Compressive MIMO Beamforming of Data Collected in a Refractive Environment. Issue 12 (4th December 2017) - Wagner, Mark; Nannuru, Santosh; Gerstoft, Peter
Abstract: The phenomenon of ducting is caused by abnormal atmospheric refractivity patterns and is known to allow electromagnetic waves to propagate over the horizon with unusually low propagation loss. It is unknown what effect ducting has on multiple input multiple output (MIMO) channels, particularly its effect on multipath propagation in MIMO channels. A high‐accuracy angle‐of‐arrival and angle‐of‐departure estimation technique for MIMO communications, which we will refer to as compressive MIMO beamforming, was tested on simulated data then applied to experimental data taken from an over the horizon MIMO test bed located in a known ducting hot spot in Southern California. The multipath channel was estimated from the receiver data recorded over a period of 18 days, and an analysis was performed on the recorded data. The goal is to observe the evolution of the MIMO multipath channel as atmospheric ducts form and dissipate to gain some understanding of the behavior of channels in a refractive environment. This work is motivated by the idea that some multipath characteristics of MIMO channels within atmospheric ducts could yield important information about the duct. Plain Language Summary: Long‐range ship to ship wireless communication is difficult because the horizon can obstruct the line of sight path between ships, causing radio signal strength to decrease rapidly with range. Sometimes, however, an event known as ducting can occur which allows radio waves to curve over the horizon. Multiple input multiple output (MIMO) radio setups can exploit knowledge of the paths taken by the signal from transmitter to receiver to increase communication strength. In this paper we take measurements from a MIMO radio setup located in a region known for ducting and observe the evolution of the signal paths, looking for patterns that may be used to predict properties of atmospheric ducts. Key Points: Compressive sensing can be used for efficient beamforming of MIMO channels Atmospheric refractivity can influence the shape of a MIMO channel MIMo channels evolve in tandem with atmospheric refractivity