Self-Optimising Call Admission Control for LTE Downlink K. Spaey, - PowerPoint PPT Presentation

FP7 ICT-SOCRATES Self-Optimising Call Admission Control for LTE Downlink K. Spaey, B. Sas, C. Blondia IBBT / University of Antwerp Joint COST 2100 / SOCRATES workshop February 5, 2010 Work performed within the context of the SOCRATES project ~ www.fp7-socrates.eu

Outline  (Self-optimising) call admission control  Reference admission control algorithm  Metrics  Self-optimising algorithm for Th HO  Evaluation methodology  Simulation results  Conclusions and future work WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 2

(Self-optimising) call admission control  Call admission control (AC) algorithm – Decides if a call request will be admitted or rejected – Bases its decisions on: • Enough resources available to guarantee QoS new call? • If call is accepted, QoS of already accepted calls will be maintained?  Self-optimising call admission control – Self-optimise / auto-tune parameters of the AC algorithm – In response to changes WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 3

(Self-optimising) call admission control  Development of a simple self-optimising AC algorithm  Evaluation under sudden overload  Reference AC algorithm (static algorithm) needed – AC algorithms are vendor specific – Literature: • Prioritisation of acceptance of handover over fresh calls • Recognise diverse QoS requirements for delay-sensitive (RT) and delay-tolerant (NRT) applications WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 4

Reference admission control algorithm  Typical AC rule: admit call if c *( t ) + c req ≤ margin × C(k) cell capacity required capacity required capacity new call already accepted Cell capacity depends on calls → packet scheduler decisions → channel conditions users → location users → varies over time Distinct margins for → estimate of time-varying cell • fresh / handover calls • RT / NRT calls capacity needed * * Based on “Adaptive connection admission control scheme for high data rate mobile networks”, S.S. Jeong, J.A. Han, W.S. Jeon, VTC Fall 2005 WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 5

Reference admission control algorithm priority is given to HO calls fresh calls are blocked  t: time of call arrival  C(k): most recent estimate of cell capacity  c req : required capacity of arriving call  c * (t): required capacity of already accepted active calls avoid that cell capacity is  c * RT (t): required capacity of already entirely filled with RT calls accepted active RT calls WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 6

Metrics to assess performance  GoS measurements – HO failure ratio = (# HO calls rejected by the AC algorithm) / (# generated HO calls) – Call blocking ratio = (# fresh calls rejected by the AC algorithm) / (# generated fresh calls)  QoS measurements (only for admitted traffic) – Traffic loss ratio = (# lost traffic) / (# generated traffic) • measured for RT traffic (voice / video) – Call throughput = (# bits of call) / (call transfer time) • measured for NRT traffic (web) • we focus on the fraction of web calls with a call throughput smaller than the minimum call throughput requested to the packet scheduler WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 7

Sensitivity analysis on Th HO  Simulations in which the 4 performance metrics are obtained – for various Th HO values – in scenarios with varying call arrival rate or varying %HO calls  Changes in the measured performance might require opposite adaptations of Th HO , depending on which performance measure is considered – QoS degradation of ongoing calls decrease of Th HO – Increasing HO failure ratio – Increasing call blocking ratio → increase of Th HO  Operator policy to decide on this trade-off  SON algorithm which auto-tunes Th HO should take the chosen policy into account WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 8

Self-optimising algorithm for Th HO  Desired properties – Th HO should be adapted based on GoS / QoS measurements, rather than on measurements on the system conditions – Measurements should be smoothed – Follow policy to handle contradictions in required adaptations of Th HO  Policy considered In order of priority: – Aim to guarantee QoS of the accepted calls – Accept HO calls with priority over fresh calls – Aim to reduce call blocking ratio WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 9

Self-optimising algorithm for Th HO  At regular time instants t = k Δ , measurements are collected  Measurements in [ k Δ ; (k+1) Δ [ , smoothed with parameter α SON – QoS_RT(k): trafic loss ratio real-time traffic – QoS_NRT(k): fraction of non-real-time calls with call throughput smaller than amount requested to scheduler – GoS_HO(k): HO failure ratio – GoS_fresh(k): call blocking ratio WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 10

Self-optimising algorithm for Th HO bad QoS or bad HO failure ratio decrease Th HO increase Th HO good QoS and good HO failure ratio and bad call blocking ratio WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 11

Evaluation methodology  Evaluation of SON algorithm under sudden overload (unpredictable event) – Scenarios where there is a sudden increase in call arrival rate or/and %HO calls  Comparison of performance obtained with – Self-optimising AC algorithm (reference algorithm + auto-tuning of Th HO ) – Static AC algorithm (reference algorithm, fixed Th HO ) WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 12

Simulation model  Simulator for downlink direction developed using OPNET Modeler  Call generation: – fresh / HO calls – VoIP (RT) / video streaming (RT) / web browsing (NRT) WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 13

Simulation results  Set-up: 0.6 calls/s, 30% HO calls after 28 minutes (± 1000 calls) 1 call/s, 60% HO calls  Parameters self-optimising algorithm – Δ = 1 minute – τ QoS_RT = 1e-5, τ QoS_NRT = 2%, τ GoS_HO = 1%, τ GoS_fresh = 5% – α SON = 0.75, 0.90  Static AC algorithm (no-SON): Th HO = 0.3, 0.4, …, 0.9, 1  SON AC algorithm (SON): Th HO is auto-tuned WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 14

Simulation results  QoS: fraction of web calls with call throughput ≤ 250 kbit/s SON no SON Before change: SON performs equally well After change: After change: SON performs equally well SON performs better WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 15

Simulation results  QoS: traffic loss ratio SON no SON Before change: SON performs equally well After change: After change: SON performs equally well SON performs better WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 16

Simulation results  GoS: handover failure ratio SON no SON Before change: SON performs equally well After change: After change: SON performs equally well SON performs better WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 17

Simulation results  GoS: call blocking ratio defined policy defined policy achieved not achieved SON no SON Before change: SON Before change: SON performs better performs equally well defined policy After change: After change: SON performs achieved SON performs better considerably worse WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 18

Conclusions and future work  SON algorithm complies better to the defined policy, both before and after the change, than the static algorithm with fixed Th HO – In general: • “high” Th HO before change • “low” Th HO after change → SON can adapt Th HO according to the state the system is in  Future work: integration of multiple SON algorithms - Admission control SON combined with handover SON • both algorithms are triggered if handover failure ratio is too high • both algorithms aim to reduce the handover failure ratio in their own way → they influence each others input measurements WWW.FP7-SOCRATES.EU Kathleen Spaey, IBBT / University of Antwerp 19