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Aduwati Sali Supervisors: Prof. Barry Evans, Dr. Guray Acar Adaptive Approach in Reliable Multicast Transmission over Geostationary Satellite Networks
Transcript
Page 1: Adaptive Approach in Reliable Multicast Transmission over ...info.ee.surrey.ac.uk/CCSR/Internal/Presentations/Aduwati.Sali.pdf · RAN Internet Gateway GPRS Support Node GGSN MCS Multicast

Aduwati Sali

Supervisors: Prof. Barry Evans,

Dr. Guray Acar

Adaptive Approach in Reliable Multicast

Transmission over Geostationary

Satellite Networks

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2

Presentation Outline

• Challenges and objectives

• Adaptive forward scheduling

• Channel State Information (CSI) collection and suppression

• Integrated channel-aware scheduling

• Multicast link adaptation

• Conclusion

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3

Challenges in reliable multicast

transmission

• retransmission cycles sensitive to the actual loss experienced by the terminals

• inefficient resource utilisation in the forward link

• increase in the traffic load in the return link due to feedback implosion

• numbers of terminals increase, the problem exacerbates

System Architecture:

RAN

user link

MTMFTP

Client

MTMFTP

Client

MT

MFTP

Client

feeder link

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4

Multicast File Transfer Protocol (MFTP) over BGAN

MFTP

Server

System Architecture:

RAN

Internet

Gateway GPRS

Support Node

GGSN

MCSMulticast Control Server

C-band

feeder link

L-band

user link

MTMFTP

Client

MTMFTP Client

MT

MFTP

Client

Adaptive forward scheduling: CAS, ADT (Chap. 4)

Multicast link adaptation (Chap. 7)

Change detection mechanism: CD (Chap. 5)

Integrated channel-aware scheduling:

CAS+CD (Chap.6)

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5

Channel model

• 2-state model from an L-band Land Mobile Satellite (LMS) Inmarsat satellite network

• Fading duration follows lognormal distribution, LOS duration follows power law distribution

• In ns2, output is time-varying Eb/No, , or PER, p

• Propagation environments: suburban and wooded areas

2-state model Determine

current state Calculate

Eb/No,

Determine

BER,

Calculate

PER,p

BER

Sent back to the RAN

(Chapter 7)

Sent back to the RAN

(Chapters 4-6)

γ

γφ

Lp )1(1 φ−−=

γ

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6

Adaptive Forward Scheduling algorithms

MFTP

Server

System Architecture:

RAN

Internet

Gateway GPRS

Support Node

GGSN

MCSMulticast Control Server

C-band

feeder link

L-band

user link

MTMFTP

Client

MTMFTP Client

MT

MFTP

Client

Adaptive forward scheduling: CAS, ADT (Chap. 4)

Aim: Increase forward resource utilisation

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7

Channel Aware Scheduler (CAS) Algorithm

Probability of retransmission from reported CSI,

Threshold probabilityfrom reported CSI,

1. Concept: resume transmission when terminals are perceived in good channel conditions

2. Input: Channel State Information (CSI) from terminals: PER, p3. Scheduling parameters: prtx and prtxthresh

4. Scheduling decision: to place packet in the current slot for transmission or not

∏=

−−=N

j

jpprtx

1

)1(1

Njpprtxthresh )1(1 −−=

prtxthreshprtx ≤If true, then transmit, if not, defer transmission by one

slot

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8

Adaptive Downlink Transmission (ADT) algorithm

1. Concept: adaptively set transport layer flow rate according to the estimated probability of retransmission

2. Input: CSI from terminals: PER, p3. Scheduling parameter: prtx 4. Scheduling decision: to set flow rate, η, from the MFTP

server

[bps]

Legend: L forward bearer size (in bits)

tRTT round trip time (in seconds)

BMax maximum transmission rate (bps)

( )

+

+

=

23218

312

3

2

,min

prtxprtxprtxprtx

t

LB

RTT

Maxη

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9

CAS and ADT performance:

retransmitted DTUs vs. N

Worst-case scenario, math. approx.

