Self-optimisa Self-optimisation in tion in futur future mobile - - PowerPoint PPT Presentation

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Self-optimisa Self-optimisation in tion in futur future mobile access netw e mobile access networ orks ks Remco Litjens Senior scientist Mobile Network Optimisation 2008 November 4, 2008 TNO Information and Communication Technology

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Self-optimisa Self-optimisation in tion in futur future mobile access netw e mobile access networ

  • rks

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Remco Litjens Senior scientist TNO Information and Communication Technology Delft, The Netherlands Mobile Network Optimisation 2008 November 4, 2008 Hôtel Palais Stéphanie, Cannes, France

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Current networks are largely manually operated
  • Separation of network planning and optimisation
  • (Non-)automated planning tools applied
  • Site selection, optimisation of radio parameters
  • ‘Over-abstraction’ of applied technology models
  • Manual configuration of sites
  • Radio (resource management) parameters updated weekly/monthly
  • Performance indicators with limited relevance
  • Time-intensive experiments with limited operational scope
  • Delayed, manual and poor handling of cell/site failures
  • Future wireless access networks will exhibit

a significant degree of self-organisation

  • Self-configuration, self-optimisation, self-healing
  • Broad attention  3GPP, NGMN, FP7, …

INTRODUCTION

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Technogical perspective
  • Complexity of future/contemporary wireless access networks
  • Multitude of tuneable parameters with intricate dependencies
  • Multitude of RRM mechanisms on different time scales
  • Complexity is needed to maximise potential of wireless access networks
  • Higher operational frequencies
  • Multitude of cells to be managed
  • Growing suite of services with distinct char’tics, QoS req’ments
  • Heterogeneous access networks to be cooperatively managed
  • Common practice in network planning and optimisation

→ labour-intensive operations delivering suboptimal solutions!

  • Enabler
  • The multitude and technical capabilities of base stations and

terminals to perform, store, process and act upon measurements increases sharply

DRIVERS

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  • Market perspective
  • Increasing demand for services
  • Increasing diversity of services
  • Traffic characteristics
  • QoS requirements
  • Need to reduce time-to-market of innovative services
  • Reduce operational hurdles of service introduction
  • Pressure to remain competitive
  • Reduce costs (OPEX/CAPEX)
  • Enhance resource efficiency
  • Keep prices low

DRIVERS

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Minimise human involvement

in planning/optimisation

  • Significant automation
  • f network operations
  • Key components
  • Self-configuration
  • Self-healing
  • Self-optimisation

VISION

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  • Self-configuration
  • Incidental, intentional events
  • ‘Plug and play’ installation of

new base stations or features

  • E.g. download of initial radio

network parameters, neigh- bour list generation, trans- port network discovery and configuration, …

  • Self-healing
  • Incidental, non-intentional events
  • Automatic fault detection
  • Automatic minimisation of

coverage/capacity loss in case of cell/site failures

  • Enhanced robustness/resilience
  • Alarm bells

VISION

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  • Self-optimisation
  • Measurements
  • Gathering via terminals, eNBs, probes
  • Propagation, traffic, mobility aspects
  • Performance indicators
  • Continuous self-optimisation
  • f radio parameters
  • In response to observed changes

in conditions and/or performance

  • In order to provide service availability

and quality targets most efficiently

  • Smart on-line algorithms
  • E.g. tilt, azimuth, power,

RRM thresholds, scheduling weights, neighbour cell lists

  • Triggers/suggestions in case

capacity expansion is unavoidable

VISION

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • OPEX reductions …
  • Primary objective!
  • Less human involvement in
  • Network planning/optimisation
  • Performance monitoring, drive testing
  • Troubleshooting
  • About 25% of OPEX is related to network operations
  • x00 million € savings potential per network

EXPECTED GAINS

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  • … and/or CAPEX reductions …
  • Via delayed capacity expansions
  • Smart eNodeBs may however be more expensive
  • … and/or performance enhancements
  • Enhanced service availability, service quality

EXPECTED GAINS

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  • … and/or CAPEX reductions …
  • Via delayed capacity expansions
  • Smart eNodeBs may however be more expensive
  • … and/or performance enhancements
  • Enhanced service availability, service quality

EXPECTED GAINS

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Definition of use cases
  • To guide development of solutions
  • Algorithms
  • Performance aspects
  • Impact on standards and operations
  • To help determine requirements
  • Technical requirements
  • Performance
  • Complexity
  • Stability/robustness
  • Timing
  • Interaction
  • Architecture/scalability
  • Required measurements

