January 2006
doc.: IEEE 802.22-06/0016r1
Updated MIMO proposal
Samsung Electronics
IEEE P802.22 Wireless RANs
Authors:
Date: 2006-01-18
Name
Company
Address
Phone
email
David Mazzarese
Samsung Electronics Co. Ltd.
+82 10 3279 5210
d.mazzarese@samsung.com
Baowei Ji
Samsung Telecommunications
America
Dong Suwon P.O. BOX 105,
416, Maetan-3dong, Yeongtonggu, Suwon-si, Gyeonggi-do
Korea 442-600
1301 E. Lookout Dr.
Richardson, TX 75082
+1 972-761-7167
Baowei.ji@samsung.com
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Submission
Slide 1
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
MIMO Contribution
• Solutions to address requirements in the following sections of the FRD
•
•
•
•
5. WRAN System Model/Requirements
5.3. Service Capacity
5.6.2. Flexible Asymmetry
8.10.1. Peak Data Rates
Submission
Slide 2
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Motivations for MIMO
•
Link reliability improvement (diversity or beamforming).
•
Range extension (diversity or beamforming).
•
Improvement of WRAN cell coverage across the TV spectrum due to the
scalability of the number of antennas with frequency at the same time as
channel propagation properties degrade.
•
Space Division Multiple Access (SDMA) by closed-loop multiuser MIMO
(CL MU MIMO) for throughput enhancement.
•
Better spectral efficiency.
•
Enhanced coexistence by reducing required over-the-air time allowed by
higher peak rates and/or lower average delay per packet.
•
Enhanced coexistence by reducing the required CPE transmit power to
achieve a target data rate.
•
Possible interference cancellation or nulling of interferers, as well as
creating nulls towards incumbents (e.g. Part 74 devices).
Submission
Slide 3
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Reminders on MIMO
• Advantages of MIMO come without transmit power nor bandwidth
increase.
• Only expenses are:
– computation complexity at baseband, which can be very limited if linear
solutions are employed (and much lower than some other system parts).
– Additional hardware (antennas, RF front-ends)
• Other issues (signaling overhead,…) are not a concern, as proved by
the adoption of MIMO in many IEEE and non-IEEE standards.
It is widely accepted that the benefits of MIMO justify the expenses.
Usually baseband complexity is seen as the main hurdle, but we do
not intent to use complex multiuser detectors.
Submission
Slide 4
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Feasibility discussion
•
1 to 5 antenna elements are feasible with an overall stride not
exceeding 1.5 m
•
Can be installed at the BS and at CPEs
•
Beamforming processing is performed in the baseband domain
•
Typical non-LOS operation justifies sufficient scaterring around CPE
to provide independent fading
•
Multiple antennas independent fading is more problematic at the BS,
but it could be available in suburban or urban areas (at the same
time as a larger customer base)
•
Multiuser MIMO techniques are feasible even in correlated channels
Submission
Slide 5
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
CPE and BS Antenna Array Concept
L < lambda
(Typically lambda/4
or lambda/10)
0.25 m
A1
A2
Frequency of operation
Below 100 MHz
100 MHz
200 MHz
300 MHz
Above 600 MHz
1.5 m
A3
A4
A5
Elements in the array
Min element Max element
spacing ( l ) spacing ( l )
A1 (RF front-end always N/A
N/A
used)
0.5l
0.5l
A1, A5
0.5l
l
A1, A3, A5
0.5l
1.5l
A1, A2, A4, A5
3l
A1, A2, A3, A4, A5
0.5l and l
The dipole length is typically between lambda/10 and lambda. If we choose the
length to be 30 cm, it covers the frequency range from 100 MHz to 1 GHz. As long
as the above constraint is met, the radiation pattern will not change significantly.
Submission
Slide 6
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Coverage and range extension
Tolerable median path loss of 119 dB
Path loss exponent: 2 up to 500 m,
then 3.18 beyond with Hata model
Note that we cannot meet the 33 km of functional requirements above
509 MHz without multiple antennas with the above assumption of
tolerable median path loss and the path loss model used here.
Submission
Slide 7
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Feasibility of linear and advanced MIMO
•
Fixed nature of CPEs means very slow channel fading, allowing to track the
channel matrices at the transmitter and at the receivers without excessive
overhead
 A cognitive network should at least be aware of its own channel !
