This webpage describes the main results and the dataset associated to our paper M. Polese, L. Bertizzolo, L. Bonati, A. Gosain, T. Melodia, An Experimental mmWave Channel Model for UAV-to-UAV Communications, in Proc. of ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets), London, UK, Sept. 2020.
Unmanned Aerial Vehicle (UAV) networks can provide a resilient communication infrastructure to enhance terrestrial networks in case of traffic spikes or disaster scenarios. However, to be able to do so, they need to be based on high-bandwidth wireless technologies for both radio access and backhaul. With this respect, the millimeter wave (mmWave) spectrum represents an enticing solution, since it provides large chunks of untapped spectrum that can enable ultra-high data-rates for aerial platforms. Aerial mmWave channels, however, experience characteristics that are significantly different from terrestrial deployments in the same frequency bands. As of today, mmWave aerial channels have not been extensively studied and modeled. Specifically, the combination of UAV micro-mobility (because of imprecisions in the control loop, and external factors including wind) and the highly directional mmWave transmissions require ad hoc models to accurately capture the performance of UAV deployments. To fill this gap,
UAV-to-UAV mmWave Channel Model: dataset and code structure
dataset.csv contains the measured data as processed by Facebook Terragraph sounders.
The MATLAB scripts in the Github repository can be used to load and manipulate the dataset, and to generate the results of the paper.
You can load and save the processed data in a
.mat file using
load_dataset.m. Then, the scripts
fit_6_12_15.m perform the fit on the measurements. Finally,
compare_beam_error_deg.m generate the plots shown in the paper.
The parameters in the
database.csv are defined as follows:
distance: Distance between the UAVs
altitude: Altitude of the UAVs from the ground
link_dir: Direction of transmission, e.g., "1to2" indicates that node 1 is transmitting and node 2 is receiving
rx_beam: Transmitter and receiver beam indices used for scanning
mcs: IEEE 802.11ad Modulation and Coding Scheme (MCS)
rx_mask*: Transmitter and receiver antenna masks. Defines which antenna elements are active. The three hexadecimal numbers in the mask represent the active state of the specific tile (*_mask22, *_mask23, *_mask24), where a 1 in a binary position represents an active and a 0 represents an inactive element. E.g., "0xfff" specifies that all beams are active on the specific tile.
tx_gain_idx: Transmitter gain indices
rx_if_gain_idx: Receiver gains indices from the Automatic Gain Control (AGC) closed-loop feedback regulating circuit in the node amplifier chains
stf_snr: SNR measure based on spatiotemporal filtering (STF)
post_snr: Post-equalization SNR
rssi: Received Signal Strength Indicator (RSSI)
rssi std: RSSI standard deviation
rx temp: Transmitter and receiver nodes junsction temperature
eirp: Effective Radiated Power (EIRP) at the receiver node
pRx: Received power at the receiver node
path_loss: Signal path loss calculated from the difference of EIRP and received power