Antenna Selection FTW 2010 Posting
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1 2010 A. F. MolischAntenna selection
Antenna selection in MIMO systems
Andreas F. Molisch
Wireless Devices and Systems (WiDeS) GroupUniversity of Southern California (USC)
FTW TelekommunikationsforumJune 18th 2010, Vienna, Austria
2 2010 A. F. MolischAntenna selection
Contents
Introduction and motivation
Performance analysis
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
3 2010 A. F. MolischAntenna selection
Antenna Selection
Additional costs for MIMO
1. more antenna elements (cheap)
2. more signal processing (Moores law)
3. one RF chain for each antenna element
Basic idea of antenna selection:
have many antenna elements, but select only best for downconversion and processing
only at one link end: cost reductions might be more important at one link end (MS) than the other
Hybrid antenna selection: select best L out of available N antenna elements, use those for
processing
4 2010 A. F. MolischAntenna selection
Transmit antenna selection
Antenna selection can be applied at transmitter or receiver or both
Fewer expensive RF chains
S/W
DAC x PA
DAC x PA
DAC x PA
5 2010 A. F. MolischAntenna selection
Contents
Introduction and motivation
Performance analysis
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
6 2010 A. F. MolischAntenna selection
Antenna Selection for Diversity
Weight selection if all antenna elements are used
Write channel matrix as
Excite channel with Vi, receive with WiH
Received power is i2
Antenna and weight selection for H-S/MRT
Create submatrices by striking rows
Compute maximum singular value for this submatrix
Search submatrix that gives largest max. singular val.
Use singular values associated with selected submatrix as antenna weights
maxSH maxii2
HVH W
7 2010 A. F. MolischAntenna selection
Bounds for the SNR distribution
Upper and lower bounds
Determine
where (i) are ordered SNRs with distribution
i i
iii
i
rt NL
222 ~~max~
,min
1
i j
2
ijH~
Si
2i
H~
Sbound h
~max
~max
tL
1i
ibound
p i1,2, N t N!
i1
Nt1
N riN r1 expi for 1 2 N t
0 otherwise .
8 2010 A. F. MolischAntenna selection
Bounds for the SNR distribution
Characteristic function:
Analytical evaluation: recursive algorithm
j N t !N rNt
0
d11
Nr1e 1ejLt1 1
0
1d22
Nr1e 2ejLt2 2
0
Nt1dNtNt
Nr1e NtejLtNt Nt
9 2010 A. F. MolischAntenna selection
HS-MRT vs. MRT
capacity C [bits/s/Hz]15
capacity C [bits/s/Hz]
cd
f(C
)
0.2
0.4
0.6
0.8
1
5 10 15
N =1
t
234
N =5
t
678
L =5
t
678
cd
f(C
)
0.2
0.4
0.6
0.8
1
5 10
L =1
t
234
Hybrid selection
Maximum ratio transmission
10 2010 A. F. MolischAntenna selection
Capacity with RX antenna selection
L=2 L=3
L=8cdf
(C)
10 20 30
L=2 L=3
L=8
capacity C [bits/s/Hz]
10 20 30
0
0.5
1
3 transmit antennas, 20dB SNR
Admissible number of spatial streams: determined by number of RF chainsSlope of capacity cdf: determined by number of antenna elements
11 2010 A. F. MolischAntenna selection
Contents
System model
Performance analysis
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
12 2010 A. F. MolischAntenna selection
Channel Estimation Error -
Diversity
ideal channelestimation
cdf
(C)
capacity C [bits/s/Hz]7 8 9 10
1
110
0.5
noisy antennaselection
noisy antennaselection
noisy TX weights
noisy antennaselection
noisy TX weightsnoisy RX weights
ideal channelestimation
13 2010 A. F. MolischAntenna selection
Channel Correlation - Diversity
