optimized network-coded scalable video multicasting over embms networks

London, 9th June 2015

R2D2EPSRC First Grant

Scheme (EP/L006251/1)

Optimized Network-coded Scalable Video Multicasting over eMBMS Networks

IEEE ICC 2015 - Mobile and Wireless Networking Symposium

A. Tassi, I. Chatzigeorgiou, D. Vukobratović, A. L. Jones a.tassi@{lancaster.ac.uk, bristol.ac.uk}

and CommunicationsSchool of Computing

http://lancaster.ac.uk

http://bristol.ac.uk

Starting Point and Goals๏ Delivery of multimedia broadcast/multicast services over

4G/5G networks is a challenging task. This has propelled research into delivery schemes.

๏ Scalable video service (such as H.264/SVC) consists of a basic layer and multiple enhancement layers.

๏ Multi-rate Transmission (MrT) strategies have been proposed as a means of delivering layered services to users experiencing different downlink channel conditions.

Goals ๏ Error control - Ensure that a predetermined fraction of users

achieves a certain service level with at least a given probability

๏ Resource optimisation - Reduce the total amount of radio resources needed to deliver a layered service in a fair way.

2and CommunicationsSchool of Computing

Index

1. System Parameters and Performance Analysis

2. Proposed Resource Allocation Modeling and Heuristic Solution

3. Analytical Results

4. Concluding Remarks


1. System Parameters and Performance Analysis


System Model๏ One-hop wireless communication system composed of a Single

Frequency Network (SFN) and a multicast group of U users

5

๏ All the BSs forming the SFN multicast the same layered video service, in a synchronous fashion.

๏ Reliability ensured via the Unequal Error Protection RNC


BSBS

BSBS

M1/M2

(MCE / MBMS-GW)

SFN

41

23

UE3UEUUE 2

UE1UE4

LTE-A Core Network

6

๏ Encoding: (i) Source elements belonging to the same window are linearly combined, (ii) The process is repeated for all the windows, and (iii) Each stream of coded packets is multicast.

Unequal Error Protection RNC

๏ We define the -th window as the set of source packets belonging to the first l service layers. Namely, where


k1 k2 k3

x1 x2 xK. . .. . .

Window 3 of K3 source elements

Win. 2 of K2 src el.

Win. 1 of K1 src el.

` x1:`

x1:` = {xj}K`j=1

K` =P`

i=1 ki

7

UEP-RNC and LTE-A


Data$streamassociated$with$$ $

⊗⊗ ⊗⊕

TB

MAC

PHY

Data$streamassociated$with$$ $

MAC$PDUassociatedwith

x1 x2 xK. . .

gj,1 gj,2 gj,K2

. . .xK2

y1 yj. . . . . .

Source$Message

. . .

yj

v1 v2

v2

Service'layers'arrive'at'the'MAC'

layer

Coded'elements'are'generated

Coded'elements'are'mapped'onto'one'or'more'

PDUs'

๏ Window is always transmitted with the MCS ๏ Coded elements of different windows cannot be mixed within a PDU

m``

Performance Model

8

๏ A user recovers the first layers (namely, the -th window) if it collects linearly independent coded elements from windows , which occurs with probability

Prob.'of'receiving ''''''out'of' PDUs

Prob.'of'decoding'window'''''


u `K`

1, . . . , `

`

Pu(N1:`)=N1X

r1=0

· ·NX

r`=0

Y

i=1

✓Ni

ri

◆(1�pu,i)

ri pNi�riu,i g(r1:`) (1)

N1:` = {N1, . . . , N`}

`✴ A. Tassi et al., “Resource-Allocation Frameworks for Network-

Coded Layered Multimedia Multicast Services”, IEEE J. Sel. Areas Commun., vol. 33, no. 2, Feb. 2015

Sums'exploit'all'the'combinations'of'received'

coded'elements

r1:` = {r1, . . . , r`}

2. Proposed Resource Allocation Modelling and Heuristic Solution


Problem Formulation


๏ We define the indicator variable User will recover the first service layers (at least) with probability if any of the windows are recovered (at least) with probability .

�u,` = I

L_

i=`

Pu(N1:i) � Q

!.

u `Q `, `+ 1, L

Q

(UEP-RAM) max

m1,...,mL

N1,...,NL

UX

u=1

LX

`=1

�u,`. LX

`=1

N` (1)

subject to

UX

u=1

�u,` � U ˆt` ` = 1, . . . , L (2)

0 N` ˆN` ` = 1, . . . , L. (3)

Problem Formulation



�u,` = I

L_

i=`

Pu(N1:i) � Q

!.

u `Q `, `+ 1, L

Q

(UEP-RAM) max

m1,...,mL

N1,...,NL

UX

u=1

LX

`=1

�u,`. LX

`=1

N` (1)

subject to

UX

u=1

�u,` � U ˆt` ` = 1, . . . , L (2)

0 N` ˆN` ` = 1, . . . , L. (3)

Pro$it'@'No.'of'video'layers'recovered'by'any'of'the'users

Cost'@'No.'of'transmissions'needed

Problem Formulation



�u,` = I

L_

i=`

Pu(N1:i) � Q

!.

u `Q `, `+ 1, L

Q

(UEP-RAM) max

m1,...,mL

N1,...,NL

UX

u=1

LX

`=1

�u,`. LX

`=1

N` (1)

subject to

UX

u=1

�u,` � U ˆt` ` = 1, . . . , L (2)

0 N` ˆN` ` = 1, . . . , L. (3)

Pro$it'@'No.'of'video'layers'recovered'by'any'of'the'users

Cost'@'No.'of'transmissions'needed

Each'service'level'shall'be'achieved'by'a'predetermined'fraction'of'users

Target'fraction'of'users

…'within'a'certain'time.

