Autonomous Self Organizing Radio Access Networks


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Autonomous Self Organizing Radio Access Networks

  1. 1. Self-X RANAutonomous Self Organizing Radio Access Networks Bell Labs Stuttgart Ulrich Barth June 2009
  2. 2. Self-X Business Perspective /Bell Labs SON vision All Rights Reserved © Alcatel-Lucent 2009 2
  3. 3. Self- organizing Radio Access NetworksMotivationCurrent situation for radio access network management Deployment and maintenance become more and more complex and cost extensive Trend to smaller cells, multi-band operation, heterogeneous mobile networks High manual intervention for configuration, capacity upgrade or in failure cases required High effort required for optimisation of system performance Deep system expertise required High effort necessary for measurement campaigns (drive tests) Different tools for planning, configuration, measurement/KPI acquisition and optimisation involved increasing effort for network management and optimisation new concepts for simplified network operation required All Rights Reserved © Alcatel-Lucent 2009 3
  4. 4. Self-X ArchitectureVision of fully distributed self-management “NEM less” network management NM OSS Fully autonomous, distributed Itf-N RAN optimisation Network Management X2-Itf Self-x functions in UE and eNB measurements, UE location info performance alarms, status reports, KPIs high level network monitoring performance tuning KPIs distributed self-x algorithms alarms Network management in NM OSS focussed on LTE RAN self-x network planning alarm and performance monitoring eNB self-x high level performance tuning self-x RAN self- optimization eNB eNB OSS: Operation Support System NEM: Network Element Manager All Rights Reserved © Alcatel-Lucent 2009 4
  5. 5. Self-Organizing Radio Access Network RAN configuration use cases: – Add/Remove cell incl. power saving cell – Neighborhood relation configuration and optimisation for LTE RAN optimization use cases tools for RAN planning, deployment new site, performance configuration add new cell, failure cases – Cell coverage optimization and capacity optimisation optimisation upgrade – Mobility robustness optimisation – Interference optimisation for LTE – Load Balancing conventional parameter self-configuration self-optimisation QoS optimization use cases configuration – Scheduler operation optimisation for LTE – MIMO mode selection optimisation for LTE All Rights Reserved © Alcatel-Lucent 2009 5
  6. 6. Self-Configuration of Radio parameters All Rights Reserved © Alcatel-Lucent 2009 6
  7. 7. Self-configuration of eNB Radio Parameters:Add Cell Use CaseAutomatic Self-Configuration of Radio Parameters deployment/removal of cells/sites Parameter Retrieval switching on/off of cells self-configurationVision: fully autonomous plug’n play classification operator templates own properties finding similar neighbors and environment only for: learning optimized configuration enabling config-parameter new features from similar neighbor eNBs/cells classification learning from preferences calculation, adaptation and similar neighbours negotiation of parameters neighbour selection: initial defaults similarity metric distributed approach based on Config. Parameter Calculation Operational Phase parameter classification outlier filter parameter calculation parameter adaptation self-optimisation similarity metrics negotiations with neighbours configuration management All Rights Reserved © Alcatel-Lucent 2009 7
  8. 8. Self-configuration of eNB Radio Parameters: Add Cell Use CaseWhat is and how to select a suitable neighbor? geographical proximity similarity of HW, cell properties (macro, micro, …; power class; …), environment parameter group wise retrieval from different eNBs (eNBs with different properties) C: distance measure, W: weights similarity metrics: Cim ,id = Wim • ( AΘBid ) A: current node, B: neighbor based on pm Θ: generalized difference vector representation of relevant parameters with weighting factors: vector norm based identification of similarity (e.g. Euclidean distance)Learning and storing good (optimized) configurations: some optimized parameter sets depend e.g. on time and date, load for use in restart situations for distinguishing different optimized configurations (e.g. load dependent) l2 recognition of parameter clustering cluster wise saving of configuration parameter sets cluster dependent reload of configuration data l1 All Rights Reserved © Alcatel-Lucent 2009 8
  9. 9. Automatic Neighbour Relation All Rights Reserved © Alcatel-Lucent 2009 9
