FP7 ICT-SOCRATES Self-organisation in future mobile cellular networks Remco Litjens TNO ICT, Delft, The Netherlands
OUTLINE Introduction Drivers Vision Expected gains Use cases – Automatic neighbour cell list generation – Admission/congestion control – Cell outage management – Self-optimisation of Home eNodeBs Challenges Approaches Who is who? Concluding remarks WWW.FP7-SOCRATES.EU 2/ ∞
OUTLINE Introduction Drivers Vision Expected gains Use cases – Automatic neighbour cell list generation – Admission/congestion control – Cell outage management – Self-optimisation of Home eNodeBs Challenges Approaches Who is who? Concluding remarks WWW.FP7-SOCRATES.EU 3/ ∞
INTRODUCTION Wikipedia Self‐organisa2on is a process of a4rac2on and repulsion in which the internal organiza2on of a system, normally an open system, increases in complexity without being guided or managed by an outside source. Another a4empt (in the specific context of telecommunica2on networks) Self‐organisa2on is the automated (without human interven2on) adapta2on or configura2on of network parameters (in a broad sense), in response to observed changes in the network, traffic, environment condi2ons and/or experienced performance. Some examples may help … WWW.FP7-SOCRATES.EU 4/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 1: ‘Transmission Control Protocol’ – Operates end-to-end on the transport layer – Automatically adapts source transfer rate to end-to-end congestion level – Limits amount of data in transit – Slow start phase is followed by congestion avoidance phase • AIMR Additive Increase, Multiplicative Decrease TCP TCP IP IP IP IP MAC/RLC MAC/RLC MAC/RLC MAC/RLC PHY PHY PHY PHY SOURCE DESTINATION NODE NODE WWW.FP7-SOCRATES.EU 5/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 1: ‘Transmission Control Protocol’ – Operates end-to-end on the transport layer – Automatically adapts source transfer rate to end-to-end congestion level – Limits amount of data in transit – Slow start phase is followed by congestion avoidance phase • AIMR Additive Increase, Multiplicative Decrease NO PACKET TIMEOUT: PACKET TIMEOUT: CONGESTION WINDOW / 2 CONGESTION WINDOW + 1 WWW.FP7-SOCRATES.EU 6/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 2: ‘Routing in ad hoc networks’ – Automatic detection of connectivity – Automatic establishment of routes – Automatic rerouting upon node failure DESTINATION NODE SOURCE NODE WWW.FP7-SOCRATES.EU 7/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 2: ‘Routing in ad hoc networks’ – Automatic detection of connectivity – Automatic establishment of routes – Automatic rerouting upon node failure DESTINATION NODE SOURCE NODE WWW.FP7-SOCRATES.EU 8/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 3: ‘Uplink transmit power control in UMTS networks’ – Default case • Fixed transmit power Near-far effect! Battery drainage! – 1 st Self-optimisation loop • Adjust transmit power to meet SINR target • Responds to multipath fading variations – 2 nd Self-optimisation loop • Adjust SINR target to meet BLER target BLER • Adapts to user velocity SINR – 3 rd Self-optimisation loop • Adjust BLER target to meet end-to-end packet loss target? • Adjust power control steps? • Adjust power control heartbeat? UE NodeB RNC WWW.FP7-SOCRATES.EU inner loop outer loop power control power control 9/ ∞
SELF-ORGANISATION IN EXISTING NETWORKS Example 3: ‘Uplink transmit power control in UMTS networks’ outer loop power control responds to a velocity increase transmit power path gain inner loop power control follows mul2path fading WWW.FP7-SOCRATES.EU 10/ ∞
INTRODUCTION Context of this presentation – Mobile cellular communications networks 2011? LTE – LTE access technology • Long Term Evolution (E-UTRAN) 2006 + HSPA • Currently under standardisation • Focus on radio access network 2003 UMTS 2001 + GPRS 1994 GSM 1989 NMT 900 1985 NMT 450 1980 OBLB WWW.FP7-SOCRATES.EU 11/ ∞
INTRODUCTION Current networks are largely manually operated – Separation of network planning and optimisation – (Non-)automated planning tools used to select sites, 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, SOCRATES, … WWW.FP7-SOCRATES.EU 12/ ∞
OUTLINE Introduction Drivers Vision Expected gains Use cases – Automatic neighbour cell list generation – Admission/congestion control – Cell outage management – Self-optimisation of Home eNodeBs Challenges Approaches Who is who? Concluding remarks WWW.FP7-SOCRATES.EU 13/ ∞
DRIVERS Technogical perspective – Complexity of future/contemporary wireless access networks • Multitude of tuneable parameters with intricate dependencies • Multitude of radio resource management 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 WWW.FP7-SOCRATES.EU 14/ ∞
DRIVERS 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 WWW.FP7-SOCRATES.EU 15/ ∞
OUTLINE Introduction Drivers Vision Expected gains Use cases – Automatic neighbour cell list generation – Admission/congestion control – Cell outage management – Self-optimisation of Home eNodeBs Challenges Approaches Who is who? Concluding remarks WWW.FP7-SOCRATES.EU 16/ ∞
VISION Minimise human involvement in planning/optimisation Significant automation of network operations Key components – Self-configuration con2nuous loop – Self-healing – Self-optimisation triggered by incidental events WWW.FP7-SOCRATES.EU 17/ ∞
VISION Self-configuration – Incidental, intentional events – ‘Plug and play’ installation of new base stations and features • Download of initial radio network parameters, neigh- bour list generation, trans- con2nuous port network discovery loop and configuration, … Self-healing – Incidental, non-intentional events – Cell outage detection • Alarm bells • Triggers compensation – Cell outage compensation • Automatic minimisation of coverage/capacity loss triggered by incidental events WWW.FP7-SOCRATES.EU 18/ ∞
VISION Self-optimisation – Measurements • Performance indicators • Network, traffic, mobility, propagation conditions • Gathering via UEs, eNodeBs, probes • Optimal periodicity, accuracy, con2nuous loop format depends on parameter/ mechanism that is optimised – Automatic tuning • Smart algorithms process measurements into para- meter adjustments – E.g. tilt, azimuth, power, RRM parameters, NCLs – In response to observed changes in conditions and/or performance – In order to provide service avai- lability/quality most efficiently triggered by • Triggers/suggestions in case incidental events capacity expansion is unavoidable WWW.FP7-SOCRATES.EU 19/ ∞
OUTLINE Introduction Drivers Vision Expected gains Use cases – Automatic neighbour cell list generation – Admission/congestion control – Cell outage management – Self-optimisation of Home eNodeBs Challenges Approaches Who is who? Concluding remarks WWW.FP7-SOCRATES.EU 20/ ∞
EXPECTED GAINS 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 WWW.FP7-SOCRATES.EU 21/ ∞
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