218,889 research outputs found
Deep Learning Framework for Wireless Systems: Applications to Optical Wireless Communications
Optical wireless communication (OWC) is a promising technology for future
wireless communications owing to its potentials for cost-effective network
deployment and high data rate. There are several implementation issues in the
OWC which have not been encountered in radio frequency wireless communications.
First, practical OWC transmitters need an illumination control on color,
intensity, and luminance, etc., which poses complicated modulation design
challenges. Furthermore, signal-dependent properties of optical channels raise
non-trivial challenges both in modulation and demodulation of the optical
signals. To tackle such difficulties, deep learning (DL) technologies can be
applied for optical wireless transceiver design. This article addresses recent
efforts on DL-based OWC system designs. A DL framework for emerging image
sensor communication is proposed and its feasibility is verified by simulation.
Finally, technical challenges and implementation issues for the DL-based
optical wireless technology are discussed.Comment: To appear in IEEE Communications Magazine, Special Issue on
Applications of Artificial Intelligence in Wireless Communication
Unmanned Aerial Systems for Wildland and Forest Fires
Wildfires represent an important natural risk causing economic losses, human
death and important environmental damage. In recent years, we witness an
increase in fire intensity and frequency. Research has been conducted towards
the development of dedicated solutions for wildland and forest fire assistance
and fighting. Systems were proposed for the remote detection and tracking of
fires. These systems have shown improvements in the area of efficient data
collection and fire characterization within small scale environments. However,
wildfires cover large areas making some of the proposed ground-based systems
unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial
Systems (UAS) were proposed. UAS have proven to be useful due to their
maneuverability, allowing for the implementation of remote sensing, allocation
strategies and task planning. They can provide a low-cost alternative for the
prevention, detection and real-time support of firefighting. In this paper we
review previous work related to the use of UAS in wildfires. Onboard sensor
instruments, fire perception algorithms and coordination strategies are
considered. In addition, we present some of the recent frameworks proposing the
use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more
efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at:
https://doi.org/10.3390/drones501001
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