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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10

CAS and ADT performance: session

duration vs. N

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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11

Conclusion – Adaptive forward

scheduling algorithms

• ADT: marginally fewer retransmitted DTUs

• CAS: significantly lower session durations

• The difference between mathematical

approximations and the simulation results are due

to:

(i) lack of scheduling impact

(ii) worst-case channel conditions representation (iii) lack of impact on how CSI is collected

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12

CSI Collection and Suppression Policy

MFTP

Server

System Architecture:

RAN

Internet

Gateway GPRS

Support Node

GGSN

MCSMulticast Control Server

C-band

feeder link

L-band

user link

MTMFTP

Client

MTMFTP Client

MT

MFTP

Client

CSI Collection and Suppression Policy

using Change detection mechanism: CD (Chap. 5)

Aim: Reduce feedback implosion in the return link

due to CSI updates

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13

Change Detection (CD) mechanism

for CSI collection policy

0

V seconds consists of

measurements of pj

Observation

window,

Reference

window,

t-V seconds

consists of R0

measurements of

pj

t

1. Concept: Each terminal access uplink slot to update its CSI if it decides that sufficient CSI change is observed

2. Input: CSI from terminals: PER, p, from 2 window frames: reference( ) and observation window ( )

3. Change detection decision: access uplink slot if

Legend: V observation window size (in seconds)average PER from observation windowaverage PER from reference window size

Gamma minimum CSI variation threshold to qualify for updates

0θ̂ 1θ̂

0θ̂

1θ̂

Gamma≥− 10 θθ

0θ̂

1θ̂

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14

Comparison of CSI collection policy

vs. periodic CSI updates

PROP. TYPE

SESSION

DURATION

NUMBER OF

RETRANSMITTED

DTUs

CHANGE DETECTION

RATE

(ratio of CSI updates over number

of periodic CSI updates x 100%)

GAIN

(+/- %)

GAIN

(+/- %)

GAIN

(+/- %)

Suburban area

(PT1)

-0.11% -5.12% +32%

Wooded area

(PT3)

-0.94% -8.46% +20%

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15

Conclusions – CSI collection policy

• Combination of CD and CAS: reduce feedback volume per

terminal; up to 32% reduction compared to the periodic CSI

collection policy.

• Stabilises return link at little penalty on forward link performance

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16

Integrated Channel-Aware Scheduling

MFTP

Server

System Architecture:

RAN

Internet

Gateway GPRS

Support Node

GGSN

MCSMulticast Control Server

C-band

feeder link

L-band

user link

MTMFTP

Client

MTMFTP Client

MT

MFTP

Client

Integrated channel-aware scheduling:

CAS+CD (Chap.6)

Aim: model mathematical approx. when

both forward link and return link proposals

are simulataneously implemented

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17

Integrated channel-aware scheduling1. Concept: Mathematical approach to characterise

performance metrics considering integrated CAS-CD

mechanism

2. Central idea: Suppression error, perror, due to non-

periodic CSI updates is represented in performance metrics estimation

3. Suppression error directly influences scheduling

performance

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18

Performance evaluations –Integrated CAS

Number of terminals, N

- With suppression

- No suppression

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUsSlot size, L: 3000 bits

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19

Performance evaluations –Integrated CAS

- With suppression

- Without suppression

Number of terminals, N

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUsSlot size, L: 3000 bits

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20

Conclusions – Integrated channel-

aware scheduling

• Simulation and mathematical results approach agreement at large numbers of terminals

• The mathematical approximations capture error due to the suppression occurrence only.

