1. Chenhui Zheng/Communication Laboratory
Correlation and Capacity analysis of Multiple Input Multiple Output Antenna System
Chenhui Zheng/Communication Laboratory
Supervisor: Professor Sven-Gustav Häggman
Instructor: PH.D. Michael Hall
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2. Outline Motivation MIMO System Overview MIMO Capacity
Correlation Impact on Capacity
Simulation Results
Conclusions
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3. Motivation
Future wireless application creates insatiable demand for high bit rate wireless access.
The spectrum has become a scarce and very expensive resource need for spectral efficiency.
System capacity is interference limited-cannot be increased by increasing transmitted power.
Time and frequency domain processing are at limits, space one-not!
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4. What’s MIMO?
MIMO is an extraordinary bandwidth-efficient approach to wireless communication.
It was originally developed in Bell Labs in
It takes advantage of the spatial dimension,offering exceedingly high bit rates without increasing transmitted power bandwidth allocation.
The central paradigm is exploitation rather than mitigation of multipath effects.
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5. Wireless Channel
Multipath propagation has historically been regarded as an impairment because it causes signal fading.To mitigate this problem, diversity techniques were developed over the years. Antenna diversity is a widespread form of diversity.
Information theory has shown that with multipath propagation, multiple antennas at both transmitter and receiver can establish essentially multiple parallel channels that operate simultaneously, on the same frequency band at the same total radiated power.
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6. Spectral Efficiency Limits: Shannon Bound
The information-theoretic capacity of single-antenna links is limited by the link’s signal to noise ratio according to Shannon’s capacity formula.
Each extra bps/Hz requires roughly a doubling of the Tx power (to go from 1bps/Hz to 11bps/Hz, the Tx power must be increased by ~1000 times!)
Increases as log of SNR very slowly!
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7. Diversity Concept
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8. Efficiency Limits with a single Array
A single array provides diversity against fading
(SIMO) Slow logarithmic growth of the bandwidth efficiency limit.
(MISO) only improve the outage performance but not the average capacity.
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9. Lifting the Limits with Dual Arrays
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10. Uncorrelated subchannels parallel independent subchannels.
How does it work?
Uncorrelated subchannels parallel independent subchannels.
Channel matrix diagonalization is a key operation for MIMO, signal processing at the receiver must do this job.
Correlated subchannels complete diagonalization is not possible increase in fading and decrease in channel capacity.
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11. MIMO Channel Capacity Capacity for a complex AWGN (M, N) MIMO channel:
Eigenvalue decomposition
Singular value decomposition
denotes the transpose conjugate
are the eigenvalues of
The total capacity of a MIMO channel is made up by the sum of parallel AWGN SISO subchannels
The rank of H
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12. Basic Assumptions Single-user link
Noise limited (no co-channel interference)
Narrowband flat fading channel
Channel perfectly known to receiver
Rich scattering environment
Antenna element spacing is sufficient uncorrelated channel.
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13. Channel Simulation by Ray Tracing
Ray tracing technique provides a simulation approach to obtain accurate channel information. It deterministically models the propagation channel including amplitudes, delays, phase shifts and angle of arrival for rays.
Carrier frequency: 2GHz
(4,4) MIMO
Antenna spacing
Transmitter Power: P=40dBm
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14. Correlation impact on Capacity
Channel correlation is the main limitation to MIMO.
Angle spread (Outdoor) and antenna element spacing(indoor) are the key factors for correlation.
Angle spread Correlation
Correlation Capacity
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15. Angle Spread vs. Correlation
AOA distribution of transmitter and receiver antenna elements.
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16. Water-filling method
When the transmitter does not know the channel, the best strategy is to divide the power equally among all channels.
When the transmitter knows the channel, capacity is maximised by using the principles of water-filling. In simple terms this means to assign the most power to channel with the least attenuation and least power to the channel with most attenuation.
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17. Asymptotic Capacities
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18. Simulation Results for capacity(I)
SNR vs. Capacity
Transmitter power vs. Capacity
Numbers of antenna elements vs. Capacity
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19. Simulation Results for Capacity(II)
Capacity with water-filling (d=0.5 , P=30dBm)
When antenna spacing is not sufficiently large, the fading between antenna elements will be correlated and capacity decreases.
Water-filling is beneficial under correlated and low SNR situation and roughly yield the same capacity as equal power allocation in high SNR situation.
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20. Future Work
Create the detail architectural database to obtain more precise channel data.
Compare the results with MIMO measurement carried out by Radio Laboratory.
Determination of channel correlation and capacity for different antenna set-ups.
Multi-user environment, frequency selective fading channel.
MIMO Radio channel modelling.
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21. Summary MIMO overcomes conventional limits.
Capacity gains can be very large in rich scattering environment.
Correlation is the major limitation to capacity.
The rich scattering environment is not always guaranteed in outdoor environment.
Power allocation strategies are used to improve MIMO capacity when transmitter knows the channel.
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