MIMO Wireless Systems Using MIMO Wireless Systems Using Antenna Pattern DiversityAntenna Pattern Diversity

Liang Dong

Department of Electrical and Computer EngineeringThe University of Texas at Austin

April 5, 2002

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OutlineOutline

• Introduction and Motivation

• MIMO Wireless Communication

• The Innovation of Polarization Diversity

• MIMO & Antenna Pattern Diversity

• Conclusion and Ongoing Research

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MotivationMotivation• Desire:

– High bit rate wireless access.

• Problem:– Wireless throughput limited by scarce & expensive spectrum,

power limitations, fading, interference, noise

• Goal:– Design spectrum efficient wireless links.– Spectrum efficiency = data rate / BW

• Solution:– Multi-antenna wireless communication systems.

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Multi-Antenna Wireless SystemsMulti-Antenna Wireless Systems

BTS

CCI

• Existing wireless systems (SISO / SIMO / MISO)– Multiple antennas at transmitter or receiver

• Future wireless systems (MIMO)– Multiple antennas at both transmitter and receiver

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Why MIMO Communication?Why MIMO Communication?

• Spectrum efficiency– Spectrum is expensive

– Maximize data rate / bandwidth -> bits / s / Hz

– MIMO technology can create multiple data pipes via spatial multiplexing

• Quality– Wireless links fluctuate due to fading and interference

– Require high mean and low variance SINR for wire-like quality

– MIMO technology can enable very reliable communication links

• Limited transmit power– Transmit power is limited in wireless systems

– MIMO technology can reduce required transmit power and/or increase range/coverage

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What is a MIMO Communication Link?What is a MIMO Communication Link?

• Propagation channel : channel matrix (narrow band)

– For this talk: assume nT = nR = n.

Space-TimeEncoder

Space-Time

Decoder

...

...bits bits

Mt Mr

transmitter receiverchannel

nT nR

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Channel Capacity with MIMO Channel Capacity with MIMO

• Channel capacity in bits per second per hertz:

• Mutual information (instantaneous channel capacity):

MIMO capacity scales linearly as the number of antennas.

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Mutual Information in Real MIMO ChannelsMutual Information in Real MIMO Channels

• Enormous (linear-scale) capacity exists when the channel matrix H unitary.

• Real channels are rarely unitary

– Function of scattering environment

– Antenna geometry

• What is the mutual information in practical channels?

• Decouple the MIMO channel into n SISO sub-channels:Performing SVD on H, let H = UV.

where, y = U+ v(R), x = AVv(T), and u = U+n.

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Dependence Between Sub-channelsDependence Between Sub-channels

• The mutual information of the MIMO channel is the sum of the mutual information of the n SISO sub-channels:

where, i2 is the gain of the ith sub-channel.

• Insufficient spacing results in loss of orthogonality between sub-channels.

• Any other ways to introduce more independent sub-channels?

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Polarization in MIMO SystemsPolarization in MIMO Systems

• Dual-polarization gives 2 (mostly) orthogonal channels

• Cross-pole discrimination characterizes coupling– Typically 15dB in practical applications

– Depends on terrain and environment

• Polarization diversity used in fixed wireless

• Antennas can be closely collocated

Can we do better than 2x?

LOS microwave links

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Mirror

Transmitter ReceiverEx

Ey

Ez

• LOSTwo degrees of electric field freedom

• LOS + Reflection A third degree of freedom results from the mirror (scattering).

Multi-polarization Communication LinksMulti-polarization Communication Links

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Communication in Multi-Polarization ChannelsCommunication in Multi-Polarization Channels

• Proposed by [Andrews et. al, 2001]

• H, 6 £ 6 channel transfer matrix.

relating the electric (E) and magnetic (B) fields with idealized oscillating electric (p) and magnetic (m) dipole moments:

= H

m

pc

B

E

c

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Multi-Polarization Capacity LimitsMulti-Polarization Capacity Limits

• Define the number of polarization channels as rank(H).At large SNR, M(H) tends to the value rank(H) log2 ().

• Claim [Andrews et. al]In free-space, dual-polarized systems rank(H) = 2.In a scattering environment rank(H) = 6.

=> Tripling the capacity.

• Questions: Can we really get this improvement in real channels?

• Answer: This is a merely a loose upper bound in a real EM world.

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TX: (9.9, 7.7, 10.5) , RX: (15.1, 109.8, 8.1) , = 0.167 m , same as in [Andrews et.].

TX

RX

Simulation (2-mirror environment)Simulation (2-mirror environment)

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Antenna Radiation PatternsAntenna Radiation Patterns

• Infinitesimal electric-dipole (z) • Infinitesimal magnetic-dipole (z)

(current-loop)

x y

z

x y

z

E

H

EH

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Simulation Result (2-mirror environment)Simulation Result (2-mirror environment)

Eigenvalues of HH+. RX is at variable distance from the TX.

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MIMO Systems Using Pattern DiversityMIMO Systems Using Pattern Diversity

• Consider a narrow band MIMO system, with closely collocated antennas at transmitter and receiver.

• Antenna pattern diversity appears in the transfer matrix.

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Building blocks (101010 m)T1 and T2: Transmission points. R1 and R2: Receiving tracks.

FASANT SimulationsFASANT Simulations

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Case 1: TCase 1: T11 => R => R11 (both LOS and NLOS regions) (both LOS and NLOS regions)

Eigenvalues of HH+

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Case 1: Comparison of Mutual InformationCase 1: Comparison of Mutual Information

• Compare (local-averaged) M(H) of 6 £ 6, 3 £ 3 and 2 £ 2 MIMO channels. The LOS region is y 2 [13.33, 26,67] m.

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Case 1: Comparison of Mutual InformationCase 1: Comparison of Mutual Information

• Ratios of M(H) of 6 £ 6, 3 £ 3 and 2 £ 2 MIMO channels.

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Case 2: TCase 2: T22 => R => R11 and R and R22 (Separated LOS and NLOS cases) (Separated LOS and NLOS cases)

Receiver on LOS street Receiver on NLOS street

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Case 2: Caparison of Mutual InformationCase 2: Caparison of Mutual Information

Receiver along: (a) R2 (LOS street ). (b) R1 (NLOS street).

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Case 2: Caparison of CCDFsCase 2: Caparison of CCDFs

Receiver along: (a) R2 (LOS street ). (b) R1 (NLOS street).

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ConclusionsConclusions

• MIMO systems that exploit antenna pattern diversity allows improvement for closely collocated receiver and transmitter antennas.

• The capacity increase is limited by the sub-channel correlation in a real electromagnetic world.

• The capacity increase depends on the characteristics of the scattering environment.

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Ongoing ResearchOngoing Research

• Design of compact antennas:

Antenna radiation pattern selection for optimal MIMO performance.

• Propagation channel study.

• Analysis of channel correlation and channel capacity of MIMO system that exploits antenna pattern diversity.

UT Faculty Contacts– Prof. Hao Ling – antenna design & analysis

– Prof. Robert Heath – MIMO communications