analysing effects of malfunctions on the performance of umts radio access networks
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ANALYSING EFFECTS OF MALFUNCTIONS ON THE
PERFORMANCE OF UMTS RADIO ACCESS NETWORKS
Author: Antti Keintola
Supervisor: Professor Sven-Gustav HäggmanInstructor: M.Sc. Anna Merjamaa
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© Ericsson AB 2005 Antti Keintola 2006-01-312
Agenda
Background Research problem and objectives Methods Analysis Results Summary
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Background
3G networks are launched all over the world Technology is complex and still somewhat immature Not much experience in operating and troubleshooting
the network Networks are not performing at the optimal level Faults and failures occur Troubleshooting is time consuming and finding the root
cause is difficult Performance statistics is sometimes the only source of
information available
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Research problem and objectives
What faults contribute most on the performance degradation?
Is it possible to find the cause of the failure by inspecting statistics?
What actions should be performed to improve performance?
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Methods
Counter data was collected from a live network– 7 RNCs, 1906 Node Bs– 28 day period– Only daily statistics, not hour or quarter data available
Improvements made simultaneously Data analysed with spreadsheet tool
– Laborious, slow– Need for dedicated tool
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Key Performance Indicators defined:– Call Completion Success Rate (CCSR)– Accessibility– Retainability
CCSR = Accessibility * Retainability
Methods
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Analysis – network
The net degradation of performance were calculated and dominant days were identified
Detailed analysis focused on days highlighted with red and yellow
Day Net contrib.
Day Net contrib.
1 3,50% 15 3,85%
2 3,69% 16 3,92%
3 2,91% 17 4,08%
4 2,63% 18 3,20%
5 3,29% 19 2,76%
6 3,61% 20 3,40%
7 4,14% 21 3,99%
8 4,52% 22 3,75%
9 3,67% 23 3,91%
10 3,43% 24 3,25%
11 2,80% 25 3,41%
12 4,81% 26 3,46%
13 3,36% 27 3,33%
14 3,87% 28 3,44%
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Analysis – accessibility
Accessibility was studied first– Almost all accessibility failures related to RRC rejects
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Analysis – RRC at RNC level
Six distinct faults were identified by analysing RNC RRC statistics
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Analysis – retainability
Speech and packet drops were studied separately
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Analysis – Radio Access Bearers
Drop rate analysis were done at RNC level– Basically RAB releases were investigated
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Results – accessibility failures
Following defects were identified and their net contribution to the overall performance were calculated
Transmission fault affects three out of seven RNCs, hence higher figure
Software and hardware defects have small impact on the overall performance
Fault Net contribution
Parameter fault 2,19%
Software fault 1,09%
AAL2 fault 1,62%
Hardware failure
0,95%
Cabling fault in core network
1,20%
Transmission fault
4,22%
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Results – accessibility failures
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Results – retainability failures
Speech calls
Packet connections
Fault Net contribution
Software fault 1,66%
Hardware failure
1,25%
Transmission fault
6,68%
Fault Net contribution
Design fault 10,72%
Parameter fault 11,29%
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Results – retainability failures
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Summary
Defects with significant impact on the network performance were identified
Impacts on the performance were calculated
Man-made defects have more severe impacts than software or hardware faults
The reasons for man-made faults should be worked out Working instructions and procedures should be revised and
improved Need for dedicated tool to analyse data from customer network
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Traffic properties
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Traffic properties
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Traffic properties
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Traffic properties
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