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organizing networks TD (10)10068 COST 2100, 10 th MCM Athens, - - PowerPoint PPT Presentation

Sep 28, 2023 125 likes •393 views

FP7 ICT-SOCRATES Handover parameter optimization in LTE self- organizing networks TD (10)10068 COST 2100, 10 th MCM Athens, Greece February 3 rd 5 th TUBS, Braunschweig, Germany IBBT, Ghent, Belgium VOD, Newbury, England Outline 1.

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FP7 ICT-SOCRATES

Handover parameter

  • ptimization in LTE self-
  • rganizing networks

TD (10)10068 COST 2100, 10th MCM Athens, Greece February 3rd – 5th TUBS, Braunschweig, Germany IBBT, Ghent, Belgium VOD, Newbury, England

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  • 1. Introduction
  • 2. Simulation scenario and LTE system-level simulator
  • 3. Simulation metrics
  • 4. Controllability and Observability studies
  • 5. Performance of the non-optimised network
  • 6. Handover optimisation SON algorithm
  • 7. Simulation results
  • 8. Conclusion

Outline

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

2/22

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  • Problem

– Handover parameter optimisation is done manually – high OPEX – long optimisation intervals based on error reports – Non-optimal handover performance – handover failures – ping-pong handovers – call dropping

  • Handover parameter optimisation objective

– automate the optimisation – adapt the handover parameters on a short-term scale – optimise the handover performance

  • Approach

– analyse the system behaviour – develop handover optimisation algorithm

Introduction

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

3/22

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Assembling Scenario Data Processing Data

User locations Environment Network Braunschweig Scenario Traffic Distri- bution Network data OpenSteetMap

Generating Source Data

Correlated User Snapshots Decorated User Snapshots Network Information LTE Simulator

Simulations

Realistic SOCRATES Scenario

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

4/22

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Realistic SOCRATES Scenario

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

  • Computing the landuse information from openstreetmap.org

Landuse classes: Road, Building, Water, Street and Railway

5/22

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  • Input data

– Realistic SOCRATES scenario

  • Power mask

– Soft frequency reuse

  • Call generation

– All users connected

  • Update RSRP/SINR

– Shadow fading maps

  • Handover procedure/algorithm

MATLAB LTE system-level simulator

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

Start Read input data Build Network Build Users

Yes No

End of Simulation? Set Power Mask Call Generation End Update RSRP/SINR HO procedure HO algorithm Next step 6/22

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  • Control parameters

– Hysteresis – Time-to-Trigger

  • Assessment metrics

– Handover failure ratio – Ping-Pong handover ratio

Simulation metrics

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

Control parameter Values Hysteresis (0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10 ) in [dB] Time-to-Trigger (0 0.04 0.064 0.08 0.1 0.128 0.16 0.256 0.32 0.48 0.512 0.64 1.024 1.280 2.56 5.12) in [s] succ HO fail HO fail HO HOF

N N N HPI

_ _ _ – Call dropping ratio fail HO npp HO pp HO pp HO HPP

N N N N HPI

_ _ _ _ accepted HO dropped HO DC

N N HPI

_ _

7/22

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  • System metrics

– RSRP (Reference Signal Received Power) – cell transmit power – pathloss

to the UE

– shadow fading with a standard deviation of 3dB – SINR (Signal to Interference Noise Ratio) – interfering cells

Simulation metrics

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

fad ue c ue c

L L P RSRP ,

N n ue RSRP ue c ue c

n

RSRP SINR

1 10 , 10 , ,

10 log 10

fad

L

ue

L

c

P N

8/22

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Simulation parameter Value Simulation time 200 [s] Simulation step time 0.01 [s] Simulation area (mobile users) 1.5 km * 1.5 km Number of users 30 eNodeB transmit power 46 [dBm] Number of considered cells in the scenario 76 Measured cells (N) 21 Considered interfering cells for SINR calculations 20 Critical ping-pong handover time (T_crit) 5 [s] Handover execution time 0.25 [s] SINR averaging window 0.1 [s]

