Abstract

• Motivation​

  • ​Millimeter-wave (mm-Wave) communication achieves
    multi-Gbps rates via highly directional beamforming.

  • Overcomes pathloss and provide the desired SNR
     

• ​Problem

  Obtain the necessary link budget is a high overhead procedure.

  • The search space scales with device mobility

  • The product of the sender-receiver beam resolution

Abstract (cont.)

• Solution - Blind Beam Steering (BBS)

  • Removes in-band overhead for directional mm-Wave communication
     

  • Couples mm-Wave and legacy 2.4/5 GHz bands using
    out-of-band direction inference to establish (overhead-free) communication.
     

  • Estimates retrieved from passively overheard 2.4/5 GHz frames to assure highest mm-Wave link quality

Introduction

• Millimeter-wave (mm-Wave)​

  • Achieve multi-gigabit-per-second performance

  • Extremely high attentuation

    • Uses directional antennas to overcome​

    • Must match the potentially narrow directions of their respective beams

Introduction (cont.)

• IEEE 802.11ad Beamforming Training

Introduction (cont.)

• Blind Beam Steering (BBS)

  • Replaces in-band trial-and-error testing of virtual sector pairs with “blind” out-of-band direction acquisition.

    • ​ Out-of-band direction interference mechanisms

  • Compliant with the IEEE 802.11ad standard.

    • ​Utilizes legacy 2.4/5 GHz bands to estimate the direction

    • The passively overheard frames does not incur any additional protocol overhead.

Introduction (cont.)

• Blind Beam Steering (BBS) (cont.)

  • ​Out-of-band direction interference mechanisms

    • Lists received signal energy over azimuthal receive spectrum

    • A history of these direction estimates is maintained for every potential pairing device in the network.

  • Multi-path and noise effects

    • Evaluates the ratio of multi-path reflections observed in the out-of-band direction information

    • Aggregates the direction estimates retrieved from frames under small scale mobility

IEEE 802.11ad and mm-Wave WiFi

• Establishment of Directional Links

  • i.e., beamforming (BF) training

  • Two stages of BF training in IEEE 802.11ad

    • Sector Level Sweep (SLS)

      • ​Replaced by utilizing out-of-band direction information

    • Beam Refinement Process/Protocol (BRP)

      • ​Complementary procedure to BBS

Node and System Architecture

• Node Architecture

  • Multi-band capable device design

    • Application Band - mm-Wave

    • Detection Band - IEEE 802.11ac/n
       

  • Final sector refinement

    • When the direction inference is not accurate enough

    • ​A low number of detection band antennas increases the search space.

Node and System Architecture (cont.)

• System Architecture

  • Background Process

    • ​Infers other devices' direction by passively overhearing detection band frames

    • Without further overhead and does not require any changes to the detection band protocol

  • ​BBS requires the received signal strength in relation to the azimuth incidence angle    .

    • Angular profile - 

    • Ensure robustness to perform reliable sector selection

Step 1. Out-of-Band Sector Inference

• Passively overheard detection band frames to calculate       

• Organized in a history for every overheard device

• Symbols

  •         - Angular profile obtained from a frame overheard at time

  •         - The node id for the device that transmitted the frame

  •         - History of every pair of profiles

Step 2. Profile History Aggregation

• The history holds two conditions.

  • An unblocked LOS path is reflected in every profile by a peak at the same angle.

  • Peaks resulting from reflections vary among profiles.

• The aggregated angle profile
  
  
  ​

  • Alternating reflections peaks are flattened.

  • The noise and multi-path affected frames slightly deviate the direct path angle.

Step 3. Line-Of Sight Inference

• Two major obstacles

  • Extreme signal attenuation from direct path blockage

  • Multi-path induce destructive interference to the direct path.

• Peak to Average Ratio
  
  
   

  • ​A reflection-less direct path results in a sharp peak.

  • If                     , do the legacy IEEE 802.11ad beam training.

3. Line-Of Sight Inference (cont.)

Fig.: Angular profile peak to average ratio.

Step 4. Sector Mapping

• Relates a direct path estimate from the direction band to the application band

• The strongest signal peak's azimuthal angle
  
   

  • ​A mapping is a straight forward geometrical matching.

