IR. To maintain a line-of-sight (LOS) channel, a reinforcement learning (RL) approach, based on Q- learning and neural networks, is proposed to model the propagation environment, such that the location and reflection coefficient of the UAV-IR can be optimized to maximize the downlink transmission capacity. Simulation results show a significant advantage for using a UAV-IR over a static IR, in terms of the average data rate and the achievable downlink LOS probability. The results also show that the RL-based deployment of the UAV-IR further improves the network performance, relative to a scheme without learning. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/GLOBECOM38437.2019.9013626 | GLOBECOM |
DocType | Citations | PageRank |
Conference | 1 | 0.36 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qianqian Zhang | 1 | 98 | 14.95 |
| Walid Saad | 2 | 4450 | 279.64 |
| Mehdi Bennis | 3 | 3652 | 217.26 |