Unmanned Aerial Vehicles (UAVs) often lack the size, weight, and power to support large antenna arrays or a large number of radio chains. Despite such limitations, emerging applications that require the use of swarms, where UAVs form a pattern and coordinate towards a common goal, must have the capability to transmit in any direction in three-dimensional (3D) space from moment to moment. In this work, we design a measurement study to evaluate the role of antenna polarization diversity on UAV systems communicating in arbitrary 3D space. To do so, we construct flight patterns where one transmitting UAV is hovering at a high altitude (80 m) and a receiving UAV hovers at 114 different positions that span 3D space at a radial distance of approximately 20 m along equally-spaced elevation and azimuth angles. To understand the role of diverse antenna polarizations, both UAVs have a horizontally-mounted antenna and a vertically-mounted antenna---each attached to a dedicated radio chain---creating four wireless channels. Using the data from this channel-sounding experiment we are able to estimate the air-to-air (A2A) channel and build a model of the channel for arbitrary azimuth and elevation angles. We use this model to analyze the effect antenna orientation and UAV relative position have on channel magnitude. First, we quantify the different ways in which the UAV body can alter the radiation pattern of a dipole antenna depending on whether the antenna is perpendicular or parallel to the body of the UAV. Then, we analyze the effect the change in the radiation pattern has on the cross-polarization discrimination (XPD). Finally, we calculate the overlapping index, a distance measure, between the distribution of channel magnitude in two symmetric regions of 3D space and observe that the two distributions are further apart when the receiver (Rx) is below the transmitter (Tx), suggesting an asymmetry in the way the Tx and Rx UAV body affect the channel. To demonstrate the impact these effects could have on communication systems, we compute the average throughput at each location based on the channel estimates, show how to optimally select an antenna orientation, and quantify the gains in such selections.

Degree Date

Summer 2022

Document Type


Degree Name



Electrical and Computer Engineering


Joseph Camp

Second Advisor

Dinesh Rajan



Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License