  • Geometrically matching can be done separately if the transmit and receive antenna geometry differ.

Step 5. Optional Sector Refinement

• The strongest peak      can slightly deviate from the direct path to the target node due to remaining noise and multi-path effect.

• The width of the strongest peak
  
  
   

  • Choosing a low         

    • Extends the angular region around     

    • Increase the chance for the direct path to lie within it

Step 5. Optional Sector Refinement (cont.)

• The width of the strongest peak
  
  
   

  • If                       , additional in-band refinement is triggered to find the optimum sector in the indicated set.

    • A stand alone BRP phase is carried out.

BBS Prototype

• Detection Band

  • FPGA-based SDR platform WARP at 2.4 GHz

    • 2 WARP boards

    • 8 transceiver chains

  • WARPLab

  • MUSIC algorithm

    • ​Out-of-band sector inference

Fig.: BBS experimental platform

BBS Prototype (cont.)

• Application Band

  • Vubiq 60 GHz waveguide development system

  • Agilent E4432B signal generator

  • Tektronix TDS7054 oscilloscope

  • 3 horn antennas

    • bandwidth: 7, 20, 80 degree

  • 1 omni-directional antenna

Fig.: BBS experimental platform

BBS Prototype (cont.)

Fig.: Measurement setup.

Tranceivers
(1 - 1.5m height)

Indoor setting

Receiver

Direct Path Detection Accuracy

Fig.: Detection accuracy of direct path for 8 to 4 detection antennas in 7 evaluated locations.

• The number of detection band antennas shows no significant impact on direct path estimation accuracy except for a 4 antenna detection band configuration.

Robustness

• Detection of Severe Multi-path

Fig.: Peak to average ratio of aggregated profiles in relation to accuracy.

• A threshold based decision strategy can successfully detect among multi-path and prevent erroneous mapping with a success rate of 94%.

Robustness (cont.)

• Detection of Blocked LOS Path

Training Overhead

• Achieves perfect sector selection with only 0 to 13% remaining in-band training.

Fig.: Overhead: remaining sectors for in-band refinement with optimal sector selection for                 

Time of Directional Link Establishment

Related Work

• Multi-band Systems
  • [1] Uses multiple interfaces on battery operated devices to save energy
  • [2] Protocols for opportunistic usage of multi-band spectrum
• Direction Inference
  • [3] MUSIC algorithm
  • [4][5][6] Utilizes for out-of-band detection inference primarily evolved from MUSIC
• 60 GHz Beamforming Overhead
  • [7] Consider as optimization of a 2-D signal strength function defined over finite codebooks.

Conclusion

• Blind Beam Steering (BBS)
  • Addresses the overhead problem for directional mm-Wave link establishment
     
  • Couples 60 GHz mm-Wave with legacy 2.4/5 GHz bands to exploit propagation properties of each
     
  • Detection Band and Application Band

Related Work

1. E. Shih, P. Bahl, and M. J. Sinclair, “Wake on Wireless: An Event Driven Energy Saving Strategy for Battery Operated Devices,” in Proc. ACM  MobiCom, 2002.

2. A. Sabharwal, A. Khoshnevis, and E. W. Knightly, “Opportunistic spectral usage: Bounds and a multi-band CSMA/CA protocol,” IEEE/ACM Transactions on Networking, 2007.

3. R. O. Schmidt, “Multiple Emitter Location and Signal Parameter Estimation,” IEEE Transactions on Antennas and Propagation, 1986.

4. J. Xiong and K. Jamieson, “ArrayTrack: A Fine-grained Indoor Location System,” in Proc. NSDI, 2013.

5. J. Xiong and K. Jamieson, “Towards Fine-grained Radio-based Indoor Location,” in Proc. ACM HotMobile, 2012.

6. J. Gjengset, J. Xiong, G. McPhillips, and K. Jamieson, “Phaser: Enabling Phased Array Signal Processing on Commodity WiFi Access Points,” in Proc. ACM Mobicom, 2014.

7. B. Li, Z. Zhou, H. Zhang, and A. Nallanathan, “Efficient Beamforming Training for 60-GHz Millimeter-Wave Communications: A Novel Numerical Optimization Framework,” IEEE Transactions on Vehicular Technology, 2014.