Presentation Feb 10

8/12/2019 Presentation Feb 10

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Performance of LTE system

(Different MCS in different speed)

modick

Feb 10, 2014


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Channel Model

Propagation model is defined channel impulseresponse.

Channel response defines the behavior ofchannel in terms of channel power delay

profile i.e. tap delay and absolute power atdelayP().

Coherence time of fading channel =

wherefmis maximum doppler

frequency

1 2 3 4

P(1)

P(2)

P(3)

P(4)

1

2 2c d c

c

T f vf


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Channel Model

If the symbol duration > coherence time (Tc)

then it is called fast fading otherwise it is

called slow fading or block fading.

LTEs useful symbol duration is 66.67sec.

Fast fading channel frequency dispersion due

to Doppler spreading is

In slow fading channel dispersion (change in

channel impulse response) is less within the

symbol duration.


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Channel Model

rms delay spread of a channel delay profile is

defined as

Rms delay spread can used to definecoherence bandwidth

If channel bandwidth then it flat fading,

which means channel response remainsconstant otherwise it is known as frequencyselective fading.

2 2

2 2 2

2

2

( )

( )

( )

k k k k

k k

kk

kk

a P

wherePa

1 5cB

S cB B


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Channel Model


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Intersymbol Interference (ISI)

If we considerx[m]as input signal, h[m]ischannel response,y[m]are output signal andw[m]is noise.

if m= 3 andL= 3 (Lis Channel length)then,

we can see previous symbolsx[2] andx[1] isaffectingy[3].

Equalizing is one method used to reduce ISI.

1

0

[ ] [ ]* [ ] [ ], 0

[ ] [ ] [ ] [ ], 0

L

l

y m h m x m w m m

y m h l x m l w m m

[3] [0]. [3] [1].x[2] [2]. [1] [3]y h x h h x w


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Equalization It is a method to guess channel delay profile

and cancel out the channel effect. Ify[n] are signal received and d[n]are desired

signal then square of error e[n] = (y[n]-d[n])2.

ify[n] is output of received signal r[n] afterpassing through filter (i.e. equalizer)g[n] of

lengthM.

MMSE will try to minimize MSE w.r.t. g[m],m=0,1, ,M-1

LS equalizer will find weights that minimizes

1

[ ] [ ] [ ]M

m

y n r n g n m

2

2

1

[ ] [ ] [ ]M

k

m

MSE E e E d n r n g n m

2

2

1 1

[ ] [ ] [ ]K M

kk m

e d n r n g n m


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Different Equalizers [1]

The equalizer can perform for the block fading and fastfading.

Utilizing Block fading equalizer means considering onlyone time estimation of channel per a transmission

block. Fast fading equalizers consider the fact that the

channel are changing rapidly within a single block anduse multiple pilots symbols.

[1] has shown that the performance of fast fadingequalizers are very robust till 100km/hr. [Link]

Performance of LS block equalizers are not perfect inthe range of 0-120 km/hr.


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ITU Channel Model

LTE use ITU channel models to simulate the performance of

the system.

P1, P2, , P3 are the path gains given by the channel models

such as Extended Vehicular Channel (EVA), Extended

Pedestrian Channel (EPA), Typical Urban (TU) etc.

TN

T5

T4

T1

T2

T3

Z-1 Z-1 Z-1 Z-1 Z-1

P1

P2

P3

P4

P5

PN

IN

Choose Doppler Spectrum

1. Flat

2. Rounded or

3. Jake

+

**

**

* *


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Extended ITU Pedestrian Model (PedA)

TapRelative delay

(ns)

Average

power (dB)

Doppler

spectrum

1 0 0 classic

2 30 -1 classic

3 70 -2 classic

4 80 -3 classic

5 110 -8 classic

6 190 -17.2 classic

7 410 -20.8 classic

Extended ITU Vehicular (VehA)

TapRelative

delay (ns)

Average

power (dB)

Doppler

spectrum

1 0 0 classic

2 30 -1.5 classic

3 150 -1.4 classic4 310 -3.6 classic

5 370 -0.6 classic

6 710 -9.1 classic

7 1090 -7 classic

8 1730 -12 classic

9 2510 -16.9 classic

Extended ITU Typical urban (TU)

Tap

Relative delay

(ns)

Average power

(dB)

Doppler

spectrum

1 0 -1 classic

2 50 -1 classic

3 120 -1 classic

4 200 0 classic

5 230 0 classic

6 500 0 classic

7 1600 -3 classic

8 2300 -5 classic9 5000 -7 classic

ITU Channel ModelITU channel model has three types

of channel defined for Pedestrian(PedA), Vehicular(VehA) and Typical

Urban (TU) environments.

