Cell Outage Management in LTE Networks COST 2100 TD(09) 941 M. - PowerPoint PPT Presentation

FP7 ICT-SOCRATES Cell Outage Management in LTE Networks COST 2100 TD(09) 941 M. Amirijoo (Ericsson), L. Jorguseski (TNO ICT), T. Kürner (TU Braunschweig), R. Litjens (TNO ICT), M. Neuland (TU Braunschweig), L. C. Schmelz (Nokia Siemens Networks), U. Türke (Atesio)

Outline  Introduction  Components in cell outage management  First Results on the Controllability Study  Concept of X-Map-Estimation  Future work WWW.FP7-SOCRATES.EU 2/32 2/

Introduction  The first release of the 3GPP Long Term Evolution (LTE) standard has been finalized  Operators require significant reduction of manual network management for LTE  Introduction of self-organisation functionalities in LTE – Reduces manual network management – Enhances network performance  One aspect that benefits from self-organization is cell outage management (COM), which consists of: – Cell outage detection – Cell outage compensation WWW.FP7-SOCRATES.EU 3/3

Introduction  Reasons for outages, e.g.: – hardware and software failures, – external failures such as power supply or network connectivity  Outages – may not be detected for hours or even days – may require manual analysis and unplanned site visits  Outage detection function must timely inform the operator about the occurrence and the cause of an outage  Automatic compensation actions are triggered to alleviate performance degradation WWW.FP7-SOCRATES.EU 4/32

Components of Cell Outage Management Control
 parameters
 Operator
policy:
 Coverage,
QoS
 Compensa-on
 Measurements
 Detec-on
 Cov.
map
 es-ma-on
 Simula-on
tools
 Scenarios
 Assessment
criteria
 WWW.FP7-SOCRATES.EU 5/32

FP7 ICT-SOCRATES First Results on Controllability Study

Simulator UE
genera-on
  Monte-Carlo based static simulator will be used for cell outage Pathloss
(G‐matrix)
 compensation due to – Simpler modeling and Round
of
algorithm
itera-on
 – Faster execution time Cell
Selec-on
  At each iteration an eNodeB Simulate
PHY,
RRM
etc
 (sector): – Samples/gathers performance Sample
Performance
 – Updates radio parameters  The time between two iterations is Compensa-on
Algorithm
 assumed to be in the order of minutes or tens of minutes Final

 – Small correlation between the No
 snapshot?
 samples – Correlation is ignored WWW.FP7-SOCRATES.EU 7/32

Scenarios  Data traffic characterised by requested data rate DL = 1 Mbps and UL = 250 kbps  Quality/Coverage targets – 10th-% DL Throughput > 256 kbps – 10th-% UL Throughput > 128 kbps  Loads – High load: load such that coverage/quality targets are satisfied (46 UEs/cell) – Medium load: 50 % of high load (23 UEs/cell) – Low load: 1 UE/cell  Capacity driven layout – ISD = 500 m – Antenna downtilt = 15º – Consider high load, medium load, low load  Coverage driven layout – ISD = such that coverage/quality targets are satisfied => ISD = 2450 m – Antenna downtilt = 5º – Consider low load WWW.FP7-SOCRATES.EU 8/32

Definitions  Assessed region = first and second tier of sectors surrounding outage site  Cell grouping: – Group 1 = Blue group – Group 2 = Yellow group – Affected = 1st and 2nd tier of sectors and outage cells  Considered metrics: – Coverage (RS&DL&UL) – Quality: smallest 10-percentile DL & UL cell throughput  Control parameters: – Reference signal (RS) power – Tilt – UL power control parameter P 0 (target received power) WWW.FP7-SOCRATES.EU 9/32

Coverage Driven Layout – RS Power Group 2 RS power (ratio of nominal power )/ dB Group 1 RS power (ratio of nominal power )/ dB Group 1 RS power (ratio of nominal power )/ dB Need to increase the RS power to enhance coverage WWW.FP7-SOCRATES.EU 10/32

Coverage Driven Layout – RS Power Group 2 RS power (ratio of nominal power )/ dB Group 1 RS power (ratio of nominal power )/ dB Need to decrease the RS power to enhance UL quality WWW.FP7-SOCRATES.EU 11/32

Capacity Driven Layout – High Load Uptiling improves coverage (nominal tilt = 15 degrees) WWW.FP7-SOCRATES.EU 12/32

Capacity Driven Layout – High Load Uptiling decreases DL and UL quality WWW.FP7-SOCRATES.EU 13/32

