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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
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
3and CommunicationsSchool of Computing
1. System Parameters and Performance Analysis
and CommunicationsSchool of Computing
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
and CommunicationsSchool of Computing
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
and CommunicationsSchool of Computing
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
and CommunicationsSchool of Computing
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'''''
and CommunicationsSchool of Computing
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
and CommunicationsSchool of Computing
Problem Formulation
10and CommunicationsSchool of Computing
๏ 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
10and CommunicationsSchool of Computing
๏ 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)
Pro$it'@'No.'of'video'layers'recovered'by'any'of'the'users
Cost'@'No.'of'transmissions'needed
Problem Formulation
10and CommunicationsSchool of Computing
๏ We define the indicator variable User will recover the first service layers (at least) with probability if any of the windows are recovered (at least) with probability .
�u,` = I
L_
i=`
Pu(N1:i) � Q
!.
u `Q `, `+ 1, L
Q
(UEP-RAM) max
m1,...,mL
N1,...,NL
UX
u=1
LX
`=1
�u,`. LX
`=1
N` (1)
subject to
UX
u=1
�u,` � U ˆt` ` = 1, . . . , L (2)
0 N` ˆN` ` = 1, . . . , L. (3)
Pro$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.
11and CommunicationsSchool of Computing
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
12and CommunicationsSchool of Computing
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'
Heurist ic Procedure1. The value of is initially set to . We try to transmit only
window
2. MCS of window is accommodated via
12and CommunicationsSchool of Computing
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'
Total'no.'of'windows
Heurist ic Procedure1. The value of is initially set to . We try to transmit only
window
2. MCS of window is accommodated via
12and CommunicationsSchool of Computing
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'
No.'of'windows'to'be'skipped'
Total'no.'of'windows
3. Analytical Results
and CommunicationsSchool of Computing
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.)
and CommunicationsSchool of Computing
max
m1,...,mL
UX
u=1
LX
`=1
˜�u,`
Numerical Results
15and CommunicationsSchool of Computing
๏ 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
16and CommunicationsSchool of Computing
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
17and CommunicationsSchool of Computing
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
and CommunicationsSchool of Computing
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.
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Thank you for your attention
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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
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