To integrate unmanned aerial vehicles (UAVs) in future large-scale deployments, a new wireless communication paradigm, namely, the cellular-connected UAV has recently attracted interest. However, the line-of-sight dominant air-to-ground channels along with the antenna pattern of the cellular ground base stations (GBSs) introduce critical interference issues in cellular-connected UAV communications. In particular, the complex antenna pattern and the ground reflection (GR) from the down-tilted antennas create both coverage holes and patchy coverage for the UAVs in the sky, which leads to unreliable connectivity from the underlying cellular network. To overcome these challenges, in this paper, we propose a new cellular architecture that employs an extra set of co-channel antennas oriented towards the sky to support UAVs on top of the existing down-tilted antennas for ground user equipment (GUE). To model the GR stemming from the down-tilted antennas, we propose a path-loss model, which takes both antenna radiation pattern and configuration into account. Next, we formulate an optimization problem to maximize the minimum signal-to-interference ratio (SIR) of the UAVs by tuning the up-tilt (UT) angles of the up-tilted antennas. Since this is an NP-hard problem, we propose a genetic algorithm (GA) based heuristic method to optimize the UT angles of these antennas. After obtaining the optimal UT angles, we integrate the 3GPP Release-10 specified enhanced inter-cell interference coordination (eICIC) to reduce the interference stemming from the down-tilted antennas. Our simulation results based on the hexagonal cell layout show that the proposed interference mitigation method can ensure higher minimum SIRs for the UAVs over baseline methods while creating minimal impact on the SIR of GUEs.
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Optimal deployments of UAVs with directional antennas for a power-efficient coverage
To provide a reliable wireless uplink for users in a given ground area, one can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another application, one can use UAVs to collect data from sensors on the ground. For a power efficient and scalable deployment of such flying BSs, directional antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We consider a large-scale wireless path-loss model with a realistic angle-dependent radiation pattern for the directional antennas. Based on such a model, we determine the optimal 3-D deployment of N UAVs to minimize the average transmit-power consumption of the users in a given target area. The users are assumed to have identical transmitters with ideal omnidirectional antennas and the UAVs have identical directional antennas with given half-power beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For uniformly distributed ground users, we show that the UAVs have to share a common flight height in an optimal power-efficient deployment, by simulations. We also derive in closed-form the asymptotic optimal common flight height of N UAVs in terms of the area size, data-rate, bandwidth, HPBW, and path-loss exponent.
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- Award ID(s):
- 1815339
- NSF-PAR ID:
- 10167869
- Date Published:
- Journal Name:
- IEEE Transactions on Communications
- ISSN:
- 0090-6778
- Page Range / eLocation ID:
- 1 to 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Data files were used in support of the research paper titled "“Experimentation Framework for Wireless
Communication Systems under Jamming Scenarios" which has been submitted to the IET Cyber-Physical Systems: Theory & Applications journal.Authors: Marko Jacovic, Michael J. Liston, Vasil Pano, Geoffrey Mainland, Kapil R. Dandekar
Contact: krd26@drexel.edu---------------------------------------------------------------------------------------------
Top-level directories correspond to the case studies discussed in the paper. Each includes the sub-directories: logs, parsers, rayTracingEmulation, results.
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logs: - data logs collected from devices under test
- 'defenseInfrastucture' contains console output from a WARP 802.11 reference design network. Filename structure follows '*x*dB_*y*.txt' in which *x* is the reactive jamming power level and *y* is the jaming duration in samples (100k samples = 1 ms). 'noJammer.txt' does not include the jammer and is a base-line case. 'outMedian.txt' contains the median statistics for log files collected prior to the inclusion of the calculation in the processing script.
- 'uavCommunication' contains MGEN logs at each receiver for cases using omni-directional and RALA antennas with a 10 dB constant jammer and without the jammer. Omni-directional folder contains multiple repeated experiments to provide reliable results during each calculation window. RALA directories use s*N* folders in which *N* represents each antenna state.
- 'vehicularTechnologies' contains MGEN logs at the car receiver for different scenarios. 'rxNj_5rep.drc' does not consider jammers present, 'rx33J_5rep.drc' introduces the periodic jammer, in 'rx33jSched_5rep.drc' the device under test uses time scheduling around the periodic jammer, in 'rx33JSchedRandom_5rep.drc' the same modified time schedule is used with a random jammer.--------------------------------
parsers: - scripts used to collect or process the log files used in the study
- 'defenseInfrastructure' contains the 'xputFiveNodes.py' script which is used to control and log the throughput of a 5-node WARP 802.11 reference design network. Log files are manually inspected to generate results (end of log file provides a summary).
- 'uavCommunication' contains a 'readMe.txt' file which describes the parsing of the MGEN logs using TRPR. TRPR must be installed to run the scripts and directory locations must be updated.
- 'vehicularTechnologies' contains the 'mgenParser.py' script and supporting 'bfb.json' configuration file which also require TRPR to be installed and directories to be updated.--------------------------------
rayTracingEmulation: - 'wirelessInsiteImages': images of model used in Wireless Insite
- 'channelSummary.pdf': summary of channel statistics from ray-tracing study
- 'rawScenario': scenario files resulting from code base directly from ray-tracing output based on configuration defined by '*WI.json' file
- 'processedScenario': pre-processed scenario file to be used by DYSE channel emulator based on configuration defined by '*DYSE.json' file, applies fixed attenuation measured externally by spectrum analyzer and additional transmit power per node if desired
- DYSE scenario file format: time stamp (milli seconds), receiver ID, transmitter ID, main path gain (dB), main path phase (radians), main path delay (micro seconds), Doppler shift (Hz), multipath 1 gain (dB), multipath 1 phase (radians), multipath 1 delay relative to main path delay (micro seconds), multipath 2 gain (dB), multipath 2 phase (radians), multipath 2 delay relative to main path delay (micro seconds)
- 'nodeMapping.txt': mapping of Wireless Insite transceivers to DYSE channel emulator physical connections required
- 'uavCommunication' directory additionally includes 'antennaPattern' which contains the RALA pattern data for the omni-directional mode ('omni.csv') and directional state ('90.csv')--------------------------------
results: - contains performance results used in paper based on parsing of aforementioned log files
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TCOMM.2020.2992521
