GPRS optimisation and Network visualization

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

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

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

4. 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 Janne Myllylä T-110.456

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

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

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

8. 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 Janne Myllylä T-110.456

9. 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. Janne Myllylä T-110.456

10. 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. Janne Myllylä T-110.456

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

12. 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). Janne Myllylä T-110.456

13. 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 Janne Myllylä T-110.456

14. 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 Janne Myllylä T-110.456

15. 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 Janne Myllylä T-110.456

16. Visualization of timeslot usage Janne Myllylä T-110.456

17. Visualizing service performance Janne Myllylä T-110.456

18. Visualizing cell level performance Janne Myllylä T-110.456

19. Effect of timeslot redimensioning % The relevant analysis ofservice performance need tobe continuous, since withoutincrease of total capacitytimeslot dimensioning is alwayscompromise. Janne Myllylä T-110.456

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

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

22. Running out of capacity Dimensioning can nowonly be used to increaseCS performance.The only way to improve PSperformance is to increasethe total capacity. Janne Myllylä T-110.456

23. 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 Janne Myllylä T-110.456

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

25. Interference basics • The frequencies have traditionally been planned usingreuse 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 Janne Myllylä T-110.456

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

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

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

29. Averaged behaviour on map Janne Myllylä T-110.456

30. 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. Janne Myllylä T-110.456

31. 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 frequenciesthat 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. Janne Myllylä T-110.456

32. Hopping mode comparison Mobile hops the same frequency pattern in both modes Janne Myllylä T-110.456

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

34. 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. Janne Myllylä T-110.456

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

36. 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 Janne Myllylä T-110.456