Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Hatem Abou-zeid*, Stefan Valentin, Hossam S. Hassanein*, and Mohamed F. Feteiha * * Queens University, Canada Bell Labs, Alcatel-Lucent, Germany QoS and QoE in Wireless Communications/Networks Workshop (QoS-QoE 2013), 9 th IWCMC13, Cagliari, Italy.

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Introduction: Downlink Scheduling Basics Proportional-Fair Scheduler (PF): Schedule user with highest Throughput-fairness balance R i (t) computed over a window T w

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

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Traditional Scheduling: Short-term QoS Indicators Traditionally, schedulers employ QoS indicators such as average rates R i (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 users 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 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

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Todays networks have fluctuating demand: in different cells at different times of the day network traffic is uneven in space and time Todays mobile usage involves: Longer user sessions and more video content Highly mobile users users traverse multiple cells during a single session Motivation for Proposing Long-term QoS 5 Users receive variable QoS as they move throughout the network Users receive variable QoS as they move throughout the network

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells 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 Long-Term Multi-cell QoS 6 Result: improve long-term user satisfaction and reduce subscriber churn

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Simple Scenario: Achieving Long-term QoS 7 Vacant cell Congested cell Without LLSWith LLS Percentage of Frozen Video User 1 User 2 Fairness in Video Quality (Freezing)

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells 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? Look-back Scheduling (LLS) 8

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

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells LL-PF: Effect of Slot Rate Metric: 10 th 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

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

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

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells System Model 19 Cell Network, 1km inter-BS distance Mobility: Random Waypoint Channel: Path-loss: 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 Jains Fairness Index 10 th percentile slot throughput: Average freezing Average ratio of playback time that is frozen for all users in the network

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

Lookback Scheduling for Long-Term Quality-of-Service Over Multiple Cells Throughput Results: LL-PF Scheduling LL-PF network throughput is also higher than PF for values of that provide a similar short-term slot rate Therefore there are gains in both throughput and fairness

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

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

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