Argos: Practical Base Stations for Large-scale Argos Interconnect Argos Interconnect Argos Interconnect

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  • Argos: Practical Base Stations for Large-scale Beamforming

    Clayton W. Shepard

  • Collaborators

    Hang Yu

    Erran Li

    Richard Yang

    Narendra Anand

    Thomas Marzetta

    Lin Zhong

    2

  • Background

    • Beamforming

    – Power Gain

    – Adjust phase (“beamweights”)

    – Leverages Interference

    • Open-loop

    – Pre-compute weights to specify direction

    • Closed-loop (adaptive)

    – Use channel state information (CSI) to target receivers

    3

    =

    =

  • Background

    • Single-user beamforming (SUBF)

    • Multi-user beamforming (MUBF)

    4

    *HcWSUBF 

    1** )(  HHHcW TMUBF

  • BS

    The CSI is then calculated at the terminal and sent back to the BS A pilot is sent from each BS antenna

    Background: Channel Estimation

    5

    +

    + =

    Align the phases at the receiver to ensure constructive interference

    For uplink, send a pilot from the terminal then calculate CSI at BS (Channels are not reciprocal)

    Path Effects (Walls)

    Tx

    Rx

    Tx

    Rx

    Tx

    Rx

    Uplink? Due to environment and terminal mobility estimation has to occur quickly and periodically

    Tx

    Rx

  • MUBF linear pre-coding: downlink

    6

    … …

    M

    K

    K

    K

    K

  • MUBF linear pre-coding: uplink

    7

    M

    K

    K

    K

    K

  • 8

    … …

    Our vision

  • Prior Work • Large-scale beamforming theory

    – T.L. Marzetta. Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications, Nov. 2010.

    – Fredrik Rusek and Daniel Persson and Buon Kiong Lau and Erik G. Larsson and Thomas L. Marzetta and Ove Edfors and Fredrik Tufvesson Scaling up MIMO: Opportunities and Challenges with Very Large Arrays. arXiv, Jan. 2012.

    • Real-world beamforming – E. Aryafar, N. Anand, T. Salonidis, and E. Knightly. Design and

    Experimental Evaluation of Multi-userBeamforming in Wireless LANs. In Proceedings of MobiCom, 2010

    • Reciprocal calibration – F. Kaltenberger, H. Jiang, M. Guillaud, R. Knopp. Relative channel

    reciprocity calibration in MIMO/TDD systems. Future Network and Mobile Summit, June 2010. 9

  • First large-scale beamforming base station

    10

  • 11

  • 12

  • Overview of contributions

    • Scalable architecture

    • Internal reciprocity calibration

    • Novel fully distributed beamforming method

    13

  • 14

    Can beamforming scale with the number of base station antennas?

  • Not with current techniques!

    • CSI acquisition – Typically requires # of base station (BS) antennas (M)

    + # of terminals (K) pilots

    • Weight calculation – All existing methods have centralized data

    dependency

    – Requires M*K channel estimates and produces M*K weight values

    • Linear pre-coding – Produces M data streams

    15

  • With careful design and new techniques it can!

    • CSI Acquisition

    – Leverage TDD reciprocity to limit pilots to K

    – Requires calibration

    • Weight Calculation

    – Novel decentralized weight calculation

    • Linear Pre-coding

    – Apply weights at radio

    – For uplink combine streams any time they meet

    16

  • Scalable linear pre-coding

    17

    … …

    M

    K

    K

    K

    K

    Common Databus!

  • MUBF linear pre-coding: uplink

    18

    M

    K

    K

    K

    K

  • Scalable linear pre-coding

    19

    M

    K

    K

    K

    K

    Constant Bandwidth!

  • Ramifications

    • CSI and weights are computed and applied (linear pre-coding) locally at each BS radio – No overhead for additional BS radios

    • No central data dependency – No latency from data transport

    – No stringent latency requirements

    – Constant data rate common bus (no switching!)

    • Unlimited scalability!

