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Primer on MIMO wireless systems Rohit Budhiraja IIT Kanpur Nov. 23, 2018 MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 1

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Page 1: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Primer on MIMO wireless systems

Rohit Budhiraja

IIT Kanpur

Nov. 23, 2018

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 1

Page 2: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 3: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 4: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMO

Millimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 5: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systems

Non-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 6: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 7: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 8: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Brief Introduction

Lead the Wireless System Design and OptiMization (WiSDOM) group

Prototyping and algorithm design for 5G systems

Massive MIMOMillimeter and cloud radio systemsNon-orthogonal multiple access systems

Practicing engineer – leading the 5G testbed effort from IIT Kanpur

Courses

MIMO wireless communications5G NRDigital communications

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 2

Page 9: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 10: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 11: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 12: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 13: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 14: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 15: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Modeling of a communication channel

Consider additive white Gaussian channel (AWGN) channel

x - input with power P

n - zero-mean Gaussian noise with power N0

Also called single-input single output (SISO) channel

Signal to noise ratio (SNR) is defined as PN0

Fact: When n1 and n2 are independent Gaussian with zero-mean

Power of n1 + n2 = 2N0

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 3

Page 16: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 17: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz

whereP

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 18: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 19: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime,

C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 20: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)

≈ PN0

log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 21: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 22: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 23: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime,

C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 24: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)

≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 25: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)

High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 26: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR.

Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 27: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 28: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 29: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 30: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 31: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Motivation for using multiple antennas

Consider AWGN channel y = x + n

Spectral efficiency

C = log2

(1 +

P

N0

)bits/sec/Hz where

P

N0is called SNR

Logarithm behaviour

when PN0� 1, low SNR regime, C = log2

(1 + P

N0

)≈ P

N0log2 e

Low SNR – capacity increases linearly with SNR

when PN0� 1, high SNR regime, C = log2

(1 + P

N0

)≈ log2

(PN0

)High SNR – capacity increases only logarithmically with SNR. Not very impressive.

Transmit power and noise variance are fixed – how do we increase SNR

Multiple receive/transmit antennas help us increase SNR

Multiple receive and transmit antennas help us transmit multiple streams in parallel

Useful at high SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 4

Page 32: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 33: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas.

We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 34: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 35: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2

= 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 36: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2

with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 37: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 38: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)

≈ 2PN0

log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 39: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas (SIMO)

Consider AWGN channel with 1 transmit antenna and 2 receive antennas

Noise power is N0 and independent across antennas. We simply add these 2 receive signals

y = y1 + y2 = 2x + n1 + n2 with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 5

Page 40: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna.

We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 41: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 42: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 43: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 44: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n

=√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 45: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n

with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 46: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 47: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antenna (MISO)

Consider AWGN channel with 2 transmit and 1 receive antenna. We still transmit one symbol x

Total transmit power is x2

2 + x2

2 = P. Transmit power is same as single transmit antenna case

Received signal is

y =x√2

+x√2

+ n =√

2x + n with SNR =2P

N0

Spectral efficiency is C = log2

(1 + 2P

N0

)≈ 2P

N0log2 e

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 6

Page 48: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna.

Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve it

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 49: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna. Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve it

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 50: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna. Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve it

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 51: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna. Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve it

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 52: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna. Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve it

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 53: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas (MIMO)

Consider AWGN channel with 2 transmit and 2 receive antenna. Transmit two symbols x1 and x2

Received signals are

y1 =x1√

2+

x2√2

+ n1

y2 =x1√

2+

x2√2

+ n2

One equation two variables; cannot solve itMIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 7

Page 54: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Fixed single-antenna wireless channels

Consider the following single-antenna fixed wireless channel. Modeled as a complex number h

AWGN channel with SNR = P|h|2N0

. Therefore its spectral efficiency is

C = log

(1 +

P|h|2

N0

)

Also know as transmission mode 1 in LTE

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 8

Page 55: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Fixed single-antenna wireless channels

Consider the following single-antenna fixed wireless channel. Modeled as a complex number h

AWGN channel with SNR = P|h|2N0

. Therefore its spectral efficiency is

C = log

(1 +

P|h|2

N0

)

Also know as transmission mode 1 in LTE

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 8

Page 56: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Fixed single-antenna wireless channels

Consider the following single-antenna fixed wireless channel. Modeled as a complex number h

AWGN channel with SNR = P|h|2N0

.