  • Min. SINR threshold
  • 6.5 [dB]

Controllability and Observability studies

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

  • Objective

Analyse the system behaviour and sensitivity Find handover algorithm approach

  • Simulation assumptions

All resources are used in all cells (maximum interference)

  • Simulation approach

Perform system simulations for all hysteresis and time-to- trigger value combination (handover operating point)

9/22

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C & O: Handover failures

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

2 4 6 8 10 0.1 0.25 0.5 2 1 5 0.02 0.04

Hysteresis [dB] Handover Failures Time-to-Trigger [s] Handover failure ratio

10/22

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C & O: Ping-Pong handovers

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

2 4 6 8 10 0.1 0.25 0.5 1 2 5 0.2 0.4 0.6 0.8

Hysteresis [dB] Ping-Pong Handovers Time-to-Trigger [s] Ping-Pong handover ratio

11/22

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C & O: Call dropping

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

2 4 6 8 10 0.1 0.25 0.5 1 2 5 0.2 0.4 0.6 0.8

Hysteresis [dB] Call drops Time-to-Trigger [s] Call dropping ratio

12/22

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Handover performance weighting function

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

  • HP = w1 HPIHOF + w2 HPIHPP + w3 HPIDC

– wx is the weight of the individual HPI – HPIHOF is the handover failure performance indicator – HPIHPP is the ping-pong handover performance indicator – HPIDC is the dropped calls performance indicator

Weighting parameter Value w1 0.5, 0.6, …, 2.0 w2 0.5, 0.6, …, 2.0 w3 0.5, 0.6, …, 2.0

  • 4096 valid weighting parameter combinations have been considered
  • If (HP<0.05) => “meaningful” handover parameter operating point

13/22

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Handover performance

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

2 4 6 8 10 0.1 0.25 0.5 1 2 5 0.5 1

Hysteresis [dB] Handover Performance (weights = [1 0.5 2]) Time-to-Trigger [s] Normalised sum of weighted HO failure rate, ping-pong HO rate and call dropping rate

14/22

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1 2 3 4 5 6 7 8 9 10 0.1 0.25 0.5 1 2 5

Operating Points (Threshold: 5%) Hysteresis [dB] Time-to-Trigger [s]

“meaningful” handover operating points

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

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Simulation parameter Value Simulation time 1000 [s] Simulation step time 0.01 [s] Simulation area (mobile users) 1.5 km * 1.5 km Number of users 50 eNodeB transmit power 46 [dBm] Operating points (Hysteresis, Time-to-Trigger) (4, 0.48), (6, 0.32), (8, 0.1), (9, 0.08) in [dB, s] Number of considered cells in the scenario 78 Measured cells (N) 21 Considered interfering cells for SINR calculations 20 Handover performance averaging window 60 [s] Critical ping-pong handover time (T_crit) 5 [s] Handover execution time 0.25 [s] SINR averaging window 0.1 [s]

  • Min. SINR threshold
  • 6.5 [dB]

Simulation parameters for the performance analysis

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

16/22

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Performance of the non-optimised network

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

100 200 300 400 500 600 700 800 900 1000 5 10 15 20 25

Time [s] Ratio [%] Handover Performance for the operating point (4, 0.48)

Handover failure Ping-Pong handover Call dropping

17/22

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Performance of the non-optimised network

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik 100 200 300 400 500 600 700 800 900 1000 0.5 1 1.5 2 2.5 3 3.5 4

Time [s] Handover failure ratio [%] Handover failure performance Operating point (4, 0.48) Operating point (6, 0.32) Operating point (8, 0.1) Operating point (9, 0.08) 100 200 300 400 500 600 700 800 900 1000 5 10 15 20 25 Time [s] Ping-Pong handover ratio [%] Ping-Pong handover performance Operating point (4, 0.48) Operating point (6, 0.32) Operating point (8, 0.1) Operating point (9, 0.08) 100 200 300 400 500 600 700 800 900 1000 1 2 3 4 5 6

