Massive MIMO a overview - •Introduction •Ways to Achieve higher spectral efficiency •Massive MIMO basics •Challenges and expectations from Massive MIMO

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  • Massive MIMO a overview



  • Outline


    Ways to Achieve higher spectral efficiency

    Massive MIMO basics

    Challenges and expectations from Massive MIMO

    Network MIMO features


  • Wireless traffic growth

    Growth in Wireless Traffic

    One Million times in last 45 years

    Martin Coopers law

    The number of simultaneous voice/data connections has

    doubled every 2.5 years (+32% per year) since the

    beginning of wireless

    Src: Martin Cooper

  • Spectrum and Limitations

    Radio spectrum is a very scarce resource Limited availability for cellular communications

    Spectral efficiency needs to be improved

    Spectral efficiency of point-to-point transmission Shannons capacity limit

    2 1 +

    Cannot do much: 4 bps/Hz -> 8 bps/Hz costs 17 times more power

  • Spectral Efficiency

    Frequency reuse Dense deployments using smaller cells

    Inter-cell interference Diminishing returns with increase in number of smaller cells

    MIMO Capacity increasing linearly with factor of min{Nt, Nr} SM for SU-MIMO

    Limited by number of antennas at the user in cellular frequency

    SDMA for MU-MIMO Larger number of antennas from distributed user terminals

  • Conventional MU-MIMO

    Performance depends on scheduler and link adaptation CSI feedback from UE report (FDD mode) Precoder design using uplink channel (Reciprocity principle for TDD)

  • MU-MIMO in LTE


    MU-MIMO (TM5)

    Dual layer DMRS based SM (TM8)

    8 layer DMRS based SM (TM9)

    Code book based scheme Maximum 2 user pairing Single layer transmission

    to each UE

    Non Code book based scheme Adaptive SU/MU MIMO More user pairing Higher rank transmission to each UE

  • FD-MIMO in LTE Release 13

    Vertical sectorization Creation of vertical sectors Just like having multiple sectors in the horizontal direction

    Beam formed CSIRS based scheme Virtual sectorization using beam selection

    Kronecker based precoding Vertical and horizontal precoder reporting from UE Forming the final precoder using KP

    SRS based scheme (TDD) Precoder selection using uplink channel Reciprocity property

  • Massive MIMO

    Hundreds of BS antennas

    Tens of active users

    Higher order improved MU-MIMO

    MU-MIMO Scheduler challenges User pairing algorithm MU-CQI prediction assuming co-user interference

  • Active Antenna Array (AAS)

    Antenna element

    Sub array TXRU model Full connection TXRU model

    Antenna element

    AAS Structure

    Src : TR 36.897

  • Massive MIMO deployment

    Linear Rectangular array Cylindrical

  • Virtual sectorization

    Conventional beamforming in horizontal direction

    3D beamforming for single UE

    3D beamforming for multiple UEs

  • Beamforming using user location

    Active Antenna System (AAS)

    Base station

    Virtual beamforming

    Horizontal beamforming

    Elevation beamforming

  • Challenges of Massive MIMO

    UE specific beamforming

    Cell wide coverage for broadcast/control channels

    To achieve cell wide coverage for broadcast /control channels Narrow beam for data channels CQI estimation for the UE specific beam

  • Further challenges

    Feedback and codebook design in FDD How to reduce the feedback overhead? How FDD reciprocity can be used?

    Uplink sounding in TDD How to accurately estimate a large number of channels? Channel estimation complexity

    Precoding, Scheduling & Link adaptation CQI prediction and scheduling Beam identification

    With and without UE location information

    Antenna grouping

    High mobility scenarios Channel ageing effects Need for better diversity scheme

    Pilot contamination It limits MU-MIMO performance Coordination between BSs is needed

  • Network MIMO

    Backhaul network

    Coordinated transmission from multiple base stations a.k.a. CoMP Fast backhaul is a challenge Improves area spectral efficiency, system capacity

  • Summary

    Massive/ FD MIMO is a promising technology to significantly improve cellular capacity

    Pilot design, Channel estimation, Precoder estimation are the main challenges

    Wider coverage for control and broadcast channels using larger MIMO

    Design of better Diversity schemes for high mobility and low SINR users

  • Thank you