• There are other errors which can be analysed and used in the mathematical approximations, such as

(i) collision errors which might reduce the number of CSI updates reaching the RAN, and

(ii) inaccuracy in reported CSI value due to propagation delay

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21

Multicast Link Adaptation

MFTP

Server

System Architecture:

RAN

Internet

Gateway GPRS

Support Node

GGSN

MCSMulticast Control Server

C-band

feeder link

L-band

user link

MTMFTP

Client

MTMFTP Client

MT

MFTP

Client

Multicast link adaptation (Chap. 7)

Aim: to increase resource

utilisation, fairness and terminal

throughput

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22

Other link adaptation technique for

multicast transmission

]})1(

1{[maxarg:1,

∏−

−+=

i tj

l

RT

rlMPF

}{minarg: ljj

lMIN γγ ≥=∗

}{maxarg: ljj

lMAX γγ ≥=∗1. Based on the best terminal,

2. Based on the worst terminal,

3. Multicast Proportional Fair,

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23

Proposed optimal algorithm: Multicast

Link Adaptation (MLA)

1. Output: Optimal transmission rate, l* by finding the solution to 0-1 multiple knapsack formulation:

Z = subject to and

2. Heuristic solution: transmission rate which maximises total terminal throughput

,maxarg ∑∑N

j l

ljl xr lj rr ≥

=otherwise

rrifx

lj

lj,0

,1

}:{,maxarg lj

i

l jirl γγ ≥∈= ∑∗

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24

Session duration distribution, N = 20

terminals

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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25

Simulation results – retransmitted

DTUs vs N

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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26

Simulation results – total number of

slots vs. N

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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27

MLA vs. MIN algorithms

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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28

Performance Comparison – Multicast

link adaptationLINK

ADAPTATION

ALGORITHM

SESSION DURATION FAIRNESS FORWARD

RESOURCE

UTILISATION

MLA Moderate. Good

especially in wooded

propagation

environment (robust

channel conditions) and

when large numbers of

terminals are considered

Excellent fairness as

the discrepancy of

session duration

performance between

the terminals with the

best and the worst

channel conditions are

small

Excellent (lowest

number of physical

bearer slots in the

forward link) in

wooded propagation

environment (robust

channel conditions) and

when large numbers of

terminals are considered

MIN Moderate. Good in

suburban propagation

environment and at low

numbers of terminals

Good Good (lowest physical

bearer slots in the

forward link) in

suburban propagation

environment and at low

numbers of terminals

MAX Excellent Very poor Very poor

MPF Poor Very poor Very poor

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29

Main conclusions

• CAS algorithm increases resource utilisation in the

forward channel

• CSI collection policy - CD mechanism reduces load in

the return link

• Mathematical approximations - suppression error in agreement with simulation results

• MLA algorithm is more robust and fair performance

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30

Future Work

• Better analytical study by considering

- scheduling impact

- collision in return link

- channel variation

• Adaptive slot allocation in multicast link adaptation for transmission of multiple multicast streams

• Combination with intelligent-based approach in

optimising resource allocation

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31

PublicationsJournal:

1) G.Giambene, S. Giannetti, C. P. Niebla, M. Ries, A. Sali, ‘Traffic Management in HSDPA via GEO Satellite’, Special Issue on Satellite Network for Mobile Services, International Journal of Space Communications, Volume 21, Number 1-2 / 2007, pp51-68

Book Chapter:

1) G.Giambene, K. P. Niebla, V. Y. H. Kueh, A. Sali, et al. "Access Schemes and Scheduling Techniques," Adaptive Resource Management and Optimization in Satellite Networks: Optimization and Cross-Layer Design’, Chapter 5, pp. 119-175, Springer, Apr. 2007, ISBN 978-0-387-36897-9

Conferences: (8 in total)

• A. Sali, G. Acar, B. G. Evans, G. Giambene, ‘A Comparison of Multicast Adaptive Techniques in Reliable Delivery over GEO Satellite Networks’, IEEE 69th Vehicular Technology Conference VTC2009-Spring 26–29 April 2009, Barcelona, Spain

