A Low Complexity Resource Allocation Algorithm with A Low Complexity Resource Allocation Algorithm with Increasing Capacity in Cooperative OFDMA SystemsIncreasing Capacity in Cooperative OFDMA Systems

Choong-Wan Park, Won-Chul Choi, Seokkwon Kim and Dong-Jo Park

School of Electrical Engineering and Computer Science

Korea Advanced Institute of Science and Technology (KAIST)

IWCMC 2008

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OutlineOutline

Introduction System Model and Problem Formulation Proposed Algorithm Simulation Results Conclusion

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IntroductionIntroduction

Dynamic resource allocation Multi-hop orthogonal frequency division multiple access

(OFDMA)

A conventional algorithm not suitable for cooperative OFDMA systems feedback channel gain information (CGI) excessive relay load balancing scheme iterative

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IntroductionIntroduction

The proposed algorithm Low complexity Practical to implement Increases the system capacity

Two types of receiver structures Selection Combining (SC) Maximum Ratio Combining (MRC)

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System Model and Problem FormulationSystem Model and Problem Formulation

In a cooperative OFDMA systems, assume that the BS can know the CGI that reports on the MS the total transmission power of each relay node

Assume The BS allocates the paths, subcarriers and power to the r

elay nodes and an MS A subcarrier is not shared by users

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System Model and Problem FormulationSystem Model and Problem Formulation

No decoding errors

MSMSMSMS

BSBSBSBS

RSRSRSRS

First Half

Second Half

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System Model and Problem FormulationSystem Model and Problem Formulation

Goal Maximizes the system capacity while minimum resources are guaranteed for

each user

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System Model and Problem FormulationSystem Model and Problem Formulation

K: the set of users. N: the set of all subcarriers. L: the set of all OFDM transceivers. ρk,n,l: the nth subcarrier usage index for user k through the lth path. pk,n,l : an allocated power to the lth path of user k in subcarrier n. hk,n,l : the nth subcarrier gain of user k through the lth path. : is the relay peak transmission power of the lrth OFDM transceiver. Rk is the total data rate of the kth user. Sth is the minimum number of subcarriers that should be allocated to each

user.

lrpeakp

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System Model and Problem FormulationSystem Model and Problem Formulation

Conventional Optimization problem

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Proposed AlgorithmProposed Algorithm

A conventional algorithm subcarrier allocation relay load balancing power distribution

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Proposed AlgorithmProposed AlgorithmA. RASC AlgorithmA. RASC Algorithm

1) Subcarrier Allocation with Partial Feedback A conventional algorithm needs

full CGI on all users, all subcarriers, and all paths.

best1 path: the best channel gain path of a user best2 path: efficient relay load balancing

Reduced uplink resources from (K · N · L) CGI to (K · N · 2) CGI

Reduced operation complexity from O(K ·N · Llog(K · N · L)) to O(K · N · 2 log(K · N · 2))

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Proposed AlgorithmProposed AlgorithmA. RASC AlgorithmA. RASC Algorithm

2) Efficient Relay Load Balancing step 1: power constraint

MSMS11

BSBS

RSRS11

RSRS22

RSRS33

MSMS22

MSMS33

power constraint :25

10

30

10

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Proposed AlgorithmProposed AlgorithmA. RASC AlgorithmA. RASC Algorithm

2) Efficient Relay Load Balancing step 2: refer to “best2 path”s for each user step 3: calculate the channel gain gap step 4: sort all the channel gain gaps

MSMS11

RSRS22

RSRS33

MSMS22

MSMS33

BSBS

RSRS11

“best2 path” for MS2

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Proposed AlgorithmProposed AlgorithmA. RASC AlgorithmA. RASC Algorithm

2) Efficient Relay Load Balancing step 5: Set the minimum valued path as the “target path”.

MSMS11

RSRS22

RSRS33

MSMS22

MSMS33

Sort:

MS2 MS1 MS3

2 3 6

BSBS

RSRS11

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Proposed AlgorithmProposed AlgorithmA. RASC AlgorithmA. RASC Algorithm

2) Efficient Relay Load Balancing step 6: exchange a path of subcarriers from “best1 path” to “bes

t2 path” step 7: repeat the step 5 and step 6 about all the relays that sati

sfy the step 1 condition.

MSMS11

BSBS RSRS22

RSRS33

MSMS22

MSMS33

RSRS11

power constraint :25

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20

10

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Proposed AlgorithmProposed AlgorithmB. RAMRC Algorithm

a different criterion RAMRC uses the MRC scheme at MSs

1) Modified Subcarrier Allocation with Partial Feedback direct path (hk,n,ld ),

”best1 path” (hk,n,lrb1 )

“best2 path” (hk,n,lrb2 )relay load balancing

2) Modified Relay Load Balancing “best1 path”: direct path “best2 path”: (target path) relay path

MSMSMSMS

BSBSBSBS

RSRSRSRS

basic subcarrier allocation

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Proposed AlgorithmProposed AlgorithmB. RAMRC Algorithm

If an MS decodes a signal by using SC the MS selects the better signal of y1 and y2.

(If y1 is better than y2)

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Proposed AlgorithmProposed AlgorithmB. RAMRC Algorithm

If an MS decodes a signal by using MRC

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Simulation ResultsSimulation Results

Because it takes too long to find the optimal solution of the problem by computer simulation two simulation scenarios

small-scale simulation proposed algorithm VS. optimal and conventional a

lgorithm large-scale scenario

proposed algorithm VS. conventional algorithm

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Simulation ResultsSimulation Results

Users (K): 5 Subcarriers (N): 32 Paths (L): 7 (RS: 6)

BS transmission power: 30W relay transmission power: 10W minimum subcarrier constraint

per user (Sth) is 4

BSBSBSBS RSRSRSRS2/3

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Simulation ResultsSimulation Results

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Simulation ResultsSimulation Results

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Simulation ResultsSimulation Results

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ConclusionConclusion

An adaptive resource allocation scheme for multihop OFDMA systems CGI on all users, all subcarriers, and all paths

waste of uplink resources a high level of complexity unsuitable for cooperative networks relay load balancing is impractical