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

1. A Low Complexity Resource Allocation Algorithm with Increasing Capacity in Cooperative OFDMA Systems Choong-Wan Park, Won-Chul Choi, Seokkwon Kimand Dong-Jo Park School of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology (KAIST) IWCMC 2008

2. Outline • Introduction • System Model and Problem Formulation • Proposed Algorithm • Simulation Results • Conclusion

3. Introduction • 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

4. Introduction • The proposed algorithm • Low complexity • Practical to implement • Increases the system capacity • Two types of receiver structures • Selection Combining (SC) • Maximum Ratio Combining (MRC)

5. System 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 relay nodes and an MS • A subcarrier is not shared by users

6. System Model and Problem Formulation • No decoding errors BS First Half Second Half RS MS

7. System Model and Problem Formulation • Goal • Maximizes the system capacity • while minimum resources are guaranteed for each user

8. System 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 nthsubcarrier gain of user k through the lthpath. • : is the relay peak transmission power of the lrth OFDM transceiver. • Rkis the total data rate of the kth user. • Sthis the minimum number of subcarriers that should be allocated to each user.

9. System Model and Problem Formulation • Conventional Optimization problem

10. Proposed Algorithm • A conventional algorithm • subcarrier allocation • relay load balancing • power distribution

11. Proposed 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))

12. Proposed AlgorithmA. RASC Algorithm • 2) Efficient Relay Load Balancing • step 1: power constraint power constraint :25 10 RS1 MS1 30 BS RS2 MS2 RS3 MS3 10

13. Proposed 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 RS1 MS1 BS RS2 MS2 RS3 MS3 “best2 path” for MS2

14. MS2 MS1 MS3 Sort: 2 3 6 Proposed AlgorithmA. RASC Algorithm • 2) Efficient Relay Load Balancing • step 5: Set the minimum valued path as the “target path”. RS1 MS1 BS RS2 MS2 RS3 MS3

15. Proposed AlgorithmA. RASC Algorithm • 2) Efficient Relay Load Balancing • step 6: exchange a path of subcarriers from “best1 path” to “best2 path” • step 7: repeat the step 5 and step 6 about all the relays that satisfy the step 1 condition. RS1 MS1 20 BS RS2 20 MS2 RS3 10 MS3 power constraint :25

16. Proposed 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 basic subcarrier allocation BS RS MS

17. Proposed 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)

18. Proposed AlgorithmB. RAMRC Algorithm • If an MS decodes a signal by using MRC

19. Simulation 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 algorithm • large-scale scenario • proposed algorithm VS. conventional algorithm

20. 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 Simulation Results 2/3 BS RS

21. Simulation Results

22. Simulation Results

23. Simulation Results

24. Conclusion • 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