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MU-MIMO scheme performance evaluationsusing measured channels in specificenvironments
Christoph Mecklenbräuker
with contributions from Giulio Coluccia, Giorgio Taricco,Christian Mehlführer, and Sebastian Caban
www.ist-mascot.org
© MASCOT 2007 2
Performance evaluation principles
Performance is representated as a functional Tdepending on the receiver input distribution F
General linear MU-MIMO channel YA = HASA + IA + N
F = joint distribution of (HA , SA , IA , N)
A = random set of active links
© MASCOT 2007 3
Role of the MU-MIMO scheduler
The scheduler defines A depending in CQIfeedback
The scheduler shapes the statistics of HA and IA
Given A, the PHY shapes the statistics of SA
Evaluation of T(F ) must account for thedependencies among HA , SA , IA .
© MASCOT 2006 2
Three approaches considered
Approach 1: Measure then simulate- Measure the MIMO channels with a channel sounder- Store the MIMO channels in a database- Run a Matlab simulation based on the stored channels
Approach 2: Emulate using real frontends- Take two PCs running Matlab- Transmitter PC
- Use Matlab to format a MIMO transmission block- Transmit it via a real MIMO transmitter frontend
- Receiver PC- Receive it from a real MIMO receiver frontend- Implement the Detector/Decoder in Matlab
- Evaluate performance using a side channel
Approach 3: Real-time testbed
© MASCOT 2006 3
Approach 1: Measure then Simul.
Advantages- Perfect repeatability of the performance evaluation- Very suitable for MU-MIMO performance evaluation- You can simulate with perfect channel state information (if
you wish so)- Many environments can be handled- Great freedom in defining ensemble averages
Disadvantages- The MIMO channel‘s behaviour must be
- simulated in Matlab (convolution), and- idealised (analog Tx/Rx front-end behaviour!)
- Channel measurement time, duration, and sampling ratesdo not match the simulated system
- Non-realtime- It is questionable whether opportunistic MU-MIMO schemes
based CSI feedback can be evaluated
© MASCOT 2006 4
Approach 2: Emulate
Advantages:- Hic et nunc- MIMO channel is used rather than simulated- Real front-end behaviour is included in performance
Disadvantages:- Performance evaluations are not perfectly repeatable- Great care must be taken when comparing two
competing MU-MIMO schemes- MU-MIMO performance evaluation is significantly
more costly than Single User case.- Non-realtime- It is questionable whether opportunistic schemes with
CSI feedback can be evaluated
© MASCOT 2006 5
Approach 3: Real-time Testbed
Advantages- Front-end effects included- Real MIMO channel behaviour- Opportunistic schemes with limited CSI feedback can
be evaluated
Disadvantages- Costly- Little flexibility- Performance evaluation not perfectly repeatable- It is difficult to emulate perfect CSI.- It is difficult to analyse a „single effect“
© MASCOT 2006 6
Example for Approach 1Measure then simulate
MEDAV‘s RUSK ATM channel sounder- 15 Tx elements (uniform circular array)- 8 Rx elements (uniform linear array)
- Measurement band: 1940-2060 MHz
- Urban, Sub-urban, Rich-scattering environments
- http://www.ftw.at/Measurements
© MASCOT 2006 7
Mobile Tx, Static Rx
Sub-urban environmentReceiver‘s view @ Weikendorf
© MASCOT 2006 9
Outdoor Channelimpulse response
© MASCOT 2006 10
Indoor rich scattering
© MASCOT 2006 11
Spatial re-sampling (1)
© MASCOT 2006 12
Spatial re-sampling (2)
© MASCOT 2006 13
Optimum receiver vs.Mismatched ML
[9] G. Taricco and E. Biglieri:Space-time decoding with imperfect channel estimation,IEEE Trans. Wireless Commun.4(4):1874-1888, July 2005
© MASCOT 2006 14
Urban environment
© MASCOT 2006 15
Rich scattering environment
© MASCOT 2006 16
Example Approach 2:Emulate with real front-ends
4 Tx Front-ends 4 Rx Front-ends 2.6 GHz band, 20 MHz bandwidth
3/42 Sebastian Caban
TransmitterTransmitter
Experiment Set Up
• Roofor even higher
• Roofor even higher
5/42 Sebastian Caban
TransmitterTransmitter
Experiment Set Up
• Roofor even higher
• Patch Antennas• 20 dBm/antenna• 2.5 GHz
• Roofor even higher
• Patch Antennas• 20 dBm/antenna• 2.5 GHz
20dBm = 0.1 watt
7/42 Sebastian Caban
ChannelChannel
Experiment Set Up
• real channel, urban environment• real channel, urban environment
7 amTX
9/42 Sebastian Caban
ReceiverReceiver
Experiment Set Up
• Indoor• 4 Monopoles• Indoor• 4 Monopoles
11/42 Sebastian Caban
[email protected] Measurement
• 13 Ec/Ior values• 2 and 4 transmit antennas• 2 CQI values• 4, 6, 8, and 10 spreading-codes active• 6552 realizations
• 13 Ec/Ior values• 2 and 4 transmit antennas• 2 CQI values• 4, 6, 8, and 10 spreading-codes active• 6552 realizations
• 4 hours net measurement time• 600 GB of data received• 4 days of work for 23 PCs
• 4 hours net measurement time• 600 GB of data received• 4 days of work for 23 PCs
12/42 Sebastian Caban
[email protected] Impulse Responses
approx 160 m
TX1 → RX1TX1 → RX1 TX2 → RX1TX2 → RX1
TX2 → RX2TX2 → RX2TX1 → RX2TX1 → RX2
13/42 Sebastian Caban
[email protected] Impulse Responses
36/42 Sebastian Caban
[email protected] Results
Parameters:• 2x2 system• Code rate of 0.7• 1000 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
95% confidence intervals
Parameters:• 2x2 system• Code rate of 0.7• 1000 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
95% confidence intervals
37/42 Sebastian Caban
[email protected] Results
Parameters:• 2x2 system• Code rate of 0.7• 6552 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
95% confidence intervals
Parameters:• 2x2 system• Code rate of 0.7• 6552 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
95% confidence intervals
38/42 Sebastian Caban
[email protected] Results
Parameters:• 2x[4,3,2] system• Code rate of 0.7• 6552 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
Parameters:• 2x[4,3,2] system• Code rate of 0.7• 6552 realizations• 10 Codes• 45 equalizer taps• 15 channel taps
39/42 Sebastian Caban
[email protected] Results
Parameters:• [4x4, 2x2] system• Code rate of 0.7• [1788,6552]
realizations• 10 Codes• 45 equalizer taps• 15 channel taps
• equal EB
Parameters:• [4x4, 2x2] system• Code rate of 0.7• [1788,6552]
realizations• 10 Codes• 45 equalizer taps• 15 channel taps
• equal EB
Question: power normalization in measurements?Question: power normalization in measurements?
40/42 Sebastian Caban
[email protected] Results
Parameters:• 2x2 system• Code rate of 0.7• 6552 realizations• [4,6,8,10] Codes• 45 equalizer taps• 15 channel taps
Parameters:• 2x2 system• Code rate of 0.7• 6552 realizations• [4,6,8,10] Codes• 45 equalizer taps• 15 channel taps
41/42 Sebastian Caban
WeWe
MobilkomMobilkomOneOne
• If the Matlab-code works,one “extended week”1 needed to measure the influence of a certain parameter
• If the Matlab-code works,one “extended week”1 needed to measure the influence of a certain parameter
1 = 7 days, 16 hours a day