1. Department of Electronics and Telecommunications March 15 th 2004 1 “A dynamic rate allocation technique for wireless communication systems” Romano Fantacci Full Professor Francesco Chiti Ph.D. Daniele Tarchi Ph.D. Department of Electronics and Telecommunications University of Florence Via di S. Marta, 3 I-50139 Florence, ITALY E-mail: {fantacci,chiti,tarchi}@lenst.det.unifi.it

2. Department of Electronics and Telecommunications March 15 th 2004 2 Outline 1.Motivations –3G systems features –UMTS-HSDPA 2.ALC Protocol Proposal –Physical channel –Proposed rate allocation protocol –System block diagram –Traffic sources –Overall Markov model –Analytical model 3.Numerical Results –N( ), T( ) theoretical and simulated –Gain 4.Conclusions and further developments

3. Department of Electronics and Telecommunications March 15 th 2004 3 Future wireless networks features 1. Motivations Global coverage by means of: –Efficient internetworking with existing wireless and wired standards by resorting to a cooperative approach rather than competitive –High mobility and variable traffic load management through dynamic Radio Resource Management policies (RRM): cell planning system reconfiguration Services integration –Multimedia traffics with real time (voice, audio/video streaming) and data (Web services, Data Base queries) applications –Different Quality of Service (QoS) requirements (bandwidth, error rate, delays) –Asymmetric connections handling

4. Department of Electronics and Telecommunications March 15 th 2004 4 1. Motivations Universal Mobile Telecommunications System 144 Kbps 500 Km/h 384 Kbps 120 Km/h 2 Mbps 10 Km/h UMTS/HSDPA cdma2000/1xEVDO IEEE802.11x TETRA2

5. Department of Electronics and Telecommunications March 15 th 2004 5 1. Motivations H igh S peed D ownlink P acket A ccess 3GPP Release 5 (2001) arranges a further downlink access scheme to handle asymmetric, high bit rate, bursty data services in an indoor environment. This purpose could be achieved by, eventually, joint selection of the following strategies: 1.Adaptive Modulation and Coding (AMC) schemes 2.Hybrid Automatic Repeat reQuest (H-ARQ) techniques 3.Fast scheduling algorithms 4.Multiple Inputs Multiple Outputs (MIMO) channel modelling 5.Fast Cell Selection (FCS) algorithms Constraints: Peak bit rate up to 10 Mbs No QoS degradation

6. Department of Electronics and Telecommunications March 15 th 2004 6 2. ALC Protocol Proposal Modulation and Coding Schemes I II III MRcRc R [bit/symb] I  II QPSK1/21 III 16QAM1/22

7. Department of Electronics and Telecommunications March 15 th 2004 7 2. ALC Protocol Proposal Physical Channel Model GOOD BAD

8. Department of Electronics and Telecommunications March 15 th 2004 8 T good, T bad : exponentially distributed P T : threshold power level P R : average received power level 2. ALC Protocol Proposal Exponential (memoryless) hypothesis [Gupta84] Physical Channel Model

9. Department of Electronics and Telecommunications March 15 th 2004 9 2. ALC Protocol Proposal Discrete Memoryless Channel (DMC) Bad 0 Good 1 channel transition probability between i state and j state within a slot: exponentially (geometrically) distributed mean value related to received signal power and user mobility Physical Channel Model

10. Department of Electronics and Telecommunications March 15 th 2004 10 1.Base Station (BS) manages downlink streams according to a FIFO scheduling policy 2.Whenever an End User (EU) is selected, BS discretely monitors EU physical channel conditions 3.Depending on channel state, a proper AMC scheme is chosen 4.BS allocates to this EU both: Dedicated Physical Channel (DPCH) Downlink Shared Channel (DSCH) with a variable shared capacity 2. ALC Protocol Proposal Proposed Protocol

11. Department of Electronics and Telecommunications March 15 th 2004 11 2. ALC Protocol Proposal System Block Diagram (uplink/downlink) Proposed Protocol

12. Department of Electronics and Telecommunications March 15 th 2004 12 Traffic Sources Poisson packet arrivals Poisson message arrivals: 1.Modified Geometric distribution of packet within each message 2.Pareto message length (constant length packets): simplified Web traffic 3.Pareto packet length and Exponential packet inter-arrivals: real Web traffic) 3. approaches 2. in the presence of an high capacity CN connection 2. ALC Protocol Proposal System Model

13. Department of Electronics and Telecommunications March 15 th 2004 13 Traffic Sources Poisson packet arrivals: Batch message arrivals  Geometrical message length:  Pareto message length: k packets arrival probability within a slot 2. ALC Protocol Proposal System Model

14. Department of Electronics and Telecommunications March 15 th 2004 14 2. ALC Protocol Proposal System Model DT Embedded Markov chain model [Neuts89] Vectorial state (i,j): i : status of the transmission channel j : number of packets in the queue

