Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/143814
Title: | Integration of visible light communication and positioning within 5G networks for Internet of Things | Authors: | Yang, Helin Zhong, Wen-De Chen, Chen Alphones, Arokiaswami |
Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2020 | Source: | Yang, H., Zhong, W.-D., Chen, C., & Alphones, A. (2020). Integration of visible light communication and positioning within 5G networks for Internet of Things. IEEE Network, 34(5), 134-140. doi:10.1109/mnet.011.1900567 | Journal: | IEEE Network | Abstract: | With the widespread deployment of Internet of Things (IoT), more and more devices are involved in wireless networks, and the fifth generation (5G) network requires to support the massive connectivity and diverse services for the huge number of IoT devices. Visible light communications (VLC) and visible light positioning (VLP) are two promising supplementary technologies to assist 5G networks to support the massive connectivity, high reliability, high data rate, high positioning accuracy, low latency, low power consumption and improved security of IoT. Hence, this article presents a multi-layer network architecture by integrating VLC and VLP within 5G networks, in order to support the above mentioned diverse requirements of IoT devices. In the multi-layer network, the macrocell and picocell layers support better coverage and reliability via the radio frequency (RF) spectrum, while the optical attocell layer provides the high-speed transmission and high-accuracy positioning services operating at the visible light spectrum. We then briefly describe some key technologies for the performance improvement of the multi-layer network, including energy harvesting, modulation and multiple access schemes. An exemplary case study and simulation analysis are provided to demonstrate the advantage and significance of the presented multi-layer network for IoT. Finally, we point out some future research directions. | URI: | https://hdl.handle.net/10356/143814 | ISSN: | 0890-8044 | DOI: | 10.1109/MNET.011.1900567 | Rights: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/MNET.011.1900567 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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