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Dynamic and Persistent Scheduling for Voice over IP Traffic in the Long-Term Evolution Uplink

Dynamic and Persistent Scheduling for Voice over IP Traffic in the Long-Term Evolution Uplink. Master’s Thesis Presentation 10.4.2007 Author: Mira Heiskari Supervisor: Professor Riku Jäntti Instructor: M.Sc. (Tech.) Anna Larmo Oy L M Ericsson Ab, Jorvas, Finland. Agenda.

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Dynamic and Persistent Scheduling for Voice over IP Traffic in the Long-Term Evolution Uplink

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  1. Dynamic and Persistent Scheduling for Voice over IP Traffic in the Long-Term Evolution Uplink Master’s Thesis Presentation 10.4.2007 Author: Mira Heiskari Supervisor: Professor Riku Jäntti Instructor: M.Sc. (Tech.) Anna Larmo Oy L M Ericsson Ab, Jorvas, Finland

  2. Agenda • Long-Term Evolution • Voice over IP • Uplink Scheduling • Background and Goals • Simulation Setup • Simulation Results • Conclusions • Future Work

  3. Long-Term Evolution (LTE) • An evolution of the 3G WCDMA technology, currently under specification process in the 3GPP • The recommendations are estimated to be ready by September 2007 • First live networks are expected to come to markets in 2009-2010 • Target data rates for LTE: around 100 Mbps in the downlink and 50 Mbps in the uplink • Main changes compared to today networks: • Simplified network architecture  less interfaces • Support for packet-switched domain only • Reduced control and user plane latencies • Multi-antenna solutions

  4. Voice over IP (VoIP) • VoIP is a general term for delivering speech traffic using the Internet Protocol (IP) on the network layer • Speech frames are packed to IP packets, and then sent over the packet-switched network to the receiver • LTE has only packet-switched domain  VoIP is a suitable technology for transferring speech in LTE networks • In VoIP traffic, the speech packet that needs to be scheduled and transmitted comes every 20 ms

  5. Uplink (UL) Scheduling • The UL scheduler monitors the users’ requests and distributes the available resources among various users • The scheduler has only limited information about the UE’s demands Example of dynamic scheduling Example of persistent scheduling

  6. Background and Goals • 3GPP standardization organization is planning to make the scheduling in LTE more effective • Based on theoretical calculations done in the thesis, signaling load could be reduced significantly with persistent scheduling • In dynamic scheduling, the resources are distributed in 1 ms intervals • In persistent scheduling, longer transmission period is allocated for user with the one grant • Persistent grant could be valid for a continuous or discontinuous time for a specified frequency domain resource • Also modulation and coding scheme would be persistent throughout the validity time of the grant (i.e., link adaptation disabled) • How the persistent scheduling will effect to the traffic performance of a user? • The practical part of the thesis was done with computer simulations

  7. Simulation Setup • The simulations were done with a detailed LTE network simulation tool developed by Ericsson Research • The author of the thesis implemented the scheduling patterns used in the simulations for the persistently scheduled users • One user moving slowly in a single-cell network  no handovers or interference from others • The simulations investigated the effects of uplink scheduling patterns to the traffic performance in terms of: • Hybrid ARQ (HARQ) retransmissions • Delay • Number of used sub-frequency bands • Used modulations

  8. Simulation Scenarios • There were three simulation cases: 1) Dynamic scheduling 2) Persistent scheduling with fixed Transport Block size (TbSize) 316 bits 3) Persistent scheduling with fixed TbSize 355 bits • All cases were tested with max. 2 and 5 HARQ retransmissions • In dynamic scheduling, the user got a scheduling grant with updated link adaptation (LA) parameters every 20 ms • In persistent scheduling, the LA parameters were saved when sending the first VoIP packet, and the same parameters were used throughout the whole call • The persistent scheduling pattern was granted for the whole duration of a VoIP call during the first VoIP packet  only one signaling message needed

  9. Results The number of used HARQ retransmissions were significantly larger for the persistently scheduled users

  10. Conclusions • The results showed quite clearly that the persistent user experienced worse results in all examined areas, even in a simple simulation scenario • All (persistently scheduled) users had a good link quality in the beginning • The lack of link adaptation for the persistently scheduled users was the main reason for lower traffic performance results • Fixed parameters used in the persistent scheduling should be selected for a poorer link quality, in order to have better traffic performance for the users, when the link quality decreases • Scheduling grant should be given for a shorter period, not for the whole duration of the call  link adaptation would exist with certain frequency

  11. Future Work • Developments for simulations: • number of users • number of cells • varying the mobility of the users • Before planning the simulation parameters more exact, the scheduling patterns should be modified to more flexible direction, in order to get better results • Different resource allocation methods than dynamic scheduling for other traffic types (e.g., Web traffic)

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