Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells

1. QoS and QoE in Wireless Communications/Networks Workshop (QoS-QoE 2013), 9th IWCMC’13, Cagliari, Italy. Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Hatem Abou-zeid*, Stefan Valentin†, Hossam S. Hassanein*, and Mohamed F. Feteiha* * Queen’s University, Canada †Bell Labs, Alcatel-Lucent, Germany

2. Introduction: Downlink Scheduling Basics Proportional-Fair Scheduler (PF): • Schedule user with highest • Throughput-fairness balance • Ri(t)computed over a window Tw

3. Introduction: Downlink Scheduling Exponential Scheduler (EXP): • Schedule user with highest • Idea: when a user queue increases relative to average queues, the user is prioritized exponentially

4. Traditional Scheduling: Short-term QoS Indicators • Traditionally, schedulers employ QoS indicators such as average rates Ri(t) to provide service guarantees and fairness. • These indicators are usually computed over a short duration, typically a few seconds. • Further, QoS indictor information from prior cells is not transferred to the user’s current cell The QoS a user receives in one cell will not impact the future QoS in upcoming cells as BSs only know the user QoS in their cell

5. Motivation for Proposing Long-term QoS • Today’s networks have fluctuating demand: • in different cells • at different times of the day • network traffic is uneven in space and time • Today’s mobile usage involves: • Longer user sessions and more video content • Highly mobile users • users traverse multiple cells during a single session Users receive variable QoS as they move throughout the network

6. Long-Term Multi-cell QoS • Long-term notion of scheduling enables cell cooperation over time by looking back • Users served poorly in congested cells can be compensated in future cells • Proposal: BSs monitor and exchange long-term user QoS Result: improve long-term user satisfaction and reduce subscriber churn

7. 1 0.9 0.8 0.7 0.6 Distance [km] 0.5 0.4 0.3 Base Stations 0.2 Mobile User 1 Mobile User 2 0.1 Static Users 0 0 0.2 0.4 0.6 0.8 1 Distance [km] Simple Scenario: Achieving Long-term QoS Congested cell User 1 User 2 40 30 Fairness in Video Quality (Freezing) Percentage of Frozen Video Vacant cell 20 10 0 Without LLS With LLS

8. Look-back Scheduling (LLS) • Look-back Scheduling adds long-term QoS indictors into the scheduling decision. • This means that user QoS is monitored either by the user, or the network, and reported during handover. • LLS scheduler should also be aware of users immediate resource needs. • LLS design factors: • Which utility functions to use for short and long-term QoS indicators? • How do you combine then for an overall user utility?

9. Look-back Scheduling: Proportional Fairness (LL-PF) Long-term user throughput over multiple BS Final User Scheduling Priority Compute Long-term User Satisfaction Combine Long and Short-term Indicators Long-term indicators QoS metrics from users on perceived quality Channel Quality User Rate Short-term indicators Long-term Look-back PF Scheduler

10. LL-PF: Effect of a Slot Rate Metric: 10th percentile throughput • Computed over T slots • Indicates slot starvation level • Will be zero if user is starved for more than 10% of the time slots • A high value indicates that user is served well in the worst 10% of the time slots

11. Look-back Scheduling: Exponential (LL-EXP) Long-term user throughput over multiple BS Final User Scheduling Priority Compute Long-term User Satisfaction Combine Long and Short-term Indicators Long-term indicators QoS metrics from users on perceived quality Channel Quality Queue Lengths Short-term indicators Long-term Look-back EXP Scheduler

12. Performance Evaluation

13. System Model • 19 Cell Network, 1km inter-BS distance • Mobility: Random Waypoint • Channel: • Path-loss: 128.1 + 37.6 log(d) • Slow fading: 8 dB log-normal • Fast fading: i.i.d. Rayleigh • Traffic: • Full buffer, • Constant bit-rate for video traffic • Metrics: • Network throughput • Jain’s Fairness Index • 10thpercentile slot throughput: • Average freezing • Average ratio of playback time that is frozen for all users in the network

14. Fairness Results: LL-PF Scheduling • LL-PF provides long-term fairness over multiple cells, while simultaneously providing short-term rates depending on the tuning factor a

15. Throughput Results: LL-PF Scheduling • LL-PF network throughput is also higher than PF for values of a that provide a similar short-term slot rate • Therefore there are gains in both throughput and fairness

16. Results: LL-EXP Scheduling • LL-EXP achieves throughput and video freezing gains • The long-term average rate computation allows the scheduler to exploit user channel opportunistically • Gains increase with load

17. Summary • In this paper we introduce the notion of Long-term Look-back Scheduling (LLS) over multiple cells. • To achieve this we propose that QoS indicators are monitored during a user session, and incorporated along with traditional short-term indicators to make the overall scheduling decision • This introduces some signalling during hand-over, where the BS or the user, should transmit the QoS indictors to the target BS. • We developed two LLS and assessed their performance: • Proportional fair scheduling with long and short-term user rates • Exponential scheduling with long and short term QoS indicators • Long-term user QoS gains were observed in both cases.

18. Thank You • Questions? • Please feel free to contact us at h.abouzeid@queensu.ca