-2 -1.5 -1 -0.5 0 0.5 1 1.5 27
7.5
8
8.5
9
9.5
10
Log(L / )corr
Ca
pa
city
[b
its/s
/Hz]
3/8 systemwith power selection
8/8 system
3/8 systemwith optimumselection
14 2010 A. F. MolischAntenna selection
Contents
System model
Performance analysis
Antenna selection algorithms
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
15 2010 A. F. MolischAntenna selection
Hardware constraints on training
Need to learn channel states of both antennas. But, only 1 antenna
can transmit/receive at any time
Increased time and (pilot) energy overhead
Step 1
Tx2
Tx1Rx1
Rx2
Rx2
Tx1
Tx2
Rx1
Step 2
RF chain
RF chain
Transmit antenna selection
Tx2
Tx1Rx1
Rx2
Step 2
Step 1
Tx2
Tx1Rx1
Rx2
Tx1Rx1
Rx2
Tx1Rx1
Rx2
Receive antenna selection
16 2010 A. F. MolischAntenna selection
AS training in 802.11n WLANs
Training done using MAC headers only
Consecutive packets train disjoint antenna subsets
Feedback: CQI or antenna indices directly
TXASR
Tx4
Tx2
Tx1
Rx
Request AS training
ASFB
AS feedback
Data from best antenna
SIFS
SIFS
Rx estimates channels
TXASI
AS train1
AS train2
AS train3
17 2010 A. F. MolischAntenna selection
Impact of outdated training
Outdated CSI leads to error floor
Analytical consideration: 1-out-of-N selection
18 2010 A. F. MolischAntenna selection
Estimation, selection, reception
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Closed-form expression of SEP
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Optimal weights
21 2010 A. F. MolischAntenna selection
Simulation results
22 2010 A. F. MolischAntenna selection
Contents
System model
Performance analysis
Antenna selection algorithms
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
23 2010 A. F. MolischAntenna selection
Principle
.
.
.
.
Down
ConvLNA A/D
Down
ConvLNA A/D
Sig
Proc
1
L
1
2
Nr
S
W
I
T
C
H
BasebandDemodulator
Pre-
Proc
(M)
RF
Diversity gain AND Beamforming gain maintained Beam selection Vs Antenna Selection Can be implemented using variable phase-shifters In case M is of size L x Nr, selection switch/algorithm is not required
24 2010 A. F. MolischAntenna selection
RF Pre-processing Solutions
Channel-independent solution
Fixed matrix (FFT Butler matrix)
Time-variant solution
Elements of pre-processing matrix tuned to instantaneous channel
state
Time-invariant solution
Elements of pre-processing matrix based only on channel-
statistics
Can be implemented with or without selection
25 2010 A. F. MolischAntenna selection
Channel-independent solution
Transformation matrix is DFT matrix
Transforms from antenna space to beamspace
Each output of DFT has full beamforming gain N
M 1r
1 1 1
1 ejr ejr1r
1 ejr1r ejr12r
26 2010 A. F. MolischAntenna selection
Time-variant solution
(instantaneous CSI)
For diversity:
Achievable performance: same as with full-complexity CSI
Phase-shifter only solution: optimum performance with 2 RF chains
Frequent channel sounding required
27 2010 A. F. MolischAntenna selection
Time-invariant preprocessing
Time-variant selection
Difficult to handle analytically
SL that depends on instantaneous channel state
Tractable lower bound: Swap max and expectation (EH)
22/1
maxmax HvMSSMMSwHMS rrr
rN
NNN LLL
t
TIN
EL
22/1
maxmax HvMSSMMSwS
HM rrr
rN
NNN LLL
t
TIN
EL
28 2010 A. F. MolischAntenna selection
Solution that Improves Lower
Bound
Given SL, problem is similar to the LxNr case
Specifies only L columns of M