  10. 10. Automatic Neighbour Relation Function (ANR) eNB W-CDMA needs NRT for UE measurements Report Phy CID 5 Strong Signal Cell A UE are configured by NodeB which UE Phy CID 3 cell to be measured (e.g. for HO) Cell Global ID 17 Centralized NRT planning required No such restriction in LTE X2 all UEs can measure the Physical Cell ID (PCI) of all neighbours Cell B SON ANR Phy CID 5 eNB can request the UE to measure algorithm Neighbor Cell Global ID 19 the Cell Global ID (CGI) related to eNB Neighbor the PCIup to 15 eNBs eNB PCI/CGI is the key info needed in Neighbour Relationship Table NRT to map it further to the IP (NRT) per cell address of eNB X2 Setup between the eNBs to enable handover All Rights Reserved © Alcatel-Lucent 2009 10
  11. 11. Automatic Neighbour Relation Function (ANR)Bell Labs decentralized proposal for ANR Start with empty NRT list Generation of NRT only based on UE measurements 2 1 6 5 Update/fine tuning based on handover optimisation 3 4 Detection and correction of PCI collision/based on ANRSimulation Assumption for feasibility study Measure Convergence Time and HO failure in worst case scenario Only information from HO signalling is used No additional measurements used No signalling with neighbour cells Full radio simulation All Rights Reserved © Alcatel-Lucent 2009 11
  12. 12. NRT Simulation (Hexagonal Grid layout 57 cells) Inter Site Distance = 500 m 95% Quantile of the NRT Completion Time 1700 HO Drops Due to Incomplete NRT 1600 3 km/h 100 1500 30 km/h 3 km/h 1400 90 1300 120 km/h 30 km/h 1200 80 120 km/h 1100Time [sec] 70 HO Drop [%] 1000 900 60 800 50 700 600 40 500 400 30 300 20 200 100 10 0 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 No. of UEs Per Cell No. of UEs Per CellNRT list setup only based on UE measurement feasible Convergence time sufficiently short Worst case scenario simulated, as only UEs in handover process participate to NRT All Rights Reserved © Alcatel-Lucent 2009 12
  13. 13. SON: Autonomous Coloring Algorithm forFrequency assignment All Rights Reserved © Alcatel-Lucent 2009 13
  14. 14. Autonomous Coloring Algorithm for Frequency assignment Inter-Cell Interference Self configuring and Coordination optimizing NetworkP Hand Over failure reduced by 5 fold f 1 2 3 4 5 6 7 Increased the throughput up to 27%P Performance increase in call set up f 1 2 3 4 5 6 7 Improve performance Self-organizing at cell edge pattern assignment All Rights Reserved © Alcatel-Lucent 2009 14
  15. 15. Inter-Cell Interference Coordination (ICIC) on terminal mobility P Frequency Pattern a. Mobile is scheduled to sub-band 3 green cell with negligible interference from orange cell Pfull b. Mobile is scheduled to sub-band 2, a where orange cell radiates with f 1 2 3 4 5 6 7 lowered power b a c. Mobile is handovered from green cell to orange cell b c d c d. Mobile is scheduled to sub-band 4, where green cell radiates with lowered power Frequency Pattern P orange cell e. Mobile is scheduled to sub-band 3 e e d with negligible interference from Pfull cell 1 f 1 2 3 4 5 6 7 All Rights Reserved © Alcatel-Lucent 2009 15
  16. 16. Autonomous Coloring Algorithm for Frequency assignmentMotivation • Bell Labs ICIC approach requires frequency planning But frequency planning is OPEX consuming • Provide a self-organizing solution for cell (sub-)frequency (‘colour’) assignmentChallenges and Bell Labs Solutions • Known mathematical approaches are only centralized ... Fully distributed colouring algorithm inside each eNB • ... and require much too much computation effort for real networks Efficient solution inside restricted areas by a novel successive algorithm • Existing approaches are not adapted to the radio networks KPI for algorithm based on Interferences and n-tier neighbours Best suited colour solution found – also when a perfect one does not exist • Decentralized systems can be susceptible to ‘instabilities’ Advanced mechanisms to detect and resolve oscillation effects Advanced functionality to avoid “a moving wave of changes through the network” All Rights Reserved © Alcatel-Lucent 2009 16
  17. 17. Major Steps of the Self Organizing + Self Optimizing SON Algorithm Self Adaptation: Neighbour Relation Table (NRT) sufficiently filled Add/Drop Cell, Scenario Creation / Update inside the eNB NRT Change Fast Initial Colouring: Each cell colours itself - if possible ICIC immediately operational Local Area Colour Optimization: Optimizing the colour assignment for several cells Periodic Resolving sub-optimal neighbour colour assignments optimiza- Finding the optimal interference situation tion by Several advanced mechanisms to prevent instabilities each cell ... - Algorithm + signalling 3GPP compliant (i.e. LTE Rel.8) - Fully distributed algorithm, runs inside each eNB All Rights Reserved © Alcatel-Lucent 2009 17
