A Utility-based Mechanism for Broadcast Recipient Maximization in WiMAX Multi- level Relay Networks Cheng-Hsien Lin, Jeng-Farn Lee, Jia-Hui Wan Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan IEEE Transactions on Vehicular Technology (IEEE TVT 2012)
A Utility-based Mechanism for Broadcast Recipient Maximization in WiMAX Multi-level Relay Networks. Cheng- Hsien Lin, Jeng-Farn Lee, Jia-Hui Wan Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. - PowerPoint PPT Presentation
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A Utility-based Mechanism for Broadcast Recipient Maximization in WiMAX Multi-level Relay Networks
Cheng-Hsien Lin, Jeng-Farn Lee, Jia-Hui Wan
Department of Computer Science and Information Engineering,National Chung Cheng University, Taiwan
IEEE Transactions on Vehicular Technology (IEEE TVT 2012)
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Outline Introduction Goal Network Model and Assumption Problem specification Multi-Level Utility-based Resource Allocation (ML-URA) Simulations Conclusions
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Introduction The emergence of IEEE 802.16 WiMAX and advances in
video coding technologies have made real-time applications possible.
This paper models the resource allocation problem in IEEE 802.16j WiMAX multi-level relay networks (multi-hop) Multi-Level Broadcast Receipt Maximization (ML-BRM) problem
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Goal To propose multi-level resource allocation mechanism
Consider the multi-level relay paths and the required resource Maximize resource utilization in WiMAX multi-level relay networks
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Network Model and Assumption In a WiMAX relay network,
one MR-BS Y RSs N MSs that subscribe to a certain real-time program
This paper assumes that the real-time program, whose streaming data size is M
Resource budget: rbudget total time slots in a TDD super frame
RS0
Each RS y (1 ≤ y ≤ Y) is denoted by RSy
Each MS n (1 ≤ n ≤ N) is denoted by MSn
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Network Model and Assumption The number of time slots required to transmit a broadcast
stream varies MSs and RSs have different channel conditions MSs and RSs have different modulation schemes the transmission rates required for RSs to successfully send data also
vary
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Network Model and Assumption The transmission rate bx,y between sender x and receiver y
based on one of the channel conditions, such as the SNR value sender x: MR-BS or RS receiver y: RS or MS
The resource required by the receiver y: M/bx,y
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Network Model and Assumption RAx: a node x with the allocated resource RAx
all nodes whose required resource is not larger than RAx can receive the downlink data successfully through one downlink transmission from node x.
x
MS
MS
MS
RAx
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Network Model and Assumption For all RSs, the channel conditions are represented by
where
records the resource required by RSy to receive streaming data
from other RSs. RResy,y= 0: RSy doesn’t demand any resource from itself.
1 2, ,...,RS RS RS RSYR R R R ,0 ,1 ,RRes ,RRes ,...,RResRS
y y y y YR
RS2RS0
RS4
RS8
RS5
RS3
RS1RS6
RS7
1 1,0 1,1 1,8RRes ,RRes ,...,RResRSR
2 2,0 2,1 2,8RRes ,RRes ,...,RResRSR
8 8,0 8,1 8,8RRes ,RRes ,...,RResRSR
...
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Network Model and Assumption Similarly, the matrix portrays the
resource requirement of all MSs, where
records the resource that MSn requires to receive data from all
RSs.
1 2, ,...,MS MS MS MSNR R R R
,0 ,1 ,MRes ,MRes ,...,MResMSn n n n YR
MS1 MS2
1 1,0 1,1 1,8MRes ,MRes ,...,MResMSR
2 2,0 2,1 2,8MRes ,MRes ,...,MResMSR
RS2RS0
RS4
RS8
RS5
RS3
RS1RS6
RS7
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Network Model and Assumption Finally, the resource allocation vector is denoted by RA = [RA0, RA1, RA2, …, RAY ], where RAy represents the amount of the resource allocated to RSy.
MS1 MS2
RS2RS0
RS4
RS8
RS5
RS3
RS1RS6
RS7
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Network Model and Assumption U(): whether the MSn can receive data from RSy successfully.