1. Janne Myllylä T-110.456 GPRS optimisation and Network visualization

2. Janne Myllylä T-110.456 Topics What do we need to know? Different types of information available Basics of GPRS capacity optimisation

3. Janne Myllylä T-110.456 Planning The network elements: type specific information (e.g. family, radiation patterns) current settings Geographic information Land use Building height Statistics Models

4. Janne Myllylä T-110.456 Planning Using the information we can estimate: Network capacities in different areas Overall service quality Affect of changes in the network Problems: Models work in a perfect world Map information is never up-to-date or accurate Butterfly effect

5. Janne Myllylä T-110.456 Are there more accurate methods? Network performance can also be measured Field measurements Network measurements

6. Janne Myllylä T-110.456 Optimisation basics Nokia NetAct Measure Analyse Optimise Provision

7. Janne Myllylä T-110.456 Measurement types Call/Session Radio Quality Volume

8. Janne Myllylä T-110.456 Field measurements + Basically a modified cellural phone is driven on a route. Reliable information available without much traffic volume Vendor independent Can measure competitors network performance - A lot of driving around needed. Measurement sample time is very limited

9. Janne Myllylä T-110.456 Network measurements + Almost all possible events are measured. Measurements span over a longer timeperiod - Not very standardized. Different vendors measure and collect slightly different data. Moderate traffic volume is needed for reliable measurements. The total amount of data is huge.

10. Janne Myllylä T-110.456 Busy Hour The distribution of traffic is not even. During weekdays there occurs peaks in the network usage. Radio networks don’t generally react well to traffic increase According to common sence: Network behaviour during the busy hour is the weakest link. Heuristics can be used to identify the bh.

11. Janne Myllylä T-110.456 What is visualized Network static information Locations & directions Parameter values Relations between elements

12. Janne Myllylä T-110.456 What is visualized There are dozens of raw measurements (Performance Indicator) that are related to GPRS performance. User wants to see the result of a preliminary analysis based on the raw measurements (Key Performance Indicator).

13. Janne Myllylä T-110.456 KPI Traditional benchmarks ( BER, FER, CSR, HSR ) (E) GPRS data related Reliability, max probability of erroneous RLC Throughput, amount of RLC payload Delay, measured time between SGSN and mobile (E)GPRS load, timeslots utilized by GPRS service And many more

14. Janne Myllylä T-110.456 Visualizing KPI Snaphot of network state: Performance of network on map List of elements not behaving within thresholds Trend of measurements Time based comparison between different elements / measurements Performance animations on map

15. Janne Myllylä T-110.456 Network capacity balancing In GSM network the available capacity is defined by timeslots dedicated for different services. It is possible to dimension timeslot usage between SDCCH CS PS

16. Janne Myllylä T-110.456 Visualization of timeslot usage

17. Janne Myllylä T-110.456 Visualizing service performance

18. Janne Myllylä T-110.456 Visualizing cell level performance

19. Janne Myllylä T-110.456 Effect of timeslot redimensioning % The relevant analysis of service performance need to be continuous, since without increase of total capacity timeslot dimensioning is always compromise.

20. Janne Myllylä T-110.456 Treatment classes Assigning GPRS capacity for different service classes PoC Streaming Corporate MMS Diverse DL/UL QoS requirements.

21. Janne Myllylä T-110.456 Capacity and QoS Capacity offered for various services SMSSpeech GPRS TREC 0 TREC 1 TREC 2 TREC 3 Priorisation Capacity Balancing QoS Priorisation

22. Janne Myllylä T-110.456 Running out of capacity Dimensioning can now only be used to increase CS performance. The only way to improve PS performance is to increase the total capacity.

23. Janne Myllylä T-110.456 How to increase capacity Some of the traffic volume could be redirected to other cells A new serving cell can be setup TRXs can be added for the current cell(s) to increase total amount of timeslots Impact matrix

24. Janne Myllylä T-110.456 Impact matrix Also known as Interference matrix All cells whose signal has been measured in serving cells dominance area Handover possibility Used to determine which cells could cause interference with serving cell.

25. Janne Myllylä T-110.456 Interference basics The frequencies have traditionally been planned using reuse patterns and propagation models In order to increase the traffic capacity, the channel re-use becomes tighter Too tight use of the same and adjacent channels causes a decline of C/I  BER and FER increase, worse coding schemes

26. Janne Myllylä T-110.456 Interference without hopping When no hopping is used some timeslots will constantly have more problems than others. After too much reuse performance deteriorates quickly

27. Janne Myllylä T-110.456 Too tight reuse on map

28. Janne Myllylä T-110.456 Averaging behaviour Frequency hopping may be used to average network behaviour Main idea is to reduce continuous bad performance between mobile and bss.

29. Janne Myllylä T-110.456 Averaged behaviour on map

30. Janne Myllylä T-110.456 Hopping mode: BB In BB hopping TRX frequencies don’t change, but TRX serving the mobile phone does. Total amount of frequencies in BB hopping is the same as the number of TRXs. Also BCCH timeslots 1-7 are included in the hopping.

31. Janne Myllylä T-110.456 Hopping mode: RF In RF hopping TRX serving the mobile phone doesn’t change, but TRX frequencies do. In RF hopping an allocation list contains frequencies that are used. BCCH TRX is not hopping. N channels enables 64*N different hopping sequences. MAIO offset has as many values as allocation list has channels HSN can be selected from 64 different sequences.

32. Janne Myllylä T-110.456 Hopping mode comparison TRX-1 BB RF TRX-2 BB RF TRX-3 BB RF Mobile hops the same frequency pattern in both modes

33. Janne Myllylä T-110.456 Measured performance EFL DCR Basically RF hopping enables a more tight channel reuse

34. Janne Myllylä T-110.456 Extreme channel reuse Two types of service areas inside cell: Normal with regular reuse patterns (overlay) Small with extreme reuse (underlay) The same underlay frequencies are used even in neighboring cells. Cell tries to make as much as possible of the traffic volume to use the underlay frequencies.

35. Janne Myllylä T-110.456 Extreme channel reuse The same traffic volume can be managed with less frequencies. With this example situation 3 underlay TRXs could free 6 frequencies. underlay

36. Janne Myllylä T-110.456 References 3GPP TS 25.215 V6.0.0 Physical layer – measurements 3GPP TS 23.107 V6.2.0 QoS concept and architecture Halonen, Romero, Melero: GSM, GPRS and EDGE performance