Therefore its spectral efficiency is

C = log

(1 +

P|h|2

N0

)

Also know as transmission mode 1 in LTE

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 8

Page 57: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Fixed single-antenna wireless channels

Consider the following single-antenna fixed wireless channel. Modeled as a complex number h

AWGN channel with SNR = P|h|2N0

. Therefore its spectral efficiency is

C = log

(1 +

P|h|2

N0

)

Also know as transmission mode 1 in LTE

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 8

Page 58: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Fixed single-antenna wireless channels

Consider the following single-antenna fixed wireless channel. Modeled as a complex number h

AWGN channel with SNR = P|h|2N0

. Therefore its spectral efficiency is

C = log

(1 +

P|h|2

N0

)

Also know as transmission mode 1 in LTE

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 8

Page 59: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 60: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals

(receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 61: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 62: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1

+ h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 63: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2

= (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 64: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x

+ h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 65: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 66: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0

=(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 67: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 68: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5;

SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 69: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

.

Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 70: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Single transmit and multiple receive antennas wireless channel

We weigh and add these 2 receive signals (receive beamforming/matched filtering)

y = h∗1y1 + h∗2y2 = (|h1|2 + |h2|2)x + h∗1n1 + h∗2n2

SNR =(|h1|2 + |h2|2)2

(|h1|2 + |h2|2)N0=

(|h1|2 + |h2|2)P

N0

For example, h1 = 1, h2 = −.5; SNR= 1.25PN0

. Fact: matched filter maximizes SNR

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 9

Page 71: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 72: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 73: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 74: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n

= (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 75: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n

= hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 76: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n

with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 77: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 78: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5;

SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 79: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 80: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR.

Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 81: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (1)

Assume h1 and h2 are not known at the transmitter. Transmit x√2

from each antenna

Received signal is

y = h1x√2

+ h2x√2

+ n = (h1 + h2)x√2

+ n = hx√2

+ n with SNR =|h|2P2N0

For example, h1 = 1, h2 = −.5; SNR= .25P2N0

= .125PN0

10-times reduction in SNR. Can we do better?

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 10

Page 82: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 83: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 84: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna

andh∗2 x√

c= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 85: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna

(transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 86: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 87: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 88: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 89: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 90: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 91: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1

+ h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 92: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n

=|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 93: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n

=√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 94: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n

with SNR =(|h1|2 + |h2|2)P

N0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 95: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 96: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel

– crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 97: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channel

Transmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 98: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and single receive antennas wireless channel (2)

Assume h1 and h2 are known at the transmitter – very important assumption

Transmith∗1 x√

c= x1 from first antenna and

h∗2 x√c

= x2 from second antenna (transmit beamforming)

Total transmit power is |h1|2|x|2c

+ |h2|2|x|2c

= (|h1|2+|h2|2)Pc

For transmit power to be equal to P, c = |h1|2 + |h2|2

y = h1x1 + h2x2 + n =|h1|2 + |h2|2√

cx + n =

√|h1|2 + |h2|2x + n with SNR =

(|h1|2 + |h2|2)PN0

Same SNR (capacity) as that of the SIMO channel – crucial that transmitter knows the channelTransmission mode 9/6 depending on how channel is estimated/fed back

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 11

Page 99: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 100: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 101: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 102: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 103: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 104: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (1)

Transmit x1√2

from first antenna and x2√2

from second antenna

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 12

Page 105: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 106: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 107: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 108: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T

Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 109: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]

To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 110: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 111: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 112: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 113: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennas

Also known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 114: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Multiple transmit and receive antennas wireless channel (2)

Received signal is

y1 =h11x1√

2+

h12x2√2

+ n1

y2 =h21x1√

2+

h22x2√2

+ n2

y = Hx + n

Receive vector y = [y1 y2]T , transmit vector x = [x1/√

2 x2/√

2]T

Receiver noise n = [n1 n2]T Channel H =

[h11 h12h21 h22

]To detect x1 and x2,

y = H−1y

= x + H−1n

Two symbols are simultaneously transmitted from two antennasAlso known as transmission mode 3 – open loop spatial multiplexing

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 13

Page 115: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

MIMO wireless systems capacity -comparison

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 14

Page 116: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 117: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenarios

When channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 118: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 119: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 120: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenarios

When channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 121: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15

Page 122: Primer on MIMO wireless systemshome.iitk.ac.in/~rohitbr/pdf/intel.pdf · Modeling of a communication channel Consider additive white Gaussian channel (AWGN) channel x - input with

Conclusions

Multiple transmit or receive antennas boost the SNR

Transmit only one data stream – optimal in low SNR scenariosWhen channel is bad, focus only at one stream

Multiple transmit and receive antennas

Transmit multiple data streams – optimal in high SNR scenariosWhen channel is good, have fun!

Thank you

MIMO Wireless Communications (Rohit Budhiraja, IITK) MIMO fundamentals 15