Antenna Selection FTW 2010 Posting

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


Contents

Introduction and motivation

Performance analysis

Effect of nonidealities

Training

RF preprocessing

Results in measured channels

Hardware aspects

Summary and conclusions


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


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


Contents

Introduction and motivation



Training

RF preprocessing


Hardware aspects



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


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 .


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


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


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


Contents

System model



Training

RF preprocessing


Hardware aspects



Channel Estimation Error -

Diversity

ideal channelestimation

cdf

(C)

capacity C [bits/s/Hz]7 8 9 10

1

110

0.5

noisy antennaselection


noisy TX weights


noisy TX weightsnoisy RX weights

ideal channelestimation


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


Contents

System model


Antenna selection algorithms


Training

RF preprocessing


Hardware aspects



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


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


Impact of outdated training

Outdated CSI leads to error floor

Analytical consideration: 1-out-of-N selection


Estimation, selection, reception


Closed-form expression of SEP


Optimal weights


Simulation results


Contents

System model




Training

RF preprocessing


Hardware aspects



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


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


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


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


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


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


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


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


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


Contents

System model




Training

RF preprocessing


Hardware aspects



Measurement setup

Measure channel for Personal Area Networks

Use access point, PC, and handheld


Diversity gain


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.


Contents

System model




Training

RF preprocessing


Hardware aspects



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)


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


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


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


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).


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).


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: [email protected]: 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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