Time [s] Call dropping ratio [%] Call dropping performance Operating point (4, 0.48) Operating point (6, 0.32) Operating point (8, 0.1) Operating point (9, 0.08)

  • Comparison of the network

performance for four different

  • perating points

(4 dB Hys, 0.48 s TTT) (6 dB Hys, 0.32 s TTT) (8 dB Hys, 0.1 s TTT) (9 dB Hys, 0.08 s TTT)

18/22

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Handover optimisation SON algorithm

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

HO SON algortihm Next cell 1) Update HPIs HPIs < threshold? Yes No Increase bad performance time Increase good performance time 2) 4) Reset good performance time Reset bad performance time Good perform- ance? Yes No Decrease HPI thresholds Bad perform- ance? No Reset good performance time Change handover

  • perating point

Yes Reset bad performance time 11) 8) 3) 5) 6) 7) 9) 10) 12) 13)

Optimisation criteria for HPIs

Handover Performance Indicator Hysteresis Time- to- Trigger Optimisation Handover failure ratio

< 5 dB ↑ TTT

5 dB – 7 dB ↑ TTT & ↑ HYS > 7 dB ↑ HYS Ping-Pong handover ratio < 2.5 dB ↑ TTT 2.5 dB – 5.5 dB ↑ TTT & ↑ HYS > 5.5 dB ↑ HYS Call dropping ratio > 6 dB > 0.6 s ↓ TTT & ↓ HYS <= 6 dB > 0.6 s ↓ TTT > 7.5 dB <= 0.6 s ↓ TTT & ↓ HYS 3.5 dB – 6.5 dB <= 0.6 s ↑ HYS < 3.5 dB <= 0.6 s ↑ TTT & ↑ HYS

  • Optimisation actions are added up
  • Hys and TTT are only changed by one

step at a time

  • The new operating point has to belong to

the set of “meaningful operating points”

19/22

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Handover optimisation simulation results

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

100 200 300 400 500 600 700 800 900 1000 1 2 3 4 5 6 7 8 9 10

Time [s] Ratio [%] Handover performance for the operating point (6, 0.32)

Handover failure Ping-Pong handover Call dropping

20/22

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Handover optimisation simulation results

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

100 200 300 400 500 600 700 800 900 1000 1 2 3 4 5 6 7 8

Time [s] Ratio [%] Handover performance (Optimisation)

Handover failure Ping-Pong handover Call dropping

21/22

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  • The system behaviour to different handover operating points has been

analysed

  • Handover performance can be optimised using the proposed algorithm
  • Handover operating points are chosen for every cell individually
  • The overall network performance is increased and the handover failure ratio

and ping-pong ratio drop to zero in the shown case

  • Next steps

– Run the algorithm in a larger scenario – Improve the SINR calculation (scheduling) – Introduce background traffic (implication on system throughput) – User specific handover parameters

Conclusion

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

22/22

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Thank you very much for your attention

FP7 ICT-SOCRATES

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Handover procedure I

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

HO procedure Next active user HO command send? Yes No Find the best server Yes Connected to the best server? 1) 2) 3) 4) No Save best server as HO candidate 5) 8) If new cell is best server set back HO

  • crit. time

6) Increase handover criteria time 7) Yes HO criteria time > TTT? No Send Handover command

24/22

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Handover procedure II

Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik Yes No 13) Increase HO duration time 10) HO duration > HO execution? 11) Handover complete 12) Save successful Handover Update UE History 14) Next active user 1) HO failure

  • ccured?

17) Save Handover failure 18) Hand back successful? 19) Yes No Yes No Reconnect to Source eNode B 21) Save call drop during Handover 20) Ping-Pong HO detected? 15) No Yes Save Ping-Pong Handover 16)

  • The handover procedure is executed in every simulation time step
  • Handover procedure is independent of the handover algorithm

25/22