1. On the use of cellular technology for digital TV Bi-directional return channel services Guilherme D. G. Jaime Flávio Pimentel Duarte Rosa Maria Meri Leão Edmundo de Souza e Silva Patricia A. Berquó José Roberto Boisson de Marca PESC-COPPE/UFRJ CETUC/PUC-RIO

2. COPPE/UFRJ CETUC/PUC-RIO 2 Summary Motivation & Goals Cdma2000 1xEV-DO: Overview Traffic Model EV-DO Model: Layers 1 e 2 Experiments, Results and Discussion Conclusions

3. COPPE/UFRJ CETUC/PUC-RIO 3 Motivation & Goals Evaluate EV-DO rev.0 as a alternative for the return channel of the Digital TV:  Throughput  Delay  User population  Fairness Could we do better?

4. COPPE/UFRJ CETUC/PUC-RIO 4 Cdma2000 1xEV-DO: Overview Reverse Link  Rates from 9.6 to 153.6Kbps per user BPSK modulation 53.30ms packets  Besides the data channel Control Channel Power controlled: - open loop - closed loop CDMA Phase reference for demod.; Channel timing Forward link rate sent to the BS Reverse Rate Indicator PilotDRC RRI ACK Forward channel data packets acknowledgment

5. COPPE/UFRJ CETUC/PUC-RIO 5 Reverse Channel: Rates and required gains PER = 1%

6. COPPE/UFRJ CETUC/PUC-RIO 6 Cdma2000 1xEV-DO: Overview Always at max. power 1.67ms TDM slots Forward Link Rates from 38.4kbps to 2.4Mbps through adaptive coding/modulation Depends on the state of the forward link Higher bit rates: lower robustness to channel impairments PFS recommended for slot allocation Main goal: throughput

7. COPPE/UFRJ CETUC/PUC-RIO 7 Cdma2000 1xEV-DO: Overview Forward Link (more...)  Four Packet Interlacing Avoids temporary monopolization of slots  Early Termination Gradual redundancy  Besides the data channel Control Channel PilotRPC RA Bit open loop power control closed-loop power control congestion control Always at max. power 1.67ms TDM slots

8. COPPE/UFRJ CETUC/PUC-RIO 8 Forward Channel: Mod./cod. e SINR/DRC PER = 1%

9. COPPE/UFRJ CETUC/PUC-RIO 9 Tangram-II Simulation Model Overview Simulation Tool:  Tangram-II (Federal University of Rio de Janeiro – Brazil)  Why Tangram-II instead of NS? Modeling is done through a high level interface: simplicity Includes additional high-level constructs to facilitate the modeling task COPPE/UFRJ CETUC/PUC-RIO

10. COPPE/UFRJ CETUC/PUC-RIO 10 Proposed model Detailed (Physical and Link layers) EV-DO model  Related work typically: Physical layer modeling Lack of detailed traffic model  Few works modeling higher layers: No open-source model presenting system capacity results as a function of user population No detailed fairness analysis Almost no clues on what could be done about fairness

11. COPPE/UFRJ CETUC/PUC-RIO 11 Traffic Model Assumptions  There is no users entering or leaving the system  No mobility – predominant scenario in the BDTvS

12. COPPE/UFRJ CETUC/PUC-RIO 12 Traffic Model (more...) Web users, on-off source COPPE/UFRJ CETUC/PUC-RIO

13. COPPE/UFRJ CETUC/PUC-RIO 13 EV-DO Model Assumptions:  A single EV-DO cell, no setorization: Thus, no soft-handoff  Early Termination not implemented Static users: low channel diversity

14. COPPE/UFRJ CETUC/PUC-RIO 14 EV-DO Model: Physical layer Propagation  Total power loss L total [dB] propagationpenetration Propagation loss penetration loss (10dB) shadowing fading (log-normal dist. de mean=0 and σ =8dB dense urban scenario)

15. COPPE/UFRJ CETUC/PUC-RIO 15 EV-DO Model: Physical layer Propagation (more...)  Okumura-Hata’s Propagation model for dense urban scenario Carrier frequency (450MHz) BS antenna height (40m) AT height (1.5m) dense urban correction factor :

16. COPPE/UFRJ CETUC/PUC-RIO 16 Power Control:  Open Loop Step 1: Pilot channel sensing Step 2: Choose the lowest power such that: After power losses it still reaches the receiver with enough strength to achieve the desired PER (1%) EV-DO Model: Physical layer

