Deep Learning Framework for Wireless Systems: Applications to Optical Wireless Communications
By Hoon Lee, Sang Hyun Lee, Tony Q. S. Quek, Inkyu Lee. 2018
48 citations recorded by the source corpus.
Optical wireless communication (OWC) is a promising technology for future wireless communications due to its potential for cost-effective network deployment and high data rate. There are several implementation issues in OWC that have not been encountered in radio frequency wireless communications. First, practical OWC transmitters need illumination control on color, intensity, luminance, and so on, which poses complicated modulation design challenges. Furthermore, signal-dependent properties of optical channels raise nontrivial challenges in both 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.
Subfields: Electrical and Electronic Engineering, Instrumentation
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- H. Vincent Poor
- Howard H. Yang
- Tony Q. S. Quek
- Zuozhu Liu
- Zhiguo Ding
- Mingzhe Chen
- Walid Saad
- Yuanwei Liu
Citations in the corpus
- Scheduling Policies for Federated Learning in Wireless Networks (2019, background): “…in a data center, to edge computing systems which largely deploy computational power to the network edges to meet the needs of applications that demand very high bandwidth and low latency, as well as supporting resource-constrained nodes reachable only over unreliable network connections [1]–[4].”
- Deep Learning for Distributed Optimization: Applications to Wireless Resource Management (2019, neutral): “To overcome the drawbacks of traditional optimization techniques, deep learning (DL) frameworks have been recently investigated in wireless resource management [7]–[12] and end-to-end communication system design [13]–[17].”