Creating and sharing knowledge for telecommunications

Experimental Analysis of the Impact of Indoor Turbulence on FSO for Intra-Datacenter Communications

Nascimento, J. ; Fernandes, M. ; Guiomar, F. P. ; Monteiro, P.

Experimental Analysis of the Impact of Indoor Turbulence on FSO for Intra-Datacenter Communications, Proc Conference on Telecommunications - ConfTele, Leiria, Portugal, Vol. , pp. - , February, 2021.

Digital Object Identifier:

Download Full text PDF ( 2 MBs)


With datacenters expanding their networks at a greater than ever rate, efficiently managing an extremely numerous a network of servers with high cabling complexity is a daunting task. This has motivated the rise of free-space
optics (FSO) communication technologies, as a reliable new solution for high-capacity communication systems, which grants a possibility for the implementation of cable-free intra-datacenter communications as a way to reduce the level of network complexity. However, as the scientific community continuously explores FSO distinctive characteristics of unregulated large-bandwidth spectrum, to easily establish new communication links, atmospheric conditions threaten its commercial deployment. As such, the effects of atmospheric turbulence on FSO links have been under investigation by researchers from all over the world, leading to the proposal of several models in an attempt to predict and therefore mitigate the effects of adverse conditions. This study seeks to capture and analyze experimental data on the
influence of turbulence on the received optical power of a FSO link in a controlled room, to simulate a datacenter environment, followed by the modeling of experimental data using the LogNormal model. Using a small 2000 RPM Fan in three different positions we increased the atmospheric turbulence of the FSO channel and measured the differences in received optical power
over the course of 1 hour per position. These measurements are then compared to a control obtained without externally induced turbulence. Using the obtained data, we demonstrate its LogNormal fit, thus enabling to determine the Rytov variance for each scenario.