Problem Heurist ic๏ Users provide as CQI feedback the max. MCS index ensuring

an acceptable PDU error probability (at the MAC Layer). The larger the MCS index is, the higher the modulation order or the lower the error-correcting capability is.

๏ The UEP-RAM is an hard integer optimisation problem because of the coupling constraints among variables. We proposed the following heuristic strategy.

๏ Remark Assume that the first windows are not delivered. The service coverage can only be offered if (i) service layers are recovered with a

probability of at least by the user fraction . (ii) and the remaining layers are recovered as stated in SLA.


s 2 [0, L� 1]

1, . . . , (s+ 1)Q t1

Heurist ic Procedure1. The value of is initially set to . We try to transmit only

window

2. MCS of window is accommodated via


and the PDU transmission are optimized via

3. If any of these problems cannot be solved, is decreased and the procedure repeated. Otherwise, the solution is refined.

s

L� 1L

` 2 [s+ 1, L]

s

(S1-`) argmax

m`2[1,15]

n

UX

u=1

I⇣

m` m(u)⌘

� U t0`

o

(S2-`) argminN`2[0,N`]

n

P(N1:`) � Q ^ 0 N` N`

o

Requires'a'Ginite'no.'of'steps

MCSs'and'PDU'trans.'indep.'

optimized'across'the'windows'


window





s

L� 1L

` 2 [s+ 1, L]

s

(S1-`) argmax

m`2[1,15]

n

UX

u=1

I⇣

m` m(u)⌘

� U t0`

o


n

P(N1:`) � Q ^ 0 N` N`

o




Total'no.'of'windows


window





s

L� 1L

` 2 [s+ 1, L]

s

(S1-`) argmax

m`2[1,15]

n

UX

u=1

I⇣

m` m(u)⌘

� U t0`

o


n

P(N1:`) � Q ^ 0 N` N`

o




No.'of'windows'to'be'skipped'

Total'no.'of'windows

3. Analytical Results


Numerical Results

14

๏ SFN scenario composed by 4 BSs

๏ We compared the proposed strategies with a classic Multi-rate Transmission (MrT) strategy

System'proGitNo'error'control'

strategies'are'allowed'(ARQ,'RLNC,'etc.)


max

m1,...,mL

UX

u=1

LX

`=1

˜�u,`

Numerical Results


๏ SFN scenario composed by 4 BSs, 1700 users placed at the vertices of a regular square grid placed on the playground

๏ We considered a 3-layer and a 4-layer video streams.

eNBeNB

eNBeNB

M1/M2

MCE / MBMS-GW

SFN

32

1B

UE3UEMUE 2

UE1UE4

x position (m)

yposition(m

)

−500 −300 −100 100 300 500 700

−200

−100

0

100

200

300

400

500

600

700

x position (m)

yposition(m

)

−500 −300 −100 100 300 500 700

−200

−100

0

100

200

300

400

500

600

700

3

33 3

3

3

3

3

33

2

2

2

2

2

2

2 2

2

22

1

1

1

1

1

1

11

1

1

1

1

UEP$RAMMrT

3

3

Heuris/c

Numerical Results


3@layer'stream

QoS'level'3'achieved'by'34.1%'vs.'60%'of'the'users'

QoS'level'3'achieved'by'74%'vs.'60%'of'the'users'SFN'BS

QoS'level'3

QoS'level'2

QoS'level'1

x position (m)

yposition(m

)

−500 −300 −100 100 300 500 700

−200

−100

0

100

200

300

400

500

600

700

x position (m)

yposition(m

)

−500 −300 −100 100 300 500 700

−200

−100

0

100

200

300

400

500

600

700 MrT

4

44 4

4

4

4

44

4

4

4

3

3

3 3

3

3

33

33

3

2

2

22

2

2

22

11 1

1

1

1

1

1 1

4

4UEP'RAMHeuris/c

Numerical Results


4@layer'stream

QoS'level'4'achieved'by'33.1%'vs.'60%'of'the'users'

QoS'level'4'achieved'by'65%'vs.'60%'of'the'users'SFN'BS

QoS'level'4

QoS'level'3

QoS'level'2

QoS'level'1

4. Concluding Remarks


Concluding Remarks

19

๏ We presented a viable method for the incorporation of the UEP-NC scheme into LTE-A stack as a means of improving the reliability of scalable video multicast services

๏ Inspired by a fundamental economics principle, we defined of a novel resource allocation framework that aims to improve the service coverage with a reduced resource footprint.

๏ We defined a novel heuristic strategy that can efficiently derive a good quality resource allocation solution of the considered problem.

๏ Results showed that our modeling ensures a service coverage which is up to 2.5-times greater than that of the considered conventional MrT strategy.


Thank you for your attention


For more informationhttp://goo.gl/Z4Y9YF

A. Tassi, I. Chatzigeorgiou, and D. Vukobratović, “Resource Allocation Frameworks for Network-coded Layered Multimedia Multicast

Services”, IEEE J. Sel. Areas Commun., vol. 33, no. 2, Feb. 2015

http://goo.gl/Z4Y9YF

London, 9th June 2015

R2D2EPSRC First Grant

Scheme (EP/L006251/1)

Optimized Network-coded Scalable Video Multicasting over eMBMS Networks

IEEE ICC 2015 - Mobile and Wireless Networking Symposium

A. Tassi, I. Chatzigeorgiou, D. Vukobratović, A. L. Jones a.tassi@{lancaster.ac.uk, bristol.ac.uk}


http://lancaster.ac.uk

http://bristol.ac.uk

optimized network-coded scalable video multicasting over embms networks

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