The relative delay and average tap

power is also defined in the

standards.

The Doppler Spectrum is Classical

modelor ClarkeGilbert Model[1]


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Channel Simulation Methodology

Discrete Multipath Channel ModelA discrete multipath channel model is tapped delay line

(TDL) whose impulse response can be defined as

where is complex channel coefficients and arethe time varying delays.

For time invariant case and

( )

1

( ( ), ) ( ( ), ). ( ( ))K t

k k k

k

c t t a t t t

( ( ), )k ka t t ( )k t

( ) KK t ( )k kt ( )

1

( , ) ( ). ( ( ))K t

k k

k

c t a t t


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Fading Channel Model


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Doppler Filtering: Generates desired Dopplerpower spectrum.

Jakes Doppler Spectrum:

Flat Doppler Spectrum

Gaussian Doppler Spectrum

2

1/4

1/4

1( ) ,

1 ( )

[ ] (3 / 4) (2 (m M/ 2) t ),for 0,1, , 1(m M/ 2)t

j d

d d

d

j d s

s

S f f f f f f

fh m J f m M

1( ) ,

2

[ ] 2 sin (2 (m M/ 2) t ), for 0,1, , 1

f d

d

f d d s

S f f f f

h m f c f m M

2

22

1/4 2 2 2

1( ) exp

22

[ ] (2 ) exp( 4 ((m M/ 2) t ) ), for 0,1, , 1

g

gg

g g s

fS f

h m m M


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In order to reduce the Gibbs phenomenonattributed by truncation, the sampled impulseresponses are multiplied with windows

(e.g. Hamming Window) and then normalized.

After Windowing, Fading process isInterpolation filter with sampling rate 2maximum Doppler shift giving filtercoefficients .

[ ]Dh m [ ]w m

1 2

0

[ ] [ ] [ ]

[ ] [ ] [m]

w D H

M

norm w wm

h m h m w m

h m h m h

[ ]kz n


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Path Gain Scaling: Path Scaling is done using

the factor which is Doppler power

spectrum which gives

Where Rician fading factor on the path k

and phase shift.

2( )k kE a t

, , ,(2 ),

,,

[ ][ ] 1,2, , .

11

d LOS k LOS k j fr Kk

k k

r Kr K

Kz na n e for k K

KK

,r KK

, ,d LOS kf


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BLER and Throughput

BLER is the ratio of number of correct block

received to the total number of block sent.

Number of block transmitted is defined by the

MCS, Bandwidth, Number of subcarriers,

Number of Resource Blocks and Antenna

Configuration.

Maximizing Throughput is the main objective

of LTE (LTE-A) system [1].


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Number of Blocks

Bandwidth: 1.4, 3, 5,10, 15, 20 MHz but only 90% is

used because 10% is used for guard band (except 1.4

MHz)

Since LTE has 15 KHz sub carrier spacing. For 20

MHz then effective bandwidth = 90% of 20MHz = 18 KHz.Number of subcarriers = 18 MHz/ 15 KHz

Number of Resource Blocks = 18 MHz/ 180 KHz = 100 [1 RB =

12 subcarrier x 7 OFDM symbols]

1.4 MHz 3 MHz 5 MHz 10 MHz 15 MHz 20 MHz

Effective BW allocated 72 180 300 600 900 1200

Theroretical number of

subcarriers

~93.3 200 ~333.3 ~666.6 1000 ~1333.3

Number of occupied

subcarrier

72

6 RB

180

15 RB

300

25 RB

600

50 RB

900

75 RB

1200

100 RB


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MCS defines the Modulation Scheme (QPSK,

16 QAM, 64 QAM) and Code Rate. MCS is

defined by Channel Quality Index (CQI).

Antenna configuration (Category 1-8) defines

maximum MIMO layers. 8 being the highesttill Release 10.

Number of Blocks / Throughput


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Relation Between Throughput and BLER

According to [4], The spectral efficiency

(Throughput) = (1BLER).maximumthroughput

Note: Results were converted from

Throughput to BLER.


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Parameters Used [3]

Bandwidth 1.4 MHz

User Velocity (km/h) 0, 20, 40, 60, 80, 100,120

CQI 1, 2, 4, 6, 8, 10,12,15

Channel Type ITU VehA

Number of subframes 500SNR (dB) -5 to 45

Configuration Mode 3 (Open Loop Spatial Multiplexing (OLSM))

Equalizer Least Square (LS) for block fading

Fading Model Fast Fading (Block Fading model still needs

simulations [Future work])

Number of transmit antennas 4

Number of received antennas 2

Different Transmission Modes of LTE

Note: results can be generated using LTE_sim_batch_michal_wsa_2010 script file mentioned in [3]


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Results (CQI 01)