Remaining (Nr - L) columns must be orthogonal to these L columns
Given SL, fix corresponding L columns
Subsequent manipulations should not deteriorate previously considered selections
Successive improvement of lower bound by fixing remaining columns
rNLTI
,,,,1 PM
29 2010 A. F. MolischAntenna selection
Beam Patterns
FFT Butler Time-Invariant
(Mean AoA = 450)
TI adapts to mean AoA and angle spread (unlike FFT)
Adapts to presence of multiple clusters
30 2010 A. F. MolischAntenna selection
Receivers with L demodulators
Gain of over 5.0 dB over antenna selection
Mean AoA = 450: Gain of 2.2 dB over FFT-Selection
Mean AoA = 450: No gain over FFT-Selection
SNR (dB)
CD
F o
f S
NR
Nr = Nt = 4, L = 1
Angle spread = 60
dt/ = 0.5
31 2010 A. F. MolischAntenna selection
Effect of Spatial Correlation
SNR (dB)
CD
F o
f S
NR
Time-invariant solution efficacy decreases as correlation decreases
Antenna selection efficacy improves as correlation decreases
Nr = Nt = 4, L = 1
Mean AoA = 600
dt/ = 0.5
32 2010 A. F. MolischAntenna selection
Contents
System model
Performance analysis
Antenna selection algorithms
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
33 2010 A. F. MolischAntenna selection
Measurement setup
Measure channel for Personal Area Networks
Use access point, PC, and handheld
34 2010 A. F. MolischAntenna selection
Diversity gain
35 2010 A. F. MolischAntenna selection
Impact of antenna configurations
d
Configurations
lamda/2
lamda/2
d
Polarization
Line
Saw
Rectangular
Horizontal (H)
Vertical (V)
Alternate H & V (Alt HV)
Dual polarized (DP)
d
d
Configurations
lamda/2
lamda/2
d
Polarization
Line
Saw
Rectangular
Horizontal (H)
Vertical (V)
Alternate H & V (Alt HV)
Dual polarized (DP)
d
-5 0 5 1010
-4
10-2
100
Line
Em
pir
ical C
DF
-5 0 5 1010
-4
10-2
100
Saw
-5 0 5 1010
-4
10-2
100
Rectangle
Normalized SNR [dB]
Em
pir
ical C
DF
-5 0 5 1010
-4
10-2
100
Separation
Normalized SNR [dB]
H - pol
V - pol
H alt V pol
DP
H - pol
V - pol
H alt V pol
DP
H - pol
V - pol
H alt V pol
DP
DP rect /2
DP rect
DP rect 2
DP line
Configuration comparison for the AP - PC scenario HS-B at PC only. LOS. 4:22:2.
36 2010 A. F. MolischAntenna selection
Contents
System model
Performance analysis
Antenna selection algorithms
Effect of nonidealities
Training
RF preprocessing
Results in measured channels
Hardware aspects
Summary and conclusions
37 2010 A. F. MolischAntenna selection
Hardware Aspects
Attenuation of switches
either decrease the effective SNR,
or LNA has to be before switchrequires more LNAs
Switching time: has to be much smaller than duration of training sequence
Accuracy of switch: transfer function has to be same from each input to each output port
MEMS switches: have low insertion loss (0.1dB), but large switching time (5 microsec)
Solid-state switches: high insertion loss (>1 dB), but short switching times (100 ns)
38 2010 A. F. MolischAntenna selection
Phase Quantization Errors
3-bit phase quantization (steps of 450): capacity within 0.1 bits/sec/Hz 2-bit phase quantization (steps of 900): capacity within 0.3 bits/sec/Hz
Spatial diversity: 1 dB loss in mean SNR observed
39 2010 A. F. MolischAntenna selection
Summary and Conclusions
Antenna selection retains the diversity degree, but SNR penalty
For spatial multiplexing, comparable capacity if LrNt Optimum selection algorithms have complexity N!/(N-L)!;
however, fast, good selection algorithms exist