•
TDD operation would allow to estimate the downlink channel from the uplink
using channel reciprocity and calibration
•
FDD operation would require explicit feedback of quantized differential
values of channel gains
•
In single-user MIMO with channel state information at the transmitter and at
the receivers, capacity is achieved by linear processing
•
In the multiuser MIMO case, linear processing comes very close to the sumcapacity limit
Submission
Slide 8
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Small-scale fading simulations
WRAN multipath profile A
Fading gains across subcarriers (5.57 MHz)
(vertical stripe shows time variations across
3400 OFDM symbols = 100 frames)
Submission
Slide 9
Fading gains across OFDM symbols
(each line shows a different subcarrier)
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Closed-loop Multiuser MIMO
Linear processing with channel sounding
Submission
Slide 10
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
CL MU MIMO
linear processing
x1 estimate
x1
W1*
M1
xk
xk estimate
Mk
transmission
Wk*
xN
Wk’*
MN
Base station transmitter
WN*
xk’ estimate
xN estimate
Users terminals
Submission
Slide 11
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
CL MU MIMO
Computation and control signals
•
Uplink pilots embedded in the uplink traffic channels are used to obtain
channel estimates at the base station (TDD), or quantized differential
channel values are feedback by the CPEs (FDD)
•
Transmit filters M and receive filters W are computed at the base station
•
Downlink pilots embedded in the downlink traffic channels are used to
convey the receive filters W to the CPEs (in case of multiple CPE antennas)
•
No new pilots are needed, they already exist in single antenna systems to
allow channel estimation for coherent detection at the BS (uplink) and at the
CPE (downlink)
Submission
Slide 12
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Robustness to antenna correlations
Where single-user MIMO techniques fail to achieve spatial multiplexing
gain in correlated environments at the base station, multiuser MIMO still
provides the maximum spatial multiplexing gain, provided that we serve
users that have uncorrelated channels among each other (basically
means widely spatially separated).
Submission
Slide 13
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Performance with correlated fading at the transmitter
3GPP LTE suburban-macro small-scale fading channel model
The channel matrix of any
given user has only one
dominant eigenvalue.
Therefore any single-user
MIMO strategy fails to
achieve a capacity larger than
receiver beamforming (SIMO)
Submission
Slide 14
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Performance with correlated fading at the transmitter
3GPP LTE suburban-macro small-scale fading channel model (mean CINR = 7.5 dB)
CINRmean = 7.5 dB
The gain of diversity techniques
(STBC) is almost null due to BS
antenna correlations
Beamforming provides array
gain in correlated channel
Multiuser diversity further
increases the spectral efficiency,
but does not allow to achieve
spatial multiplexing gain
Only closed-loop multiuser
MIMO allows to achieve
multiplexing gain, even in
correlated environments
Note: Spatial multiplexing gain = linear increase in capacity with number of transmit antennas
Diversity gain = logarithmic increase in capacity with number of antennas
Submission
Slide 15
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Performance with correlated fading at the transmitter
3GPP LTE suburban-macro small-scale fading channel model (mean CINR = 7.5 dB)
Adding antennas at the CPE
improves the spectral efficiency
considerably!
It is a manufacturer’s and
operator’s choice
but we can make that choice
transparent to the algorithm in
the standard
Submission
Slide 16
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Performance with correlated fading at the transmitter
3GPP LTE suburban-macro small-scale fading channel model (mean CINR = 7.5 dB)
Even a small amount of multiuser
diversity is sufficient to achieve
spatial multiplexing gain with CL
MU MIMO.
CL MU MIMO algorithm is
transparent to:
- Correlations at the BS antennas
- Number of CPE antennas
Ability to achieve multiplexing gain
is preserved in all cases
Throughput is nevertheless larger
in uncorrelated channels with
multiple CPE antennas.
Submission
Slide 17
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
Supporting MAC, pilots and control signals
•
Downlink and uplink pilots per antenna for channel estimation : only a
few are needed to track the channel efficiently in slow fading.
•
An adaptive pilot structure must be designed to support a variable
number of antennas (already incorporated to cope with varying channel
conditions in joint proposal ETRI/FT/Gatech/Philips/Samsung).
•
The same pilots can be used for sounding using beamforming vectors.
•
MAP field for the operation of multiple users on the same sub-channel
(same time-frequency resource in OFDMA) for CL MU MIMO, otherwise
same MAP as SISO case.
•
MAC field to switch MIMO modes (CL MU MIMO, Beamforming, SISO).
Submission
Slide 18
David Mazzarese
January 2006
doc.: IEEE 802.22-06/0016r1
MIMO modes
• Closed-loop multiuser MIMO
• Closed-loop single-user MIMO: not always good due to spatial
correlations.
• Diversity reception: whenever multiple receive antennas are
present. When multiple transmit antennas are present, it is
automatically included in MIMO modes.
• Diversity transmission: fallback mode when CSIT is unavailable
or unreliable, but might provide no gain in 802.22.
• SISO: fallback mode when diversity reception/transmission is
unavailable or not implemented if it is optional.
Submission
Slide 19
David Mazzarese