USE CASES

  • Business requirements
  • Faster roll-out of LTE networks
  • Simplified operational processes
  • Easy deployment of new services
  • End user quality/cost benefits
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  • Non-exhaustive use case list
  • Self-optimisation
  • Radio network optimisation
  • Interference coordination
  • Self-optimisation of physical channels
  • RACH optimisation
  • Self-optimisation of Home eNodeB
  • GOS/QoS-related optimisations
  • AC/CC/PS optimisation
  • Link level retx scheme optimisation
  • Coverage hole detection/compensation
  • Handover related optimisation
  • Handover parameter optimisation
  • Load balancing
  • Neighbour cell list
  • Others
  • Reduction of energy consumption
  • TDD UL/DL switching point
  • Management of relays and repeaters
  • Spectrum sharing
  • MIMO

USE CASES

  • Self-configuration
  • Automatic NCL generation
  • 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
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  • Self-configuration/-optimisation use case
  • NCL indicates potential handover target cells
  • Typically limited to 32 cells
  • Missing neighbours induces call

dropping or excessive interference

  • Undesired neighbours cause

unnecessary measurements

  • Self-optimisation based on e.g.
  • UE’s signal strength reports
  • eNB scans of neighbours
  • Call drops, handover failures
  • Handover stats: used neighbours
  • Triggers
  • Site/cell addition
  • Poor performance
  • Periodic optimisation

USE CASES

AUTOMATIC NEIGHBOUR CELL LIST GENERATION

EXAMPLE EXAMPLE

A: {B,C,D} C: {A,D} D: {A,B,C,E} E: {B,D} B: {A,D,E}

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  • Self-optimisation use case
  • Key radio resource management mechanism in LTE
  • All traffic all multiplexed over shared channels
  • Distinct QoS requirements
  • Rate requirements, latency tolerance, elasticity
  • A typical scheduler integrates proportional

fairness and deadline-based principles

  • With various tunable parameters, e.g.
  • Capacity sharing between services
  • Degree of proportional fairness
  • Subscription-based priorities
  • Self-optimisation based on
  • Observed performance or efficiency issues
  • Observed ‘environmental’ changes
  • Traffic characteristics, traffic mix, spatial distribution
  • User mobility
  • Propagation effects

USE CASES

PACKET SCHEDULING OPTIMISATION

EXAMPLE EXAMPLE

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  • Self-healing use case
  • Cell outage detection
  • Automatic detection of failures
  • eNodeB failure, cell failure, physical signal/channel failure
  • Generate alarms for automated compensation and manual repair
  • Indicate location, type and urgency of outage
  • Minimise detection time, probability of missed detection and false alarm
  • Measurements
  • UE measurement

reports: pilots, interference levels

  • eNB hard/software

reports, carried load, call drops, … USE CASES

CELL OUTAGE MANAGEMENT

EXAMPLE EXAMPLE

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  • Self-healing use case
  • Cell outage compensation
  • Automatic compensation of failures
  • Optimise ‘regional’ coverage, capacity and/or quality
  • Control parameters
  • Power settings
  • Downtilt, azimuth(?)
  • Intra/inter-RAT handover parameters, load balancing
  • Neighbour cell lists

USE CASES

CELL OUTAGE MANAGEMENT

EXAMPLE EXAMPLE

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  • Self-healing use case
  • Gains

USE CASES

CELL OUTAGE MANAGEMENT

EXAMPLE EXAMPLE

local revenue time manual detection time eNodeB dies eNodeB revived repair time

CASE WITHOUT SELF-HEALING

local revenue time repair time

CASE WITH SELF-HEALING

regained revenue due to cell outage compensation regained revenue due to cell outage detection

  • therwise

missed revenue

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Development of effective self-organisation

methods imposes quite a few challenges

  • Measurements
  • What data? What frequency?
  • Trade-off: signalling cost

vs achieved performance

  • Appropriate processing to

determine ‘network state’

  • Detection/handling of erroneous/

malicious reports

  • Effectiveness of self-organisation
  • Multi-objective optimisation
  • Intricate parameter dependencies
  • Frequency of adjustments
  • Mutual timing → prevent oscillations
  • Centralised vs distributed control
  • Timely detection, swift response

CHALLENGES

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  • Development of effective self-organisation

methods imposes quite a few challenges

  • Dealing with delayed feedback
  • Feedback upon control actions

is not immediate

  • Effects of control decisions
  • r due to natural variations
  • Reliability
  • Actions must be reliable
  • No human sanity checks or

revision of actions

  • Operator must trust the system

when giving up direct control

  • Gradual introduction
  • Shape the network architecture
  • Incorporation in actual systems
  • Protocols, interfaces, architecture

CHALLENGES

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Cooperation among world-leading mobile network operators
  • General objective
  • To collect and promote operator requirements

and recommendations for future mobile networks

  • Establish clear performance targets, fundamental

recommendations and deployment scenarios

  • Project 12
  • Develop operator vision on self-organisation
  • Ensure that self-organisation capabilities become

an inherent part of the initial design of future systems

  • Push vendors to fulfil operator requirements regarding

the implementation of particular solutions

  • Concrete activities include
  • Industry conferences, vendor workshops
  • White papers, 3GPP contributions

WNO IS WHO?

