Scheduling Algorithms for Super 3G Jean-Christophe Laneri Kungliga - - PowerPoint PPT Presentation

Master Thesis Presentation Scheduling Algorithms for Super 3G 2006-03-23 1

Jean-Christophe Laneri Kungliga Tekniska Högskolan Radio Communications Laboratory Master Thesis Project

Advisor: Hannes Ekström (Ericsson Research) Examiner: Slimane Ben Slimane (KTH)

Scheduling Algorithms for Super 3G

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Agenda

Scheduling Algorithms for Super 3G The Big Picture Algorithms Simulation Results Conclusions

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Super 3G

Initial deployment in the 2009-2010 time perspective

• Evolution of the 3GPP Radio Access Network (RAN)
• Traffic carried on to of IP: Enhancements for packet-based services
• Targets related to this work

– High Peak & ’ cell-edge ’ data rates – Spectrum Efficiency improvement & Spectrum Flexibility – Improved Service Provisioning

• Possible ways of enforcing these objectives which concern this project

– Reduced number of Network Nodes – Differentiation of Services over a Shared Infrastructure – Physical Layer

• Downlink: OFDM with frequency adaptation

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Motivations and Problem Definition

Providing Quality of Service over Shared Channels

• Schedulers are used in order to

– Divide the Resources between the users over Shared Channels – Provide Spectrum Efficiency – Fulfill Service Requirements

• We study Downlink Scheduling Algorithms within the following context

– Multi-user OFDMA environment (with frequency adaptation) – Services Differentiation – ‘Realistic’ Traffic Models

• We aim at

– Verifying if the QoS policy profiles can be enforced – Evaluating some scheduling algorithms characterized by different level

• f fairness (in terms of user data rates)

– Investigating the tradeoffs between network capacity and user fairness

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QoS Concept

Realization of DiffServ for 3GPP access networks

• Principle

– Mark each packet at the network edge with a a Flow-Class Identifier (FC-ID) – FC-IDs permit to identify the QoS class of packets at each network node – Associate a Policy Profile to each FC-ID

• FC-IDs are grouped into three categories

– SIGnaling – Guaranteed Bit Rate: Policy Profile = [strict priority] – Best Effort: Policy Profile = [Committed Rate, Priority]

Time Aggregate Cell Throughput

VoIP (Pr=1) Video (Pr=2) Corporate Access Internet Access Allocated to Signaling

CR= 70% CR= 30% CR= 70% CR= 30%

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Scheduling Architecture

Dividing the bandwidth between the FC-IDs

BE Inter-FC-ID Scheduler GBR Inter-FC-ID Scheduler S3G Scheduler

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Scheduling Framework

Radio Resources, Algorithm Inputs and Design Parameters

Perceived User Throughputs Channel Estimate for all OFDM subbands Available at every tti AR-process with 1 s memory

Link Adaptation

Estimate the transferable amount of bits given a scheduling allocation

Scheduling Decision

<user><FC-ID><Number of Bits>

…

20 MHz bandwidth

Scheduler

Allocation Algorithm

1 81

FC-ID Policy Profiles

GBR <FC-ID><Priority><delay cst> BE <FC-ID><CR><Priority>

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Resource Allocation Algorithms (1/2)

Dividing the bandwidth between the users: Intra-FC-ID

• Maximum Signal to Interference Ratio (Max SIR)
• Proportional Fair (PF)
• Exponential Rule (ER)
• Modified Exponential Rule (ER2)
• VoIP Scheduler (VoIP)

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Resource Allocation Algorithms (2/2)

Dividing the bandwidth between the users: Intra-FC-ID

• Fair Throughput
• While users in U1 = {7,5,2} have data to receive

– Iterate over U1, giving the best available chunk

• While users in U2 = {6,9,3} have data to receive

– Iterate over U2, giving the best available chunk

average Smaller throughput Larger throughput

User 7 User 3 User 5 User 2 User 6 User 9

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Scenarios & Performance Measures

Algorithms Validation and Realistic Traffic Evaluation

• Scenarios

– Fully Loaded System

• (Infinite source – only PHY/MAC is simulated)

– File Transfer

• (10 MB fixed file size, PHY/MAC/RLC/IP/TCP simulated)

– Web-Browsing

• (500 kB fixed file size, PHY/MAC/RLC/IP/TCP simulated)

– Voice Over IP

• (32 B frame every 20 ms, PHY/MAC/RLC/IP/UDP/RTP simulated)
• Performance Measures

– Cell Throughput (Information bits) – Link Utilization (Percentage of used chunk) – User Throughput Fairness (Jain fairness index) – Mean User Throughput – VoIP capacity: 90 % of the users with a delay below 50 ms

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Simulation Results

QoS Concept Verification for the Best Effort Policies

• GBR service is emulated

BE traffic gets a varying percentage of the resources.

• Two BE FC-IDs, with

Committed Rates of 70 % and 30 %

• BE Policies are enforced!

48.15 % 36.3 % 15.55 % Time (s)

Percentage of Allocated Resources

CR=30 % CR=70 %

Emulated GBR

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Simulation Results

Full Buffer Scenario (PHY/MAC only-100 users–400 s)

• Traffic belonging to one

BE FC-ID Is simulated.

• Tradeoff between Cell

and User Throughputs

Maximum SIR Fairness = 0.121 ER2 Fairness = 0.245 Proportional Fair Fairness = 0.435 ER Fairness = 0.418 1Mbps 10Mbps Fair Throughput Fairness = 0.899 100Mbps

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Simulation Results

File Transfer (PHY/MAC/RLC/IP/TCP-10 MB files-20 min) Cell Throughput Link Utilization Fairness Mean Throughput

Arrival Rate (users/s) Arrival Rate (users/s)

Fair Throughput Maximum SIR Proportional Fair Modified ER

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Simulation Results

Web Browsing (PHY/MAC/RLC/IP/TCP-500 kB pages-20 min)

• Web-Effect: users with low serving time (high SIR)

monopolize the system

• Traffic with interactive characteristic
• Conclusion:

– A fair scheduler could be profitable

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Simulation Results

VoIP (PHY/MAC/RLC/IP/UDP-32 B frames-20 min)

Delay Constraint: 90% of the received packets with a delay under 50 ms

Number of Users

50 ms delay tolerance Fair Throughput Max SIR VoIP

90th percentile of the packet delays

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Conclusions and Future Works

QoS Concept Validated – Service Specific Scheduler

• Conclusions

– Policy Profiles can be enforced – Proposed schedulers validated with the Full-Buffer Scenario – Impact of realistic traffic: service-dependent scheduling algorithms

• Radio oriented method for background downloads
• Fair approach for interactive scenarios
• Delay aware scheduler for conversational services

– QoS concept well suited for this type of differentiation

• Future Works

– Controlling the scheduling decision as a function of what the users perceive (fairness, mean throughput) and load. – Resources Allocation for more than one tti

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