For low-rank channels, transmit antenna selection can increase capacity
Channel estimation errors do not decrease capacity significantly
Frequency selectivity reduces effectiveness of antenna selection
RF preprocessing greatly improves performance, especially in correlated channels
Covariance-based preprocessing especially suitable for frequency-selective channels
Switches with low attenuation required both for TX and RX
40 2010 A. F. MolischAntenna selection
Acknowledgements
This work was done in collaboration with Moe Z. Win
Jack H. Winters
Yang-Seok Choi
Xinying Zhang
Sun-Yuan Kung
Jin-Yun Zhang
Neelesh B. Mehta
Pallav Sudarshan
Yabo Li
Peter Almers
41 2010 A. F. MolischAntenna selection
References (1)
Book chapters and journal papers V. Kristem, N. B. Mehta, and A. F. Molisch, Optimal Receive Antenna Selection in Time-Varying Fading Channels
with Practical Training Constraints, IEEE Trans. Comm., submitted (first round of reviews). T. Wang, J. Tao, A. F. Molisch, P. Orlik, and J. Zhang, Adaptive Antenna Selection at Mobile Stations for SDMA in
WiMAX Networks, Wireless Computing and Mobile Communications, in press P. Almers, T. Santos, F. Tufvesson, A. F. Molisch, J. Karedal, and A. Johansson, Antenna selection in measured
indoor channels, IET Microwaves, Antennas & Popagation 1, 1092-1100 (2007). Y. Li, N. B. Mehta, A. F. Molisch, and J. Zhang, Optimal Signaling and Selection Verification for Transmit Antenna
Selection, IEEE Trans. Comm, 55, 778-789, 2007. N. Mehta and A. F. Molisch, Antenna selection, in G. Tsoulos (ed.), MIMO antenna technology for wireless
communications, invited, Wiley, (2006). H. Zhang, A. F. Molisch, and J. Zhang, Applying Antenna Selection in WLANs for Achieving Broadband Multimedia
Communications, IEEE Trans. Broadcasting, 52, 475-482 (2006).
P. Sudarshan, N. B. Mehta, A. F. Molisch, and J. Zhang, Channel Statistics-Based Joint RF-Baseband Design for Antenna Selection for Spatial Multiplexing, IEEE Trans. Wireless Comm. 5, 3501-3511, (2006)
A. F. Molisch, M. Z. Win, Y. S. Choi, and J. H. Winters, Capacity of MIMO systems with antenna selection, IEEE Trans. Wireless Comm., 4, 142-154 (2005).
X. Zhang, A. F. Molisch, and S. Y. Kung, Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection, IEEE Trans. Signal Proc., 53, 4091-4103 (2005).
A. F. Molisch and X. Zhang, FFT-based Hybrid Antenna Selection Schemes for spatially correlated MIMO channels, IEEE Comm. Lett., 8, 36-38 (2004).
A. F. Molisch and M. Z. Win, MIMO systems with antenna selection, IEEE Microwave Magazine March 2004, 46-56 (2004).
A. F. Molisch, M. Z. Win, and J. H. Winters, Reduced-complexity transmit/receive diversity systems, IEEE Proc. Signal Proc, special issue on MIMO., 51, 2729-2738 (2003).
42 2010 A. F. MolischAntenna selection
References (2)
Conference papers V. Kristem, N. B. Mehta, and A. F. Molisch, A Novel Energy-Efficient Training Method for Receive Antenna Selection, IEEE ICC 2010, in
press.
V. Kristem, N. B. Mehta, and A. F. Molisch, Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training, IEEE ICC 2009.
T. Wang, Z. Tao, A. F. Molisch, P. Orlik, and J. Zhang, Antenna Selection for SDMA in Next Generation WiMAX Networks, IEEE IWCMC2009.
C. Nie, Z. Tao, N. B. Mehta, A. F. Molisch, J. Zhang, T. Kuze, and S. Panwar, Antenna Selection for Next Generation IEEE 802.16 Mobile Stations, IEEE ICC 2008 3457-3462 (2008).