17. COPPE/UFRJ CETUC/PUC-RIO 17 Power Control (more…):  Closed loop Step 1: BS calculates for each user Step 2: Matches the received power with d Commands the AT to increase or decrease its power EV-DO Model: Physical layer pilot channel received energy total perceived interfering power thermal noise channel bandwidth (1.25MHz)

18. COPPE/UFRJ CETUC/PUC-RIO 18 DRC Estimation: Geometric Method Step 1: Measure the received power from the BS: X Step 2: Calculate SINR: Relation between X and the interference from rings 1 and 2 EV-DO Model: Physical layer First interfering ring Second interfering ring

19. COPPE/UFRJ CETUC/PUC-RIO 19 DRC Estimation :  Step 3: Find the higher DRC that matches the calculated SINR value, send it to the BS EV-DO Model: Physical layer PER = 1% DRC Rate (kbps) SINR (dB)

20. COPPE/UFRJ CETUC/PUC-RIO 20 Scheduling Algorithm – PFS  Choose user j  Updating average rate for user i EV-DO Model: Link layer Last DRC value Received from user i User i average transmission rate PFS “fairness” parameter User i current transmission rate

21. COPPE/UFRJ CETUC/PUC-RIO 21 Congestion Control  Noise rise – δ R δ R =N t /N 0 δ R = 5 as a threshold for the RA bit activation If the base station activates the RA Bit, ATs decreases its reverse date rate transmissions EV-DO Model: Link layer total interfering power thermal noise power

22. COPPE/UFRJ CETUC/PUC-RIO 22 Experiments: Considerations Dense urban scenario Web user population: from 10 to 80 Interest Metrics:  Throughput; Delay; Fairness Description0ValueUnit AT Maximum Power23dBm Antenna Maximum Power55.8dBm Penetration Loss10dB Thermal Noise-165dB PFS α0.001 Cable loss3dB Antenna Gain17dB AT Sensibility-119dB

23. COPPE/UFRJ CETUC/PUC-RIO 23 Results: User Throughput vs. Pop. and zone Zone Population Throughput (Kbps) Decreasing Throughput with increasing population and distance

24. COPPE/UFRJ CETUC/PUC-RIO 24 Results: User Delay vs. Pop. and zone Zone Population Delay (s) Increasing delay with increasing population and distance

25. COPPE/UFRJ CETUC/PUC-RIO 25 Results: User Throughput vs. PFS α PFS α - Extreme values: no significant fairness variation  α = 1 – Round Robin  α = 0.001 – PFS: Strong Throughput priority Zone throughput (Kbps) alpha = 1.0 alpha = 0.001 Round Robin PFS

26. COPPE/UFRJ CETUC/PUC-RIO 26 Discussion: Fairness issue Throughput, delay quite worse for the most distant users PFS α parameter adjustment  Same fairness issue  Worst overall throughput

27. COPPE/UFRJ CETUC/PUC-RIO 27 Proposed Solution: Directional Antenas Experiment 1: Experiment 2: Experiment 3: Distance Zone 1 23 … 8910 …………… … … … … no-users (no directional antennas) 2-zones 1-zone 1-user Former experiments:

28. COPPE/UFRJ CETUC/PUC-RIO 28 Results: User Thoughput - fairness through directional antennas Zone throughput (Kbps) No user 1-user 1-zone 2-zones From white to black bars: Increasing Fairness (thoughput) Population of 60 users

29. COPPE/UFRJ CETUC/PUC-RIO 29 Results: User Delay - fairness through directional antennas Zone Delay (s) No user 1-user 1-zone 2-zones From white to black bars: Increasing Fairness (delay) Population of 60 users

30. COPPE/UFRJ CETUC/PUC-RIO 30 Results: User throughput - directional antennas for two zones Zone throughput (Kbps) 60 users 80 users Increased population: No significant fairness difference  The are no direction antennas in zones 1 to 8 directional antennas

31. COPPE/UFRJ CETUC/PUC-RIO 31 Conclusions Detailed EV-DO model  Related work typically: Physical layer modeling Lack of detailed traffic model  Few works modeling higher layers: No open-source model presenting system capacity results as a function of user population Lack of detailed fairness analysis How bad is the fairness from the closets to the cell edge zones i.e. Distribution of directional antennas could be studied through our model

32. COPPE/UFRJ CETUC/PUC-RIO 32 Conclusions Population below 60 users:  Throughput and delay under control  Perceived quality among different zones has no significant variations Above 60 users:  Throughput, Delay and fairness deterioration Very simple solution for the considered experiments fairness issue  Directional antennas for the most distant users