NGMN

now finished  follow-up project

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  • Standardisation of E-UTRAN (LTE)
  • Self-Optimising Networks
  • Introduced in Q2 ‘07
  • Primary objective is to reduce OPEX
  • Self-configuration, self-optimisation, cell outage compensation
  • Considered in SA2/5, RAN1/2/3
  • Releases
  • R8 (finalised Q1/2009)
  • Some auto-configuration concepts included, incl. ‘automatic

neighbour relation’, automatic physical cell ID discovery

  • No new use case, just closing holes …
  • R9/10 (R9 tentatively finalised 12/2009)
  • No concrete plans yet, but expected to consider load balancing,

handover optimisation coverage hole/cell outage management, interference reduction, capacity/coverage optimisation

WHO IS WHO?

3GPP

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  • Overview
  • Self-Optimisation and self-ConfiguRATion in wirelEss networkS
  • Self-configuration, self-optimisation, self-healing
  • 3-year duration: from 01/01/2008 until 31/12/2010
  • Effort: 378 person months, € 4.980.433
  • EU IST FP7-ICT-2007-1

WHO IS WHO?

SOCRATES

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  • Scope
  • Technological focus: 3GPP E-UTRAN (LTE)
  • Radio (resource management) parameters, e.g. pilot power, antenna

tilt, neighbour cell lists, SHO/CC/CAC/scheduling parameters, …

  • Consortium

WHO IS WHO?

SOCRATES

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  • Objectives
  • Development of novel concepts, methods and algorithms for the

effective self-organisation of wireless access networks

  • Specification of the required information, its statistical accuracy and the

methods of retrieval incl. the needed protocol interfaces

  • Validation and demonstration of the developed concepts and methods

for self-organisation through extensive simulation experiments, assessing the established capacity/coverage/quality enhancements, and the attainable O/CAPEX reductions

  • Assessment of the operational impact of the developed concepts and

methods for self-organisation, with respect to the network operations, e.g. radio network planning and capacity management processes

  • Influence on 3GPP standardisation and NGMN activities

WHO IS WHO?

SOCRATES

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  • Evolutionary approach
  • Quantitative character
  • Development of methods and algorithms
  • Quantitative assessment
  • Simulation of scenarios
  • Contacts and cooperation
  • FP7  E3, 4WARD, EFIPSANS, EURO-NF, ….
  • COST 2100
  • 3GPP, NGMN, WWRF

WHO IS WHO?

SOCRATES

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  • Work packages
  • WP1 ‘Project management’
  • WP2 ‘Use cases and framework for self-organisation’
  • Use cases, requirements
  • Assessment criteria
  • Development framework

parameter groups and relations, relations between SO-SC-SH

  • WP3 ‘Self-optimisation’
  • Development and assessment of algorithms
  • Impact on measurements, architecture and interfaces
  • WP4 ‘Self-configuration and self-healing’
  • Development and assessment of algorithms
  • Impact on measurements, architecture and interfaces
  • WP5 ‘Integration, demonstration and dissemination’
  • Integration, demonstration, implications,

exploitation, liaisons to 3GPP/NGMN, dissemination

FINISHED ON-GOING WHO IS WHO?

SOCRATES

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Come and see us at the joint workshop* on

‘Self-organisation for beyond 3G wireless networks’

at ICT Mobile Summit ’09 in Santander, Spain

WHO IS WHO?

SOCRATES

*pending approval

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OUTLINE

  • INTRODUCTION
  • DRIVERS
  • VISION
  • EXPECTED GAINS
  • USE CASES
  • CHALLENGES
  • WHO IS WHO?
  • CONCLUDING REMARKS
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  • Self-organisation is gaining attention …
  • … for
  • O/CAPEX reduction
  • enhancement of capacity, coverage, quality
  • … by
  • 3GPP:

standardisation of protocols, architecture, interfaces, measurements

  • NGMN: operators’ vision based on use cases;

discussion of vendor proposals

  • FP7:

development, assessment, demonstration of algorithms derivation of impact on standards and network operations

CONCLUDING REMARKS

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