    20

  • • Scalable

    – Support thousands of BS antennas

    • Cost-effective

    – Cost scales linearly with # of antennas

    • Reliable

    21

    ???

    Design goals

  • How do we design it?

    • Daisy-chain (series) – Unreliable – Large end to end latency

    • Token-ring / Interconnected – Not amenable to linear pre-coding – Variable Latency – Routing overhead

    22

    • Flat structure – Un-scalable – Expensive, with large fixed cost

  • Solution: Argos

    • Modular

    – Daisy-chainable

    – 1 or more radios

    • Hierarchal

    – Increases Reliability

    – Constrains Latency

    – Cost-effective

    23

    Central Controller

    Argos Hub

    Argos Hub

    Argos Hub

    Module Module Module

    Module

    Module

    Data Backhaul

    Module Radio Radio Radio…

  • Scalability of Argos

    • Scalable in 4 directions: – # of Radios per Module – # of Modules per Chain – # of ports per Hub – # of Hubs (and levels)

    • Reliable – Branches can fail without affecting other branches – Central hubs can be easily made redundant

    • Accommodates linear pre-coding – Add samples together at every junction

    24

  • Implementation

    25

    Argos Interconnect Argos

    Interconnect Argos

    Interconnect

    Central Controller (Host PC w/Matlab)

    WARP Module FPGA

    (controlled by XPS)

    Power PC (C code Target)

    FPGA Fabric

    Hardware Model (SimuLink)

    Peripherals and Other I/O

    Clock Board

    Daughter Cards

    Radio 4

    Radio 3

    Radio 2

    Radio 1

    WARP Module FPGA

    (controlled by XPS)

    Power PC (C code Target)

    FPGA Fabric

    Hardware Model (SimuLink)

    Peripherals and Other I/O

    Clock Board

    Daughter Cards

    Radio 4

    Radio 3

    Radio 2

    Radio 1

    WARP Module FPGA

    (controlled by XPS)

    Power PC (C code Target)

    FPGA Fabric

    Hardware Model (SimuLink)

    Peripherals and Other I/O

    Clock Board

    Daughter Cards

    Radio 4

    Radio 3

    Radio 2

    Radio 1

    WARP Module FPGA

    (controlled by XPS)

    Power PC (C code Target)

    FPGA Fabric

    Hardware Model (SimuLink)

    Peripherals and Other I/O

    Clock Board

    Daughter Cards

    Radio 4

    Radio 3

    Radio 2

    Radio 1

    16

    Argos Hub

    Sync Pulse (WARP Board)

    Data Switch (Ethernet)

    Clock Distribution

    (AD9523)

    Argos Interconnect

    Et h

    e rn

    e t

  • WARP Modules

    Central Controller

    Argos Hub

    Clock Distribution

    Ethernet Switch

    Sync Distribution

    Argos Interconnects

    26

  • Overview of contributions

    • Scalable architecture

    • Internal reciprocity calibration

    • Novel fully distributed beamforming method

    27

  • Channel reciprocity

    txi

    rxi

    rxj

    txj

    c

    Transciever i

    Transciever j

    Wireless Channel

    ijij rxctxh 

    jiji rxctxh 

    ijh 

    jih

    28

  • Calibration coefficients

    • Given the complete channel:

    • We define a calibration coefficient as:

    • Thus:

    ij

    ji

    ji h

    h A

     

    jiji rxctxh 

    ijjiji hAh  

    i

    j

    ji A

    A A

      1

    1 and

    29

    ijij

    ji

    Arxtx

    rxtx

     

     

    1

    ij

    ji

    rxctx

    rxctx

    

     

  • Applying to large-scale BS

    • Find A between each BS antenna and a reference antenna (1)

    • Every BS radio listens to terminal pilot

    • Find A between reference and terminal

    • We can derive

    • Now every h can be found via

    tA1

    mA 1

    mttmtm hAh  

    m

    t tm

    A

    A A

      

    1

    1

    mth 

    30

  • Key observation

    • But this requires K+1 pilots… – Even worse, it requires feedback

    • A constant phase shift across the entire array does not alt