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Millimeter-Wave UAV Communications and Channel Modeling
Monisha Ghosh ([email protected]), Ismail Guvenc ([email protected]), NadisankaRupasinghe ([email protected]) and Ahmed S. Ibrahim ([email protected])
Motivation
• Unmanned aerial vehicles (UAVs) can be used as aerial base stations (BSs) to deliver broadband wireless connectivity during, for example, temporary events or after disasters.
• mmWave communications allows high throughput delivery in hot spot scenarios.• mmWave communication, networking, and channel propagation characteristics have not been studied in the context of UAVs, which constitute the main scope of this project.
Preliminary Results on Sum Capacity (GLOBECOM 2016)
Research Goals
• Mobility-based 3D Beamforming and Equalization Techniques for mmWave UAV Networks (2017-2019)
• Multi-‐Access and Multi-‐Hop mmWave UAV Communication Methods with UAV Mobility (2016-2018)
• mmWave Communications and Channel Sounding Testbed (channel sounding experiments and models in 2017, multi-hop experiments and results in 2018-2019)
• Capacity results in Globecom 2016
Applications
mmWave Beamforming with Leakage Minimization
Reconnecting Disconnected Backhaul Network
Equalization
• Investigate trade-off between (i) single-carrier mmWave with Decision Feedback Equalization (DFE) and (ii) single-carrier mmWave with Linear Equalizers for the mmWave UAV scenario.
• Past results with simulated and real mmWaveoutdoor channels indicate significant performance gains from the use of DFEs. We will investigate gains in the mmWave UAV channel.
Multiple Access for mmWave
• Investigate time-domain, frequency domain and code-domain multiple access schemes.
• Beamforming will reduce the frequency diversity due to multipath, hence OFDMA may not be the desired multiple access option.
• With fewer users in a beam, and reduced frequency selectivity, CDMA becomes an attractive option.
Low Cost Channel Sounding Approaches using 802.11ad chipsets
• Since the mmW receiver computes the channel estimates prior to equalization, one could potentially use the values computed by the chip itself. The problem however is that most manufacturers do not make these available as an output in production chips: they are available for internal use only during debugging. (Requires cooperation of chip-set manufacturers).
• There is an optional mode specified in the standard whereby the receiver transmits the channel it just estimated to the transmitter. However, since this is an optional mode, it is not implemented, yet. If this were to be implemented in future versions, the channel estimates could be retrieved without the need to access he chip internals. (Requires cooperation of chip-set manufacturers).
• The chip-set can be used as a transmitter only and the preamble and channel estimation can be implemented on a FPGA. This would require an implementation effort in both the RF and digital processing, but there is additional flexibility by doing so instead of relying on the algorithms in the chip. For example, the accuracy of the estimate can be improved by averaging over longer periods. (Fairly intensive FPGA development effort).
Other Channel Sounding Possibilities
• Upconverting lightweight ultrawideband kits to mmWave bands
• Upconverting lightweight USRPs to mmWave bands
• Other solutions: Pasternack, SpaceKLabs, Virginia Diodes, other?
UAV Leakage minimization
UE
InternetGateway
Disconnected
small
cell
UAV (maintains backhaul connectivity)
UE
Sum Capacity Over UAV Network
UAV MobilityBased Approach
Fixed UAV
heights
Random UAV
heights
Orthogonal spreading codes within beams and across clusters
Orthogonal codes in different beams minimize interference at edges, or can be combined
UWB P410 (Time Domain Corp.)
USRPs (National Inst.)
Vubiq(Pasternack)
• We are investigating reconnecting a disconnected backhaul network using a limited number of UAVs acting as flying relays among the small cells.
• We aim to utilize the flexibility of 3-D movement of the UAVs and guide them to optimal locations, which can maximize the connectivity of the overall network (consisting of fixed small cells and flying UAVs.)
• We consider a mobility based mmWavecommunication network that can densely reuse 3D spatial resources via narrow mmWave beams.
• In one approach, we assume user locations are known; then we only need channel state information from desired user, and we can still minimize interference leakage to other users (no global CSIT is needed).
• With UAV location optimization, this is shown to perform better than random UAV locations with zero-forcing beamforming (which requires global CSIT).