  18. 18. Operation of SON ICIC algorithmInitial eNB based (self-) assignment offrequency patterns for ICIC network is already in operational state without lowered sub-bands (i.e. re-use 1” ― no frequency pattern is assigned) self-assignment is started when the NRT has settled after ANR the found assignment is stable while the particular NRTs do not change significantly All Rights Reserved © Alcatel-Lucent 2009 18
  19. 19. Operation of SON ICIC algorithmModification of network deployment Addition of Omni-directional cell Initial color is chosen to the fewest interference load (best neighbour) Subsequent optimization procedure finds a solution by re-coloring the own cell and a further (neighbour) cell All Rights Reserved © Alcatel-Lucent 2009 19
  20. 20. Operation of SON ICIC algorithmModification of network deployment Replacement of Omni-directional cell with tri-sectorized basestation Quick reaction of neighbors on changed neighborhood in NRT All Rights Reserved © Alcatel-Lucent 2009 20
  21. 21. Mobility Robustness (Handover Optimization) All Rights Reserved © Alcatel-Lucent 2009 21
  22. 22. Configuration Parameters for Handover in LTE Filtered RSRP [dB] Source Cell Target Cell Radio problem Hyst(dB) detection T1 (e.g. 500 ms) Radio link failure RLF threshold TTT (ms) P(ms) Handover Handover Time Event A3 Command LTE handover more sensitive compared to W-CDMA Configuration parameters Filtered RSRP values Handover Margin, i.e. hysteresis between source and target Time to trigger (TTT) Cell Individual Offset (CIO) All Rights Reserved © Alcatel-Lucent 2009 22
  23. 23. Targets For Self-Optimization of Handovers (HO) To increase network performance by the minimization of Radio Link Failures (RLF) and ping pong effects occurring due to inappropriate HO parameters To avoid manual update and setting of HO parameters after the initial deployment To monitor neighbor specific HO problems Each cell monitors the HO problems occurring due to its own parameters or due to specific neighbor’s parameters Every cell autonomously detects and resolves the HO problems by using decentralized self-detection and optimization algorithms To avoid drive tests run specially for the detection of such problems All Rights Reserved © Alcatel-Lucent 2009 23
  24. 24. Classification of HO ProblemsRLF due to inappropriate HO decisions and HO parameter settings RLF before HO RLF before source cell receives UE measurement report for initiation of HO detection by source or neighbor cells RLF during HO RLF in source cell occurring during HO (HO command failure) detection by source or neighbor cells RLF just after HO RLF in target cell just after the successful HO detection by target cellShort Stays Ping pong effect Rapid handovers between two neighbor cells Island effect Handover from Cell A to Cell C and successive rapid handover from cell C to Cell B instead of handover directly from Cell A to Cell B (avoid short stay in Cell C so called hot spot or island effect) All Rights Reserved © Alcatel-Lucent 2009 24
  25. 25. Possible Handover OptimizationAvoiding high handover failure rates or too many short stays Detection of non-suitable neighbor relations by collecting and analyzing handover statistics Optimization algorithms have to deal with rare and sporadic input values Avoid handovers to non-suitable neighbors Considering that in some cases only specific locations at cell borders are non-suitable All Rights Reserved © Alcatel-Lucent 2009 25
  26. 26. Possible Handover OptimizationOptimization by modification of HO parameters Make sure handover problems are caused within the source cell Options for modification of HO parameters in source cell Handover Margin (HOM) Time to Trigger HO (TTT) Filter Coefficient and Cell Individual Offset (CIO) Simulation results Normalized HO Rate Vs Residual BLER for ; TTT=0 to 200 ms; 20ms step HOM and Filter Coefficient can be fixed 35 TTT must be selected depending 30 Normalized HO Rate upon the UE speed 25 20 15 10 5 0 0 1 2 3 4 5 6 7 8 9 10 BLER [% ] All Rights Reserved © Alcatel-Lucent 2009 26
  27. 27. Coverage and Capacity Optimisation All Rights Reserved © Alcatel-Lucent 2009 27