15. Department of Electronics and Telecommunications March 15 th 2004 15 2. ALC Protocol Proposal Steady State Equations probability of being in i phase with j queued packets probability of having k packets arrivals System Model

16. Department of Electronics and Telecommunications March 15 th 2004 16 arrival generating function average queued packets average queuing time (by Little formula) 2. ALC Protocol Proposal Transformed Domain Equations System Model

17. Department of Electronics and Telecommunications March 15 th 2004 17 3GPP standard compliant:  IPv6 fast backbone: -maximum message length equal to 5 MB (truncated Pareto pdf) -packet length equal to 1.5 KB  Time slot (TTI) equal to 2 ms  Bit rate equal to 1.92 Mbps Worst case multipath fading: and r 01 = r 10 = 0.2 (duty cycle = 0.5) Infinite shared memory buffer length: no dropping effect ARQ policy belonging to GB class (RTT<TTI) P outage equal to 5% 3. Numerical Results Operative Assumptions

18. Department of Electronics and Telecommunications March 15 th 2004 18 NePSi: a Network Protocol Simulator NePSi (Network Protocol Simulator) is a Discrete Event Simulator It is based on C++ programming language Object oriented programming is used in order to model different entities in the system S. Nannicini, T. Pecorella, L. S. Ronga, “IneSiS: Integrated Network Protocols and Signal Processing Simulator”, Sixth Baiona Workshop 1999, Vigo, Spain. Available at http://lenst.det.unifi.it/INeSiS/ under GNU License.http://lenst.det.unifi.it/INeSiS/ 3. STF 179 Proposal

19. Department of Electronics and Telecommunications March 15 th 2004 19 3. Numerical Results Poisson packet arrival: HSDPA Gain: improving transport bit rate or network capacity (QoS) or decreasing on board device complexity

20. Department of Electronics and Telecommunications March 15 th 2004 20 HSDPA Gain: lowering expected delay (QoS) 3. Numerical Results Poisson packet arrival:

21. Department of Electronics and Telecommunications March 15 th 2004 21 Moderate impact on protocol efficiency 3. Numerical Results Poisson packet arrival:

22. Department of Electronics and Telecommunications March 15 th 2004 22 3. Numerical Results Geometrical Batch message arrival:

23. Department of Electronics and Telecommunications March 15 th 2004 23 3. Numerical Results Pareto Batch message arrival (3GPP):

24. Department of Electronics and Telecommunications March 15 th 2004 24 3. Numerical Results Increasing HSDPA Gain along with traffic burstiness Traffic models comparison:

25. Department of Electronics and Telecommunications March 15 th 2004 25 3. Numerical Results Traffic models comparison: N and a k are statically similar: few queued messages (protocol efficiency)

26. Department of Electronics and Telecommunications March 15 th 2004 26 ARQ protocols less affect HSDPA performance 3. Numerical Results Poisson packet arrival:

27. Department of Electronics and Telecommunications March 15 th 2004 27 Conclusion High QoS applications (high bit rate, time sensitiveness) feasibility within 3G networks has been investigated Following 3GPP recommendations, as to novel HSDPA scheme, a new protocol has been proposed Based on physical channel state observation, a dynamic bandwidth is allocated to users Protocol efficiency has been tested under several traffic models, including Web services models (LRD) A remarkable gain has been highlighted, if compared with M/D/1 systems 4. Conclusion & developments

28. Department of Electronics and Telecommunications March 15 th 2004 28 More accurate channel monitoring (3 MCS allocation) Further Developments 4. Conclusion & developments State 0: 4-QAM, R c =1/2 State 1: 16-QAM, R c =1/2 State 2: 64-QAM, R c =1/2

29. Department of Electronics and Telecommunications March 15 th 2004 29 Enhanced Link Adaptation Algorithm Steady State Equations (3 states) 4. Conclusion & developments

30. Department of Electronics and Telecommunications March 15 th 2004 30 Publications [1] F. Chiti, L. Caponi, R. Fantacci: “Dynamic Bandwidth Allocation in Wireless Communications Systems”, in Proc. of AIRO 2002. [2] F. Chiti, L. Caponi, R. Fantacci: “An Efficient Rate Allocation Technique based on Channel Status Observation for Wireless Communication Systems”, in Proc. of IEEE WCNC 2004. [3] F. Chiti, L. Caponi, R. Fantacci: “A Dynamic Rate Allocation Technique for Wireless Communication Systems ”, in Proc. of IEEE ICC 2004. [4] F. Chiti, L. Caponi, R. Fantacci: “A Dynamic Radio Resources Allocation Technique for Wireless Communication Systems ”, submitted to Trans. on Vehic. Tech. Founded Research Projects ETSI STF 179 on TETRA Release 2 TEDS Adaptive Link Control 4. Conclusion & developments