• G. Fairhurst, G. Giambene, G. Giannetti, C. Parraga, A. Sali, ‘Multimedia Traffic Scheduling in DVB-S2 Networks with Mobile Users’, International Workshop on Satellite and Space Communications 2008 IWSSC’08, Toulouse, 1st – 3rd October 2008, pp211-215

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32

Publications• A. Sali, G. Acar, B. G. Evans, G. Giambene, ‘Channel-Aware Scheduling Algorithms with

Channel Prediction for Reliable Multicast Data Transmission over Geostationary Satellite

Networks’, International Workshop on Satellite and Space Communications 2008 IWSSC’08,

Toulouse, 1st – 3rd October 2008, pp85-89

• A. Sali, G. Acar, B. Evans, G. Giambene, ‘Change Detection Mechanism in Feedback

Implosion Suppression Algorithm for Reliable Transmission of Multicast Data over

Geostationary Satellite Network’, 26th AIAA International Communications Satellite Systems

Conference (ICSSC-2008), San Diego, 10th -12th June 2008

• A. Sali, G.Acar, B.Evans, G.Giambene, ‘Feedback Implosion Suppression Algorithm for

Reliable Multicast Data Transmission over Geostationary Satellite Networks’, International

Workshop on Satellite and Space Communications 2007 IWSSC’07, Salzburg, 12th-14th

September 2007, pp139-144

• A.Sali, G.Acar, B.Evans, ‘A Cross-Layer Approach for Packet Scheduling in reliable Multicast

Data Transmission over Geostationary Satellite Networks’, IEEE 65th Vehicular Technology

Conference VTC2007, Dublin, 23rd-25th April 2007, pp1395-1399

• A.Sali, G.Acar, B.Evans, ‘A Channel-Aware Scheduler with Feedback Implosion Suppression

in Reliable Multicast Data Transmission over Geostationary Satellite Networks’, 25th AIAA

International Communications Satellite Systems Conference (ICSSC-2007), Seoul, 10th -13th

April 2007

• A. Sali, A.Widiawan, S. Thilakawardana, R. Tafazolli, B. Evans, 'Cross-Layer Design

Approach for Multicast Scheduling over Satellite Networks’, Wireless Communication

Systems, 2005, 2nd International Symposium on, 5-7 Sept. 2005, pp701- 705

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33

Thank you.

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34

EXTRA SLIDES…

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35

Background

1. 2 reliability aspects; full reliability or partial-

reliability

2. Full-reliable multicast transmission is

considered throughout this presentation where

the mobile terminals (MTs) are subject to

fluctuating channel conditions

3. Feedback-based transport protocol initiates

retransmission of lost packets until all users

receive the exact copy of the original data.

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Performance metrics characterisation

1. Estimated retransmitted DTUs, A

2. Session duration in seconds, sd

[no. of DTUs]RTTthresh

Max

DTU tKB

LAM⋅+≤+⋅

⋅+)]Pr(1[

)(γγCASsd

=

][

)

))ˆ321(ˆ8

ˆ312

3

ˆ2(

,min(

)(

][)(

2

s

rtxprtxprtxprtxp

t

L

T

L

LAM

stKLAM

sd

RTT

Slot

DTU

RTT

DTU

ADT

++

×+=

⋅+×+

( ) ( )( )

−−−⋅⋅= ∑

=

+K

k

Nk

DTUj

Nk

DTUj ppkMA0

111

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37

Change Detection (CD) mechanism for CSI collection policy

0

V seconds consists

of measurements

of pj

Observatio

n window,

Reference

window,

t-V seconds

consists of R0

measurements

of pj

t

1. Concept: Each terminal access uplink slot to update its CSI if it decides that sufficient CSI change is observed

2. Input: CSI from terminals: PER, p, from 2 window frames: reference( ) and observation window ( )

3. Change detection decision: access uplink slot if

Legend: V observation window size (in seconds)average PER from observation windowaverage PER from reference window size