  28. 28. Coverage Optimization for LTETargets detection and minimization of coverage & capacity problems load / UE density depending tilting cell outage compensation & power saving by switching cells off/onVision after planning and deployment of a new cell: fully automatic / autonomous optimization in eNB: antenna tilt, TxPower replacement of drive tests decentralized / distributed approachNew optimization process required: STATE OF THE ART SON TARGET cell global drive tests, UE cell global UE measurements PM counters call based traces PM counters UE location info optimization algorithm based root cause analysis algorithm design automatic measurementtool and expert based partly automated, expert driven know how shift decentralized: configuration, continuous, from OAM expert data evaluation centralized: to manufacturer ⇒ offline, (planning) tool based re-planning optimization optimization algorithm expert know how algo design parameter adaptation parameter adaptation All Rights Reserved © Alcatel-Lucent 2009 28
  29. 29. Coverage Optimization for LTEChallenges: complex optimization problem: collaborative (w.r.t cells and sites) and predictive optimization required interdependency with other self-x/SON optimization targets (e.g. HO optimization, load balancing) spatially resolved detection based on UE measurements required: areas with insufficient coverage / low SINR / high interference areas with high traffic (hot zones) limitations/constraints regarding UE based measurements: accuracy, range and availability (radio link based and positioning data) statistical nature adaptation to network dynamics mid and long term changes in traffic load/distribution, interference, neighbor relations All Rights Reserved © Alcatel-Lucent 2009 29
  30. 30. Outage CompensationCell outage compensation by power variation no real compensation by power reduction of neighbours power increase: drawback large over provisioning required azimuth variation good compensation results (almost complete coverage) but: normally not available in the field antenna tilting at least partial compensation expected All Rights Reserved © Alcatel-Lucent 2009 30
  31. 31. Coverage Optimization for LTEImpact of tilt: Simulation model:CDF of Geometry reflects situation channel model: Okumura Hata, in entire simulated area. shadow fading 10dB std dev. SINR: serving cell selection by strongest signal, Example with various tilt angles interference: sum of all remaining cells 9-21 degrees, 15 degrees provide interference limited optimum coverage. ° ° ° ° ° 09° 12° 15° 18° 21° 500m inter site distance coverage problems All Rights Reserved © Alcatel-Lucent 2009 31
  32. 32. Coverage Optimization for LTEOptimisation goals: optimize CDF especially for low geometry values view: cell global - 3dB Problem of 3-sectorised base stations with re-use 1: locations where 3 sectors have almost the same signal strength local problem, put in areas of very low user density discrete coverage hole: local geometry optimization problem with high relevance user density/ load: conditional probability distributions can be employed: e.g. exclude locations w/o users, there is no need to provide coverage at all optimize geometry in high traffic zones All Rights Reserved © Alcatel-Lucent 2009 32
  33. 33. Load Balancing All Rights Reserved © Alcatel-Lucent 2009 33
  34. 34. Load Balancingbased on HO parameter modification: LTE intra frequency handover 0,2 w/o ICIC without ICIC 0,18 TTTH=0.050 sec critical in re-use 1 schemes: 0,16 TTTH=0.100 sec HO Rate [1/s] 0,14 TTTH=0.150 sec 0,12 – no scrambling gain 0,1 0,08 0,06 – lower limit for usable SINR range 0,04 0,02 0 – especially critical: HO command 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 BLER [% ] potential for load balancing rather low Residual BLER [%] (RLF) with ICIC with static ICIC, reuse 7/6 0,2 LTE inter frequency HO 0,18 0,16 TTTH=0.050 sec TTTH=0.100 sec HO Rate [1/s] 0,14 TTTH=0.150 sec no cell overlap SINR problem 0,12 0,1 0,08 – e.g. hierarchical cell structures 0,06 0,04 0,02 – to be considered: UE velocity vs. cell size, 0 QoS requirements (e.g. GBR, NGBR) 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 Residual BLER [%] (RLF) load balancing possible Inter system HO also no cell overlap SINR problem – to be considered: service QoS requirements load balancing possible All Rights Reserved © Alcatel-Lucent 2009 34
  35. 35. Load Balancingother approaches for intra frequency LTE: DL Power modification increased power in unloaded neighbour cells: – requires PA over provisioning – UL critical decreased power in overloaded cell: – possible in interference limited (urban) scenarios – degrading indoor coverage to be investigated 1 2 3 4 5 6 7 – risk of local coverage spots ongoing investigation Interference coordination enabled load balancing: IFCO as Enabler dynamic allocation of subbands for reduced power load reduction by dynamic IFCO based interference reduction seems to have higher potential, ongoing investigation 1 2 3 4 5 6 7 All Rights Reserved © Alcatel-Lucent 2009 35
  36. 36. All Rights Reserved © Alcatel-Lucent 2009 36