![System
oCoS=Ptotal for downlink
oCoS=Pu
for uplink
Application
Network
rQoS=[rR,rBER]
oQoS=[oR,oBER,oCoS]
Resource Allocation
[User x Subcarrier]
Physical Layer](https://image.slidesharecdn.com/ofdma-1-140114055650-phpapp02/85/Ofdma-1-8-320.jpg)
![Resource Allocation RATE:
BER:
[12
6
6
8
]
[1e-2 1e-2 1e-4 1e-4]
Resource Allocation
Subcarrier
r es U
Channel
QoS
64-QAM
16-QAM
4-QAM](https://image.slidesharecdn.com/ofdma-1-140114055650-phpapp02/85/Ofdma-1-10-320.jpg)
Ofdma 1
- 1. QoS Aware Adaptive Subcarrier Allocation in OFDMA Systems Mustafa Ergen & Sinem Coleri {ergen,csinem}@eecs.berkeley.edu University of California Berkeley
- 2. Introduction Motivation Orthogonal Frequency Division Multiple Access(OFDMA) OFDMA System Resource Allocation Problem Algorithms Optimal Suboptimal Simulation Conclusion
- 3. Motivation Broadband Wireless Access Ex: IEEE 802.16, Wireless MAN OFDM Eliminates OFDMA InterSymbol Interference
- 4. OFDM Diagram
- 5. OFDM-TDMA Multiuser OFDM Time Subcarrier OFDM-FDMA Time OFDM-TDMA OFDM-FDMA OFDMA Subcarrier OFDMA Time User 1 User 2 User 3 … … Subcarrier
- 6. Resource Allocation Goals: Dynamic subcarrier selection Improve system performance with adaptive modulation More bits transmitted in large channel gain carriers Provide QoS Rate and BER
- 7. Resource Allocation ri ar bc su Assumptions: Base station knows the channel Base station informs the mobiles for allocation er Base Station user
- 8. System oCoS=Ptotal for downlink oCoS=Pu for uplink Application Network rQoS=[rR,rBER] oQoS=[oR,oBER,oCoS] Resource Allocation [User x Subcarrier] Physical Layer
- 9. OFDMA
- 10. Resource Allocation RATE: BER: [12 6 6 8 ] [1e-2 1e-2 1e-4 1e-4] Resource Allocation Subcarrier r es U Channel QoS 64-QAM 16-QAM 4-QAM
- 11. Notation Transmit Power : Pkc,n = f k (ck , n ) α k2,n user : k ∈ {1,..., K } subcarrier : n ∈ {1,..., N } assigned bit : c ∈ {0,1,..., M } k, n channel gain : α 2 k, n No −1 BER M − QAM : f (c) = Q ( 3 4 2 ) (2c − 1)
- 12. K min γ k ,n ,c N M ∑∑∑ f ( ck , n ) k =1 n =1 c =1 subject to Rk = α N 2 k ,n γ k ,n ,c for γ k ,n ,c ∈{0,1} M ∑∑ c k ,n .γ k ,n ,c for all k , n =1 c =1 and 0 ≤ K M ∑∑ γ k , n ,c Pc2 Pc3 r es U Integer Programming ≤ 1, for all n. Subcarrier Subcarrier Subcarrier k =1 c =1 es U Pc1 r es U Optimal r es U Subcarrier
- 13. Motivation for Sub-optimal Algorithms IP is complex Allocation should be done within the coherence time Time increases exponentially with the number of constraints
- 14. Current Suboptimal Algorithms 2-step: Subcarrier Allocation Assume the data rate for all subcarriers Assume modulation rate is fixed Assign the subcarriers Bit Loading Greedy approach to assign the bits of user
- 15. Current Suboptimal Algorithms Subcarrier Hungarian algorithm Optimal, very complex LP approximation to IP problem Bit Loading For each k , repeat the following Rk times : n = arg min ∆Pk ,n (ck ,n ) n∈S k c k ,n =c Subcarrier Close to optimal r es U r es U Subcarrier Allocation k ,n +1 evaluate ∆P (c ). k ,n k ,n r es U Subcarrier
- 16. Problems in Current Suboptimal Algorithms Subcarrier assignment and bit loading are separated Users with bad channels may need higher number of subcarriers Not iterative subcarrier assignment
- 17. Iterative Algorithm Iterative algorithm based on Assignment of bits according to highest modulation Finding the best places Distributing the assigned bits to other subcarriers or to non-assigned subcarriers Exchanging the subcarriers among user pairs for power reduction.
- 18. Iterative Algorithm Fair Selection(FS) Greedy Release(GR) Horizontal Swaping(HS) Vertical Swaping(VS)
- 19. Iterative Algorithm Start ASSIGNMENT Modulation-- ITERATION PA W L A C T REV S I GREEDY RELEASE PA W L AT N OZ R OH S I Ptotal<Pmax FAIR SELECTION
- 20. Simulation Environment Build the OFDMA system Modulations:4-QAM,16-QAM,64-QAM Independent Rayleigh fading channel to each user Number of subcarriers =128 Nodes are perfectly synchronized
- 21. CDF of total transmit power without Pmax constraint
- 22. CDF of total transmit power with Pmax constraint
- 23. Average bit SNR vs. RMS delay spread As RMS delay spread increases, the fading variation increases hence higher gains are obtained by adaptive allocation
- 24. Average bit SNR vs. number of users As the number of users increases, the probability of obtaining good channel at a subcarrier increases
- 25. Instantaneous Average bit SNR vs Time Iterative Algorithm improves its Average Bit SNR by the time.
- 26. Conclusion OFDMA Broadband Wireless Access Resource Allocation Channel Information QoS Requirement Optimal Algorithms complex Iterative Algorithms
Editor's Notes
- #3: The analysis, Research and consultancy (ARC) group forecasts that the fixed wireless deployments in both homes and business will reach 28 million by 2005. 802.16 comiitee broadband wireless access based on OFDMA.
- #4: BWA is alternative to DSL technologies Physical layer should mitigate non LOS environments in indoor. 802.16 10-66GHz 802.16a 2-11GHz
- #7: Instead of assigning a fixed frequency or time slot to each user, the performance will increase. The users will not use the subcarriers that are in deep fade. The performance will increase since it is quite unlikely that this subcarriers will be in deep fade for all the other users.