Self-Organisation in LTE - Results of the FP7 SOCRATES project 34. - - PowerPoint PPT Presentation

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Self-Organisation in LTE - Results of the FP7 SOCRATES project 34. - - PowerPoint PPT Presentation

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FP7 ICT-SOCRATES Self-Organisation in LTE - Results of the FP7 SOCRATES project 34. Treffen der VDE/ITG-Fachgruppe Universitt Stuttgart Thomas Jansen Institut fr Nachrichtentechnik Technische Universitt Braunschweig Outline 1. The

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FP7 ICT-SOCRATES

Self-Organisation in LTE - Results of the FP7 SOCRATES project

  • 34. Treffen der VDE/ITG-Fachgruppe

Universität Stuttgart Thomas Jansen Institut für Nachrichtentechnik Technische Universität Braunschweig

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WWW.FP7-SOCRATES.EU

  • 1. The SOCRATES Project
  • 2. SON use cases
  • 3. Realistic simulation scenario
  • 4. Stand-alone use cases
  • 5. Integration use cases
  • 6. Summary

Outline

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

2/18

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SOCRATES

– Self-Optimisation and self-ConfiguRATion in wirelEss networkS

Project period

– 3-year duration: From 01/01/2008 until 31/12/2010

Effort

– Number of person months: 378 – Total project costs: € 4,980,433

Consortium

Project overview: facts and figures

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

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Self-organisation in wireless networks

– Self-optimisation

– measurements, processing,

parameter adjustment, …

– continuous loop

– Self-healing

– failure detection – automatic minimisation of

coverage/capacity loss – Self-configuration

– e.g. ‘plug-and-play’ of new base

stations

Focus on 3GPP LTE (E-UTRAN)

Project overview: key issues

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

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Radio network optimisation

– Interference coordination – Self-optimisation of physical channels – RACH optimisation – Self-optimisation of home eNodeB

GOS/QoS related parameter optimisation

– Admission control parameter optimisation – Congestion control parameter optimisation – Packet scheduling parameter optimisation – Link level retransmission scheme optimisation – Coverage hole detection

Handover related optimisation

– Handover parameter optimisation – Load balancing – Neighbour cell list

Others

– Reduction of energy consumption, Tracking areas,

TDD UL/DL switching point, Management of relays and repeaters, Spectrum sharing, MIMO

For each use case:

  • Description
  • Objective
  • Parameters
  • Triggers
  • Required measurements
  • Architect. aspects
  • Potential gain
  • Related use cases
  • References (NGMN, …)
  • ….

Use cases: self-optimisation

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

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Self-configuration

– Intell. selecting site locations – Automatic generation of default parameters for NE insertion – Network authentication – Hardware/capacity extension

Self-healing

– Cell outage prediction – Cell outage detection – Cell outage compensation

Supporting Function

– X-Map-Estimation

Use cases: self-configuration and -healing

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

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  • 1. The SOCRATES Project
  • 2. SON use cases
  • 3. Realistic simulation scenario
  • 4. Stand-alone use cases

–

Handover optimisation

–

Load balancing

  • 5. Integration use cases
  • 6. Summary

Outline

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

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City area of 1.5 km x 1.5 km in

Germany

50 mobile users traces derived with the

help of a road traffic simulator (SUMO)

Network information available (site

location, sector orientation, tilt)

Realistic path loss predictions at 2.6

GHz

– used for determining 30 strongest cells

for each user position Land-use classes converted from

Openstreetmap

Realistic SOCRATES Scenario

Source: Google Earth 5.0 Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

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Realistic SOCRATES Scenario

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

Introducing mobility using SUMO (Simulation of Urban MObility) − microscopic road traffic simulator

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Goal:

– Improved handover performance – Reduced number of handover failures – Reduced number of “ping-pong” handovers – Reduced number of radio link failures

Approach:

– Optimisation based on handover performance indicators (HPIs) – Analysis of the current handover performance – Adaptation of handover control parameters

