Topic: Massive MIMO - MOOC@ .Topic: Massive MIMO Prof. Dr. Wolfgang Utschick Technische Universit¤t

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  • Topic: Massive MIMO

    Prof. Dr. Wolfgang Utschick

    Technische Universitt Mnchen

    MOOC @ TU9

    Week 3

    Digital Engineering: From Advanced Physical Layer

    Technologies in 5G to Secure Services

    Mon 03 Nov 2014

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Todays Agenda

    Wireless communications suffers from attenuation and

    interference

    Multiple antenna systems (MIMO) are a well-known

    solution against

    Massive MIMO promises additional advantages over

    standard solutions

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 2

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Physical Wireless Communication Link: SISO

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 3

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Physical Wireless Communication Link: SISO

    sig

    nal

    str

    en

    gth

    -80dB

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 3

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    MISO

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 4

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    MISO

    x1

    h1

    x2h2

    x3h3

    x4 h4

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 4

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    MISO

    x1

    h1

    x2h2

    x3h3

    x4 h4

    Transmission Model (baseband representation)

    y =

    4

    m=1

    hmxm + n = hTx+ n, hm C

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 4

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Beamforming

    x1w1

    h1

    x2w2

    h2

    x3w3

    h3

    x4w4

    h4

    s

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 5

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Beamforming

    x1w1

    x2w2

    x3w3

    x4w4

    s

    Received Signal (baseband rep.)

    y =hTh

    hs+ n = hs+ n

    Matched Filter

    w =h

    h

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 5

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Array Gain

    Matched filter

    w =h

    h

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 6

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Array Gain

    Matched filter

    w =h

    h

    Received Signal (baseband rep.)

    y =hTh

    hs+ n = hs+ n

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 6

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Array Gain

    Matched filter

    w =h

    h

    Received Signal (baseband rep.)

    y =hTh

    hs+ n = hs+ n

    SNR =h22s

    2n M

    M number of antenna elements2s (

    2n) signal (noise) variance

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 6

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Multi-User MISO ( MIMO)

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 7

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Multi-User MISO ( MIMO)

    h1

    h2

    h3

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 7

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Multi-User MISO ( MIMO)

    h1

    h2

    h3

    Received Signal (baseband rep.)

    yi = hT

    i x+ ni, x =

    K

    i=1

    hi

    hisi

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 7

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Multi-User Transmission

    Beamforming

    yi = hisi +

    K

    j=1j 6=i

    hTi h

    j

    hjsj + ni

    useful signal interference

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 8

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Multi-User Transmission

    Beamforming

    yi = hisi +

    K

    j=1j 6=i

    hTi h

    j

    hjsj + ni

    useful signal interference

    Received Signal (baseband rep.)

    SNRi =hi

    22si

    2ni SINRi =

    hi22si

    K

    j=1j 6=i

    |hTi hj |2

    hj22sj +

    2

    ni

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 8

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Massive MIMO

    Large number of base station antennas

    M K

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 9

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Benefits

    Array Gain

    M

    SNR

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 10

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Benefits

    Array Gain

    M

    SNR

    Asymptotic Orthogonality

    hH

    i hj

    M 0 SINR SNR

    Robust and simple signal processing methods

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 10

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Task of the Week

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 11

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Channel State Information (CSI) Acquisition

    Uplink Training

    h = h + n

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 12

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Channel State Information (CSI) Acquisition

    Uplink Training

    h = h+hI + n

    Pilot-Contamination

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 12

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Questions

    What is the impact of Pilot Contamination (PC) on the

    downlink communication mode?

    What kind of Countermeasures (against PC) could be

    thought of?

    Hint: Compute the SINR at the i-th receiver based on the

    erroneous channel vector estimates

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 13

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Appendix

    SISO stands for Single-Input Single-Output and in the

    context of wireless communications refers to a single

    antenna element at the transmitter and a single antenna

    element at the receiver side of a communication link

    MISO stands for Multiple-Input Single-Output

    MIMO stands for Multiple-Input Multiple-Output where

    the multiple antenna elements at the receiver side are

    either deployed at a single receiver or distributed among

    multiple receivers

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 14

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Appendix (contd)

    M is the number of antenna elements at the transmitter K is the number of receivers si is the dedicated signal for the i-th receiver wi is the weight at the i-th antenna element of the

    transmitter (in case K = 1) wi is the weight vector (beamformer) at the transmitter

    dedicated to the i-th receiver (in case K > 1) wi consists of the weights wi,1, wi,2, . . . , wi,M where wi,m is

    the m-th weight of the i-th beamformer xi is the transmitted signal from the i-th antenna element at

    the transmitter x is the transmitted signal vector ni is the noise at the i-th receiver yi is the received signal at the i-th receiver

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 15

  • Chair of Signal Processing Methods Technische Universitt Mnchen

    Appendix (contd)

    hi is the channel coefficient from the i-th antenna element

    at the transmitter to the single receiver (in case K = 1) hi is the channel vector from the transmitter unit to the i-th

    receiver (in case K > 1) hi consists of the channel coefficients hi,1, hi,2, . . . , hi,M

    where hi,m is the channel coefficient between the m-th

    antenna element at the transmitter and the i-th receiver hi is an estimate of the channel vector hi hI,i is the distortion of the estimated channel vector due to

    pilot contamination 2si and

    2ni

    are the variances of signal si and noise ni SNR is the Signal-to-Noise Ratio SINR is the Signal-to-Interference-and-Noise Ratio h

    T is the transposed vector h, h is the norm (length) ofh, and h is the conjugate complex vector h

    Technische Universitt Mnchen Chair of Signal Processing MethodsTechnische Universitt Mnchen 16