0

0.2

0.4

0.6

0.8

1

1.2

-6 -5 -4 -3 -2 -1 0 1 2 3 4

BLER

SNR (dB)

BLER Performance for different velocity for CQI 01

0

20

40

60

80

100

120


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Results (CQI 02)

0

0.2

0.4

0.6

0.8

1

1.2

-6 -5 -4 -3 -2 -1 0 1 2 3 4

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 04)

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8 9

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 06)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25 30

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 07)

0

0.2

0.4

0.6

0.8

1

1.2

6 8 10 12 14 16 18 20 22 24 26

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 08)

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

10 15 20 25 30 35 40

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 10)

0

0.2

0.4

0.6

0.8

1

1.2

12.5 14.5 16.5 18.5 20.5 22.5

BLER

SNR (dB)


0

20

40

60

80

100

120


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Results (CQI 12)

0

0.2

0.4

0.6

0.8

1

1.2

18 23 28 33 38 43

BLER

SNR (dB)


0

2040

60

80

100

120


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Results (CQI 15)

0

0.2

0.4

0.6

0.8

1

1.2

25 30 35 40 45

BLE

R

SNR (dB)


0

20

40

60

80

100

120


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Discussion Higher CQI value have more information carrying capacity

due to less coding and higher modulation order.

Higher CQI value means it has more modulation bit persymbols (i.e. For CQI 1-6 (QPSK), For CQI 7-9 (16QAM) andFor CQI 10-15 (64QAM)).

The performance against noise and Doppler fading will beQPSK>16QAM>64QAM

Information per symbol carrying capacity 64QAM > 16QAM> QPSK [7].

The increase in value of CQI will reduce the Cyclic

Redundancy Code bits hence, higher code rate as Alowercode rate means the more redundancy bits are insertedduring the channel coding process and a higher code ratemeans that less redundancy bits are inserted.

X


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Throughput vs. speed [2]

0 50 100 150 200 250 300

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

User Speed [km/h]

Throughput[Mb

its/s]

LS block (CQI 10)

LS block (CQI 08)

LS block (CQI 04)LS block (CQI 02)

LS block (CQI 01)

Bandwidth 1.4 MHz

Speed 0-300 km/h

CQI 1, 2, 4, 8, 10

Receiver Type SSD

Channel Type ITU VehA

Number of subframes 500

Fading Type Block fading

SNR 20 dB


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References

1. R. Jain, An Overview of Long Term Evolution Advanced, download:http://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.html

2. A. Jemmali and J. Conan, PerformanceEvaluation of MIMO Schemes in 5 MHzBandwidth LTE System, The Eigth International Conference on Wireless andMobile Communications (ICWMC), Venice, Italy, June 24-29, 2012.

3. M. Simko, C. Mehlfuhrer, M. Wrulich and M. Rupp, DoublyDispersive Channel

Estimation with Scalable Complexity, Proceeding of International ITGWorkshop on Smart Antennas, Bremen, Germany, Feb, 2010.

4. B. E. Priyanto and T. B. Sorensen, Single-Carrier Transmission for UTRA LTEUplink, in .Long Term Evolution: 3GPP LTE radio and cellular technology,Auerbach, 2009, ch. 6, pp. 181212.

5. T. S. Rappaport, Wireless Communications: Principles and Practice, 2nd Ed.,Pearson publication.

6. Iskander, C. D., A MATLAB Object-Oriented Approach to Multipath FadingChannel Simulation

7. http://www.berk.tc/combas/digital_mod.pdf

8. LTE Transmission Modes and Beamforming: White Paper, Bernhard Schulz,Rohde and Schwarz
http://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www.berk.tc/combas/digital_mod.pdfhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.htmlhttp://www1.cse.wustl.edu/~jain/cse574-10/ftp/lte-adv/index.html


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Results of [3]


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Results of [3]

Back


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Different Transmission Modes In LTE

LTE has 7 transmission modes

To parameters Used

Transmission

ModeTransmission scheme

1 Single antenna port, port 0 (SISO)

2 Transmit diversity

3 Open Loop Spatial Multiplexing (OLSM) Transmit Diversity if

associated rank indicator is 1, otherwise large delay CDDCDD is a diversity scheme used in OFDM based telecommunication systems,

transforming spatial diversity into frequency diversity avoiding ISI

Can gain frequency diversity at the receiver without changing the SISO

structure.

4 Closed Loop Spatial Multiplexing (CLSM)

5 Multiuser MIMO

6 CLSM with a single transmission layer

7 If the number of PBCH antenna ports is one, Single antenna

port, port 0; otherwise Transmit diversity


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OLSM and CLSM

Precoding Matrix Indicator

d

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Presentation Feb 10