Handover parameter optimisation: Goal and Approach

Network monitoring

Handover statistics: HO failure ratio RL failure ratio Ping‐pong HO ratio

Handover parameter adaptation

HO parameters: Hysteresis Time‐to‐Trigger

Performance Analysis

Optimisation Policy: Weighting of the handover statistics

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

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Handover parameter optimisation: HO Algorithm

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

HP = w1 HPIHOF + w2 HPIHPP + w3 HPIRLF

– wx is the weight of the individual HPI Handover operating points are chosen from a

limited set

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

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WWW.FP7-SOCRATES.EU Dipl.-Ing. Thomas Jansen, TU Braunschweig, Institut für Nachrichtentechnik

Load balancing: Goal and Approach

Problem

– Users concentrate in the area served by one

cell

– Unequal load distribution causes an overload – Users can not be served with required quality

level due to lack of resources Main Idea

– Reallocate some users from the overloaded cell

to less loaded neighbour cell(s)

– Overloaded (SeNB) cell must find neighbouring

cell(s) (TeNB) which may accommodate additional load

– SeNB adjusts the HO offset of the TeNB and

forces users to HO to the TeNB Result

– TeNB increases the overlapping area and takes

  • ver some users previously served by the SeNB

– LB operation sets free resources at SeNB – SeNB is able to serve remaining users with the

required QoS

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  • 1. The SOCRATES Project
  • 2. SON use cases
  • 3. Realistic simulation scenario
  • 4. Stand-alone use cases
  • 5. Integration use cases

–

Overview

–

Load balancing and handover optimisation

  • 6. Summary

Outline

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

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5 different integration use cases have been selected

– Admission control and handover optimisation (AC & HO) – Handover optimisation and load balancing (HO & LB) – Interference coordination and packet scheduling (ICO & PS) – Macro and home eNodeB handover optimisation (Macro HO & HeNB HO) – Automatic generation of default parameters and handover optimisation

(AGP & HO) Analyse the impact on and interaction between multiple use cases Develop concepts for coordination

Integration use cases: Goals

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

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Handover optimisation and load balancing: Interaction analysis

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

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The SeNB is overloaded (1) The load balancing algorithms hands

  • ver users to the TeNB and

increases the hysteresis offset of the TeNB (1->2)

The HPI (radio link failure) of the

TeNB increases

The handover algorithm decreases

the hysteresis of the TeNB (3)

The users hand back to SeNB Overall situation is worse than

before

Handover optimisation and load balancing: Interaction analysis

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

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SON algorithm Unsatisfied users HO pp ratio HO failure ratio Radio Link Failure ratio # % % % Reference 12.76 0.43 1.66 13.62 HO

  • ptimisation

11.24 1.97 0.71 6.67 LB only 3.63 4.91 4.22 26.65 LB + HO opt. 2.84 5.11 1.87 16.62

Handover optimisation and load balancing: Simulation results

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

The handover optimisation and load balancing algorithms interact

with each other

Coordination between the algorithms is needed

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Stand-alone use case algorithms have been developed Significant gain in system performance can be achieved Use case algorithms interact with each other Two types of conflicts have been observed

– Control parameter conflict – Observation parameter conflict

Coordination between these algorithms is needed The results of the integration use cases are currently documented

Summary

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

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Thank you very much for your attention

FP7 ICT-SOCRATES

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Call for Papers: International Workshop on Self-Organizing Networks (IWSON) at

  • http://www.ieeevtc.org/vtc2011spring/workshops.php
  • Scope:

– SON for mobile networks (radio / core / transport) as enabler for efficient network

  • peration

– Focus on 3GPP technologies (LTE) – Results from industry and academia – Keynote, papers, posters & demonstrations

  • Topics: self-configuration, -optimization, -healing, supporting SON functions and

technologies

  • Submission deadline: November 15, 2010
  • Organizers:

May 15, 2011