N. B. Mehta, A. F. Molisch, J. Zhang, and E. Bala, Antenna Selection Training in MIMO-OFDM/OFDMA Cellular Systems, IEEE CAMSAP 2007, invited, 2007.
Y. Li, N. B. Mehta, A. F. Molisch, and J. Zhang, Optimal Signaling for Single Transmit Antenna Selection with Erroneous Feedback, Proc. IEEE Globecom 2006, (2006).
P. Almers, T. Santos, F. Tufvesson, A. F. Molisch, J. Karedal, and A. J. Johansson, Measured Diversity Gains from MIMO Antenna Selection, Proc. IEEE VTC 2006 fall 1-6 (2006)
H. Zhang, A. F. Molisch, D. Gu, D. Wang, and J. Zhang, Implementing Antenna Selection in Wireless LAN, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2006, Las Vegas, NV, April 6-7, 2006.
P. Sudarshan, N. B. Mehta, A. F. Molisch, and J. Zhang, Channel Statistics-Based Joint RF-Baseband Design for Antenna Selection for Spatial Multiplexing, Proc. IEEE Globecom 2004, 3947 3951 (2004).
P. Sudarshan, N. B. Mehta, A. F. Molisch, and J. Zhang, Spatial Diversity and Channel Statistics-Based RF-Baseband Co-design for Antenna Selection, Proc. 60th IEEE Vehicular Techn. Conf.,, invited paper, 1658 - 1662 (2004).
P. Sudarshan, N. B. Mehta, A. F. Molisch, and J. Zhang, Antenna Selection with RF Pre-Processing: Robustness to RF- and Selection- Non-Idealities, Proc. IEEE Radio and Wireless Conf. (RAWCON) 2004, 391 394 (2004).
X. Zhang, A. F. Molisch, and S. Y. Kung, Phase-shift-based antenna selection for MIMO channels, Proc. IEEE Globecom 2003, 1089-1093 (2003).
Y. S. Choi, A. F. Molisch, M. Z. Win, and J. H. Winters, Fast antenna selection algorithms for MIMO systems, (invited) Proc. 58th IEEE Vehicular Techn. Conf., 1733 - 1737 (2003).
A. F. Molisch, X. Zhang, S. Y. Kung, and J. Zhang, FFT-based Hybrid Antenna Selection Schemes for spatially correlated MIMO channels,Proc. IEEE Symp. Personal Indoor Mobile Radio Comm 2003, 1119-1123 (2003).
A. F. Molisch, MIMO systems with antenna selection an overview, (invited), Proc. IEEE Radio and Wireless Conf. (RAWCON) 2003, 167-170 (2003).
A. F. Molisch, M. Z. Win, and J. H. Winters, Performance of Reduced-Complexity Transmit/Receive-Diversity Systems, Proc. IEEE Int. Conf. Wireless Personal Multimedia Comm. 2002, 738-742 (2002).
A. F. Molisch, M. Z. Win, and J. H. Winters, Reduced-Complexity Transmit/Receive-Diversity Systems , Proc. 53rd IEEE Vehicular Techn. Conf., 1996-2000 (2001).
A. F. Molisch, M. Z. Win, and J. H. Winters, Capacity of MIMO systems with antenna selection , Proc. IEEE ICC 2001, 570-574 (2001).
43 2010 A. F. MolischAntenna selection
Andreas F. Molisch
Ph.D., FIEEE, FIETHead, Wireless Devices and Systems (WiDeS) GroupCommunications Sciences Institute, Dpt. Of Electrical EngineeringViterbi School of EngineeringUniversity of Southern California (USC)Los Angeles, CA, USA
Email: Andreas.Molisch@ieee.orgWebsite: wides.usc.edu
Acknowledgement: some slides in this presentation are based on cooperations withDr. N. B. Mehta (IISc), Dr. J. Zhang (MERL), Dr. F. Tufvesson (Lund Univ.), Dr. H. Zhang (Marvell), Dr. X. Zhang (Princeton)
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