1. Opportunistic Scheduling Algorithms for Wireless Networks
Vegard Hassel
CUBAN Seminar 22. April 2004

2. Agenda What is scheduling/opportunistic scheduling? Cross-layer design
Different types of channel models
Fairness
Algorithms that only consider the channel conditions
Algorithms that consider QoS
Algorithms that consider power consumption
Current & future research

3. What Is Scheduling?
Scheduling policy:
-a rule that specifies which user is allowed to transmit and which user is allowed to receive at each timeslot
Uplink (user transmits) and downlink (user receives) at different frequencies.

4. What Is Opportunistic Scheduling?
Opportunistic: Scheduler tries to exploit channel conditions to achieve higher network performance
SCHEDULER
USER 1
USER 2
BUFFERS
USER 3
The base station serves as a scheduling agent

5. Qualcomm Example (1)
The channel conditions for each user is independent
The channel is GOOD 50% of the time and BAD 50% of the time
Two users with bitrates:
User 1: 200Mbit/s or 400Mbit/s
User 2: 400Mbit/s or 800Mbit/s
The users cannot be active at the same time
Round robin algorithm without opportunistic scheduling:
R1=0.5*(0.5*200Mbit/s+0.5*400Mbit/s)=150Mbit/s
R2=0.5*(0.5*400Mbit/s+0.5*800Mbit/s)=300Mbit/s

6. Qualcomm Example (2) But what if both users need 200Mbit/s?
With opportunistic scheduling, the user that has the GOOD channel condition is chosen:
25% of the time both users have BAD channel
50% of the time one user has GOOD channel
25% of the time both users have GOOD channel
The user with the relatively best channel is chosen
Round robin with opportunistic scheduling:
R1=0.5*(0.25*200Mbit/s+0.75*400Mbit/s)=175Mbit/s
R2=0.5*(0.25*400Mbit/s+0.75*800Mbit/s)=350Mbit/s
Opportunistic scheduling gives a 17% capacity gain
But what if both users need 200Mbit/s?

7. Cross-Layer Design TCP/IP-layers: Application Transport (TCP, UDP)
Internet (IP)
Network access (MAC, LLC)
Physical
Today: Some adaptation between neighbouring layers
Tomorrow: Network stack that take advantage of the interdependencies between the layers

8. Cross-Layer Design Variations follow different time scales:
SNR variations ~ microseconds
Congestion of packets ~ seconds?
Cumulative user traffic ~ seconds
Goldsmith: Because of the different timescales, adaptation between layers is reasonable only if problems cannot be fixed locally within a layer.

9. What Influences Scheduling?
QoS requirements
Delay
Throughput
SCHEDULING
Fast fading
Slow fading
Instantaneous channel conditions

10. Restrictions From Other Layers
Physical layer:
Adaptive coding and modulation (MQAM)
TDMA or CDMA
TDMA: The channel should be constant within a time-slot
Higher layers:
Throughput requirements
Delay requirements

11. Channel Models Two-state Markov: GOOD/BAD
Slow fading: log-normal distribution
Fast fading:
Rice (LOS)
Rayleigh (LOS blocked)
Nakagami (general)
The average SNR, , for the fast fading models is influenced by slow fading
Slow scheduling: parameters changes slowly
Fast scheduling: parameters changes fast

12. Fairness
Choosing the best user with regard to the channel can lead to starvation of some users
Fair algorithms assign a guaranteed time or throughput to the users (Robin Hood)
Fairness not so important in a fast fading environment

13. Algorithms That Only Consider The Channel Conditions
Proportional fair algorithm
Max SNR scheduling
Max SNR scheduling with a threshold
Opportunistic beamforming

14. Proportional Fair Algorithm
Proportional fair if:
increasing the current throughput by x% for one user leads to a cumulative throughput decrease for the other users of more than x%
Maximises the product of the throughputs
The user with the relatively best channel is chosen
Starvation is avoided
Used by Qualcomm/HDR (IS-856)

15. Proportional Fair Algorithm
STEP 1:
At time t choose the user with the highest Ri(t)/ Ci(t):
STEP 2:
Update average rate:

16. Max SNR Scheduling Proportional Fair algorithm with:
large values of tc
same for all users: Ri(t) ~ i(t) and Ci(t) ~
The user with the largest SNR is chosen
Also called greedy algorithm
Not fair if is different for different users

17. Max SNR Scheduling With Threshold
The user with the largest SNR above a threshold is chosen:
Reduces the amount of feedback from the users. Channel state information is only fed back if SNR is above the threshold.

18. Opportunistic Beamforming
Induce channel fluctuations in a slow fading environment:
MS’s with multiple antennas
Antennas are fed with random phase and amplitude
The overall induced SNR of a user is fed back to the BS
The BS schedules proportionally fair according to the different SNR values

19. Algorithms That Consider QoS
FUNDAMENT: Revenue-based algorithm
This algorithm maximizes the throughput with regard to QoS requirements:
wi(t): weight assigned to a user to include the QoS requirements

20. Algorithms That Consider QoS
Examples of QoS-requirements:
Minimum delay requirement
Minimum throughput requirement

21. M-LWDF Modified Largest Weighted Delay First
i: constant for controlling delay distributions
Wi(t): head-of-the-line packet delays
This simple algorithm is throughput optimal!

22. M-LWDF: Throughput Guarantees
Guarantees minimum throughput Ri:
Ri: constant token arrival rate in bucket i
Wi(t): delay of the longest delay token in bucket
i: constant for controlling time-scale on which throughput guarantees are provided

23. Lazy Scheduler
A scheduler that trades off delay for energy

24. M-LWDF: Delay vs. Power?
i: constant for controlling trade-off between power and delay
Wi(t): head-of-the-line packet delays
Pi(t): power that has to be provided to user i

33. System Model Buffering on both uplink and downlink SCHEDULER BUFFERS
USER 1
USER 2
BUFFERS
USER 3
BUFFERS

34. Current Research
Have investigated buffering between wired and wireless (Rayleigh) networks using optimal SNR scheduling.
New expression for overflow probability when the rate into the memoryless buffer is constant.
The corresponding expression has been found for a queue with Poisson distributed traffic from the wired network (M/G/1-queue)

35. What Will I Do Next?
Investigate max SNR Scheduling with both power and rate adaptation for M-QAM
Investigate the effects of Dopplerspread, coherence time and avg fade duration
Spectral efficiency and BER for a scheduling algorithm using a -threshold
Max SNR scheduling with delayed CSI
SNR scheduling with different

36. Future Research 1) Physical layer issues:
Optimising adaptive coding/modulation to the scheduling algorithm in use
Scheduling for slow fading channels (fairness!)
Evaluating channel information inaccuracy
Analysing interference/multicell issues
Combining MIMO with scheduling
Combining OFDM with scheduling
Energy efficient scheduling (with Sébastien)

37. Future Research 2) QoS issues: Must look at algorithms that:
Provide QoS differentiation between users
Maximise the number of users that can be supported with the desired QoS
Provide minimum flow guarantees?
Gives minimum buffer overflow

38. Future Research 3) Other issues: Ad Hoc networks Multi-hop networks
MAC and ARQ protocols
CAC: Connection Admission Control