multipe-symbol sphere decoding for space-time modulation

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Multipe-Symbol Sphere Decoding for Space- Time Modulation Vincent Hag March 7 th 2005

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Multipe-Symbol Sphere Decoding for Space-Time Modulation. Vincent Hag March 7 th 2005. Why MIMO?. Limited radio resources Need for higher data rate (3G services and beyond) - PowerPoint PPT Presentation

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Page 1: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Multipe-Symbol Sphere Decoding for Space-

Time Modulation

Vincent HagMarch 7th 2005

Page 2: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Why MIMO?

• Limited radio resources• Need for higher data rate (3G services and beyond)

Make the best possible use of the spectrum in order to further increase throughput as well as user-capacity

MIMO antennas is a key technology

Page 3: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Why Multiple-Symbol Detection?

N received symbols are jointly processed to estimate N-1 symbols

Better evaluation of the channel statistics yields improved performances

Page 4: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Why Non-coherent Detection?

Phase estimation difficult or costly

Develop (de)modulation techniques that do not require CSI

Extend DPSK to MIMO systems

Page 5: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Problem Formulation

Performance(exploit space and time dimensions)

Complexity

(exponential in space and time dimensions)

Need for fast-algorithm based detection

Page 6: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Talk Outline

Transmission

Channel Model

Reception: Sphere Decoder

Simulation Results

Conclusions and Further Works

Page 7: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Transmission

Non-coherent Detection Differential Transmission

Diagonal codes (= extension of DPSK signals to STC)

Page 8: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Differential Encoding

klV

0 0

1k k k

l l

l l l

S VS V S

Code matrices are differentially encoded such as

Page 9: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Diagonal Codes

11tNu u

12

2

0 0

0 0 time

0 0

space

k

k

Nt

lj u

L

l

j u

L

Ve

e

Page 10: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Channel Model

• AWGN• Rayleigh fading• Multi-channel action:

1 1 1 10 0

0 0

0 0N N N N

R S H W

R S H W

Page 11: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Communication link

Page 12: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Catch-up slide

fast detection scheme

MIMO systems

Multiple-Symbol Sphere Decoding

for

Space-Time Modulation

Page 13: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Talk Outline

Transmission

Channel Model

Reception: Sphere Decoder

Simulation Results

Conclusions and further Works

Page 14: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Reception: Metric

Metric:

2

arg max Pr |

arg min

N

N

MLS C

MLS C

S R S

S US

ML decision rule:

Page 15: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding: Concept

Fix and examine signals such that

2 2US

S

Search of signals lying inside a sphere of radius instead of the whole space

Page 16: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding

i N?2 2 2

NN N N NU S d S

2

11 1 120

0 0

N

NN N

U U S

U S

with U upper triangular

NS 1SS can be determined component-wise,

starting from and tracking up to

Page 17: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding

1i N

?22 2 2

1 1 1 1 1 1N N N N N N N N Nd U S U S d S

2

11 1 120

0 0

N

NN N

U U S

U S

Page 18: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding

choose that minimizes to keep it as small as possible:

Partial distance criterion:

2

2 21

1

N

i i ii i ij jj i

d d U S U S

2

1

arg mini

N

i ii i ij jS C

j i

S U S U S

iS id

Page 19: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding

1i

S

radius updated to U S

Then, restart the sphere decoding algorithm with the new radius value

Page 20: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Sphere Decoding

• Phase ambiguities:

1NS fix and start sphere decoding at

• Search strategy:

Zigzag procedure: hypothetical symbols(examined for the ith component) are ordered according monotically increasing distance

1i N

iS

id

Page 21: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Zigzag for 8-PSK constellation

Page 22: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Representation in a tree

Page 23: Multipe-Symbol Sphere Decoding for Space-Time Modulation

DFDD

Attractive low-complexity algorithm performing differential detection

Linear predictor making decision onbased on and

klV

-( -1), , k k NR R ( 1, , 2)k ilV i N

Page 24: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Talk Outline

Transmission Channel ModelReception: Sphere DecoderSimulation ResultsConclusions and further Works

Page 25: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Simulation Results

• Simulation setup

• BER performances

• Computational Complexity

• BER vs. Complexity

Page 26: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Simulation Setup

• bit/channel use,

• Spatially independent Rayleigh continuous fading channels

• Detect at least 1000 bit errors to assess the BER at any SNR

• Number of multiplications as a measure of the complexity

2R 0.03dB T

Page 27: Multipe-Symbol Sphere Decoding for Space-Time Modulation

BER performances

Error floor removed

Single Antenna System

Page 28: Multipe-Symbol Sphere Decoding for Space-Time Modulation

BER performances

MSDSDvs

DFDD

3tN

Page 29: Multipe-Symbol Sphere Decoding for Space-Time Modulation

BER performances

Mismacth of the Doppler rate

4dB shiftRobust?

Page 30: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Computational Complexity

Average Number of Real Multiplicationsdone to estimate a 10-length sequence

Page 31: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Computational Complexity

( ) log ( )c NE N ANMB

Page 32: Multipe-Symbol Sphere Decoding for Space-Time Modulation

BER vs Complexity

Restrict the number of multiplications for practical reasons

Page 33: Multipe-Symbol Sphere Decoding for Space-Time Modulation

BER vs Complexity

Page 34: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Conclusion

• SD outperforms DFDD, a good low-complexity algorithms

• Excellent performance versus complexity trade-off:

• ML performances

• But orders of magnitudes below that of brute-force search (ML detection)

• Gains in power efficiency almost for free

Page 35: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Further Works

• Investigate other STC, possibly with other search strategy for PDP

• Take interference into account

Page 36: Multipe-Symbol Sphere Decoding for Space-Time Modulation

Questions?