Gamma minimum CSI variation threshold to qualify for updates

0θ̂ 1θ̂

0θ̂

1θ̂

Gamma≥− 10 θθ

0θ̂

1θ̂

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38

0.001 0.002 0.0030

200

400

600

800

Gamma

Num

ber

of M

FT

Ppa

cket

s re

tran

smitt

ed

0.001 0.002 0.0030.9

0.92

0.94

0.96

0.98

1

Gamma

Dow

nlin

k re

sour

ce u

tiliz

atio

n

0.001 0.002 0.003600

620

640

660

680

Gamma

Ses

sion

dur

atio

n (s

)

0.001 0.002 0.0030

0.2

0.4

0.6

0.8

1

Gamma

Cha

nge

dete

ctio

n ra

te

Impact of CSI variation threshold, Gamma and

observation window size, V (suburban area)

Obs. Window size, V = 0.08s Obs. Window size, V = 0.16s Obs. Window size, V = 0.4s

File size: 10MBNo. of DTUs in the first cycle: 7364 DTUs

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39

Feedback implosion suppression (FIS)1. Concept: The RAN decides which terminal should

access the uplink slot for CSI updates based on CSI change, last update duration, and NACK availability.

2. Input: CSI from terminals: and , transport layer ACK/NACK, database on update timer

3. FIS decision: Based on Multiple Subset Sum Problem (MSSP) formulation:

max subject to where

4. Solution: terminals with S highest rj will be selected to access the uplink slots.

5. Only a subset of terminals will be selected:

0θ̂ 1θ̂

∑∑= =

S

i

N

j

jij xr1 1

iRxr Max

N

j

jij ∀≤∑=

,

1

jUpdate

j

j

j tr ,∆×=φ

ω

}1:{ == njxjN

(

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40

FIS performance evaluations

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41

Performance evaluations

• Change detection (CD) mechanism: fixed-size observation

window and a growing reference window performed the best

in terms of session duration with tolerable suppression gain.

• Combination of CD and CAS: reduce feedback volume per

terminal; up to 32% reduction compared to the periodic CSI collection policy.

• Feedback implosion suppression (FIS) mechanism: able to support not only on the proper arrival of CSI updates, but

also in the absence of suppression problem.

• Combination of FIS and CAS: use of dedicated uplink slots

for selected terminals reduce CSI inaccuracy due to collision

problem

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42

Multicast link adaptation

(dB)

Equivalent

(dB)

Forward

bearer

sub-type, l

Payload

size, L

(bits)

Payload

duration

(s)

Average

transmission rate

(kbps)

3.92 -2.10 L3 2000 0.01 200.0

4.85 -1.17 L2 2320 0.01 232.0

5.81 -0.21 L1 2664 0.01 266.4

6.71 0.69 R 3000 0.01 300.0

7.84 1.82 H1 3440 0.01 344.0

8.90 2.88 H2 3840 0.01 384.0

9.88 3.86 H3 4224 0.01 422.4

10.97 4.95 H4 4640 0.01 464.0

11.92 5.90 H5 4920 0.01 492.0

12.99 6.37 H6 5120 0.01 512.0

os NEob NE

*Wideband 16-QAM bearer operating at a symbol rate of 151.2 ksym/s

Link Adaptation Table: Forward link vs. bearer type

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43

Performance comparison

]})1(

1{[maxarg:1,

∏−

−+=

i tj

l

RT

rlMPF

}{minarg: ljj

lMIN γγ ≥=∗

}{maxarg: ljj

lMAX γγ ≥=∗

Comparison with other multicast link adaptation techniques:

1. Proposed MLA:

2. Based on the best terminal,

3. Based on the worst terminal,

4. Multicast Proportional Fair,

}:{,maxarg lj

i

l jirl γγ ≥∈= ∑∗

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44

Transmission rate vs. no. of terminals

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45

Session duration vs. no. of terminals

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46

Performance Evaluations


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