Overall Summary of Simulation Results Control parameter = RS power, P 0 , Tilt Impact on Impact on Impact on coverage DL quality UL quality 87.5-94.5% 80-185 kbps 55-105 kbps Capacity-driven, high 75-94% 110-225 kbps 10-100 kbps load 86-99% 70-220 kbps 15-110 kbps 87.5-94.5% 170-340 kbps 160-250 kbps Capacity-driven, 81-98% 210-410 kbps 50-250 kbps medium load 86-99% 125-400 kbps 60-250 kbps 91.5-94.5% Not affected Not affected Capacity-driven, low 75-99% Not affected Not affected load 86-99% Not affected Not affected 92.5-96.5% Not affected 120-210 kbps Coverage-driven, low 55-96% Not affected 170-250 kbps load 82-96% Not affected 80-200 kbps WWW.FP7-SOCRATES.EU 14/32

Conclusion  RS power, P 0 and tilt have impact on coverage and DL/UL quality – Degree of impact depends on network layout and load  Coverage – Tilt has highest impact – Impact of P 0 depends on load – RS power has lowest impact  DL quality – All parameters have impact for capacity driven and high/medium load  UL quality – All parameters have impact for capacity driven and high/medium load – P 0 also impacts coverage driven layout (low load) WWW.FP7-SOCRATES.EU 15/32

Scenario  Hexagonal grid, 19 sites with 3 sectors each  eNodeB height = 32 m, UE height = 1.5 m  BW = 10 MHz  Max BS power = 46 dBm, Max UE power = 25 dBm  RS power ~ 10% Ptotal  Noise spectral density: – DL N 0 ≈ -199 dBW/Hz – UL -195 dBW/Hz  Pathloss = 128.1 + 37.6 log10(r) [3GPP@2GHz]  Shadowing STD = 8dB  Shadowing correlation = 0.5 (sites), 1 (sectors)  Decorrelation distance = ISD / 15;  Minimum coupling loss = 75 dB;  3GPP 3D antenna model WWW.FP7-SOCRATES.EU 16/32

FP7 ICT-SOCRATES Concept of X-Map Estimation WWW.FP7-SOCRATES.EU 17/32

Concept of X-Map-Estimation  Objective – To automatically derive X-maps based on UE measurements and other sources of information requiring minimal human effort  Main principle – Connect UE event/measurements with estimated position – Gather UE reports to build map relating geo reference data and metric of interest  X-map can show, e.g., – Coverage related entities, e.g., pathloss, RSRP – Interference – End user perception (e.g. voice quality, throughput) – HO performance (success ratio, drop ratio) WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 18/32

Concept of X-Map-Estimation cont.  A UE delivers a measurement entitiy, e.g. – Reference Signal Received Power (RSRP) – CQI  UE position information is essential in order to derive X-maps WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 19/32

Implementaion of X-Map-Estimation Initial condition X-Map X-Map Est Measurement entity, Position estimate, Prediction, Confidence, Confidence (RAT) Localization & Measurement Manager Planning tool Measurement entity, (Position) ... UE source 1 UE source n WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 20/32

Accuracy of X-Map Estimation  Confidence of measurement depends on – Positioning accuracy – Measurement accuracy  Positioning accuracy is a function of, e.g.: – Radio environment (urban, suburban, indoor, outdoor) – Number of measured RBSs – Dynamic range of UE – Positioning technique  SOCRATES – is not interested in developing positioning techniques – assumes that proper positioning techniques are in place – is interested on good position error models WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 21/32

Position Error Modelling  For LTE three different localisation methods are planned – GPS – Observed Time Difference of Arrival (OTDOA) – Enhanced cell ID positioning methods  Model for the position error based on the Cramér-Rao lower bound  This model is based on the – Geometry of eNodeBs / satellites and the UE – Number of measured signals – Standard deviation of the measurement error (for GPS: 33.3 ns)  In the following preliminary results for GPS and OTDOA are shown WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 22/32

Simulation Scenario  Small realistic scenario of 1.5 km x 1.5 km in Braunschweig  Static and mobile users based on a mobility model  Network information available  Realistic path loss information derived from a prediction model Source: Google Earth 5.0  Satellite orbit for a specific date and time WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 23/32

Position Error Modelling - GPS  Application of Ray-Tracing to determine LOS Satellite-MS WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 24/32

Position Error Modelling - GPS histogram number of visible satellites  Direct path between UE and satellite  satellite is visible WWW.FP7-SOCRATES.EU WWW.FP7-SOCRATES.EU Prof. Dr.-Ing. Thomas Kürner, TU Braunschweig 25/32