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MillimeterWave UAV Communications and Channel Modeling Monisha Ghosh ([email protected] ), Ismail Guvenc ([email protected]), Nadisanka Rupasinghe ([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 Mobilitybased 3D Beamforming and Equalization Techniques for mmWave UAV Networks (20172019) Multi Access and Multi Hop mmWave UAV Communication Methods with UAV Mobility (20162018) mmWave Communications and Channel Sounding Testbed (channel sounding experiments and models in 2017, multihop experiments and results in 20182019) Capacity results in Globecom 2016 Applications mmWave Beamforming with Leakage Minimization Reconnecting Disconnected Backhaul Network Equalization Investigate tradeoff between (i) singlecarrier mmWave with Decision Feedback Equalization (DFE) and (ii) singlecarrier mmWave with Linear Equalizers for the mmWave UAV scenario. Past results with simulated and real mmWave outdoor channels indicate significant performance gains from the use of DFEs. We will investigate gains in the mmWave UAV channel. Multiple Access for mmWave Investigate timedomain, frequency domain and codedomain 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 chipset 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 chipset manufacturers). The chipset 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 ultrawideban d kits to mmWave bands Upconverting lightweight USRPs to mmWave bands Other solutions: Pasternack, SpaceK Labs, Virginia Diodes, other? UAV Leakage minimization UE Internet Gateway Disconnected small cell UAV (maintains backhaul connectivity) UE Sum Capacity Over UAV Network U AV Mo b ility Based Approach Fixed U AV h eig h ts Ran d o m U AV h eig h ts Or thogonal spr eading codes within beam s and acr oss cluster s Or thogonal codes in differ ent beam s m inim ize inter fer ence at edges, or canbe com bined 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 3D 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 mmWave communication 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).

RCN mmWave Poster (Monisha, Guvenc) v4 · 3D spatial resources via narrow mmWave beams. • In one approach, we assume user locations are known; then we only need channel state information

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Page 1: RCN mmWave Poster (Monisha, Guvenc) v4 · 3D spatial resources via narrow mmWave beams. • In one approach, we assume user locations are known; then we only need channel state information

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).