Challenges on Customer Role on Distributed Agile

Dynamic Bandwidth Allocation of OFDMA LTE System with Game TheoryDPS 861A

Josua Purba Jill O'SullivanRaul ZevallosSergio BonicheChina Pankey

1OutlineWhat is Resource Management on Cellular System ? Current Research on LTE Resource ManagementResearch QuestionsSo What?LTE Technology OverviewWhy use Game Theory?Research MethodologyFuture ResearchConclusion2 What is Resource Management on Cellular System ?What are the resources?Bandwidth (Spectrum Frequency)The RF Spectrum frequency where the signal information are sent.Limited in size.Could be 5 MHz (WCDMA), 1.4, ,5,10,20 MHz (LTE)Affect the rate and application run on the systemControl the capacity of the system to handle the users

PowerTransmit Power of Radio signalCan cause interference to other user/sector/cell if to bigDifferent system different requirements3 What is Resource Management on Cellular System ?CodeOn Code Division Multiplex technique (CDMA family, WCDMA, HSPA)Limited number of codeCould not use too many code would cause interference, thus reduce performance. This could make receiver more complex. 4 What is Resource Management on LTE System ?Resource Management on LTE System [17]The role of RRM is essentially to :Ensure that radio resources are efficiently utilizedTaking advantage of the available adaptation techniquesServe users according to their quality of service (QoS) attributes.Usually RRM handles Mobility Management (Handover) from 1 BS to another.5 What is Resource Management on Cellular System ?The mechanisms include [17]Bearer admission controlmulti-user time and frequency domain packet schedulingQoS-awareHybrid automatic repeat request (ARQ) managementlink adaptation with dynamic switching between different transmission modes. The available transmission modes include single- and dual-codeword transmissions for multi-antenna configurationsLocalized and distributed subcarrier transmission.bearer = carrier = owner6 What is Resource Management on LTE System ?BS User Plane and Control Plane Architecture [17]

7 Current Research on Resource ManagementSpectrum pooling [10],[11]Licensed Users (LU) share spectrum with Rental Users (RU)RU get the same Bandwidth size like LURU needs to detect LU before use the spectrumInterference issue from RU to LU and vice versaWorks on FDMA/TDMA and OFDM systemStudy the packet delay, throughput and the blocking probability for a spectrum pooling system by using Markov chain. [11]

Problem with spectrum pooling:Fix size for the BW, some users do not need a lot if they just use for phone callPooling all the channel and check whether it is available.Lease the BW to Rental user, not cellular8 Current Research on Resource Management?Spectrum pooling [10]

9 Current Research on LTE Resource Management?Spectrum Pooling + Random Access [13]Spectrum Pooling use Round Robin not efficientCombine it with Random Access to improve utilization radio resources and improve throughputUse Wifi for the experiment

Heterogeneous system (TV and Wireless) [14]Share (Sell) TV spectrum to service providersUse double auction game theoryOne between TV station and service providersOne between service providers and users

Problem with Spectrum pooling + Random accessIt works by modifying wifi MAC scheduler with random AccessRandom access is not organized more for ad-hoc mode. This is for wifi

For Heterogeneous system, TV broadcasters and 802.22 WRAN service providers share the spectrum:Not Cellular network but like the ideas of double auction.

10 Current Research on LTE Resource Management?Scheduling [21] Classical scheduling goals in a communication system are to maximize utilization (throughput) and to allow communication for all users (fairness).Study the fairness vs. efficiency on OFDMA scheduling. Compare various kind of game theory criteria for cooperative bargaining. Found Kalai-Smorodinsky solutions as alternative to proportional fairness (Nash solution), both offer compromise between efficiency and fairness.The problem of this research:Focus only on schedulingCan apply this to auction theory11 Current Research on LTE Resource Management?Adaptive [15]Exploits the time diversity, frequency diversity as well as multiuser diversity in the time, frequency and user domain, respectively.Adopt a two-step allocation method to reduce the scheduling complexity and meanwhile improve the scheduling performance.Allocate users into 2 dimension frequency and time domain like grids.

The key is scheduling on time, frequency and user domain.The problem with this research:Complexity is high since it involves a lot of mathMore static, since the derivation based on the certain assumption. Different condition, different assumption might give different derivation and could give different results.

12 Current Research on LTE Resource Management?Adaptive [15]

The key is scheduling on time, frequency and user domain.13 Current Research on LTE Resource Management?Optimal Solution [9] Investigate the issue of power control and subcarrier assignment in a sectorized two-cell downlink OFDMA (WIMAX) system impaired by multicell interference.Usually with practical problem, this would not have simple closed form solution.Some of available bandwidth would be reused by different base station, subject to multi cell interference.The rest of the available bandwidth would be shared in an orthogonal way between the different base stations, no multi cell interferenceThe paper provide simpler form of general solution.The key is scheduling on time, frequency and user domain.The problem with this research:Use WIMAX not LTE. They are similar but not exactly the same.More static, since the derivation based on the certain assumption. Different condition, different assumption might give different derivation and could give different results.

14 Current Research on LTE Resource Management?Cognitive Radio [8] Propose and validate a Cognitive RRM scheme in the context of LTE network segments. Use cognitive features that provide the system with knowledge which observed from past interactions with the environment. The system will be able to apply already known solutions in timely manner when identifying a problem that has been already addressed in the past. Assume: all sub carrier use the same modulation type and power level (comment: not practical) Proposed scheme can result in significant efficiency improvement in terms of performance and network adaptation.RRM: Radio Resource ManagementThe problem with this research:Use cognitive radio only, does not use game theoryDoes not involve user decision, not distributed. More centralized.15 Current Research on LTE Resource Management?Game Theory Auction Theory [20] Develop theory on allocate wireless channel with auction theorem.Consider fair competition over independent wireless fading channel.each user submits a bid according to the channel condition (assume known in the beginning time slot)Use centralized scheduler that assign time slots according to the Nash equilibrium strategy based on users average money amount.The transmitter chooses the one with the highest bid to transmit;The problem with this research:Use wireless network, not cellular networkThis is more on mathematical theory development. We can use the technique for the auction theory part. But it does not have any cognitive and scheduling aspect. 16 Research questionsWhat is the optimum way to allocate bandwidth dynamically on OFDMA LTE system with auction theory, scheduling and cognitive radio? Is it possible to find general optimum solution?What is the complexity of the dynamic bandwidth allocation with auction theorem compare to results without game theory?How to apply time notion as multiple step decision of auction theory on allocation the bandwidth dynamically?17So What ?RIM CEO mention the need to conserve bandwidth(http://www.mobilecrunch.com/2010/02/16/rim-ceo-pulls-an-att-we-need-to-conserve-bandwidth/)At the end 2009, AT&T ask its customer to reduce to use their smart phone by giving incentive.http://news.cnet.com/8301-30686_3-10412804-266.htmlOperator can increase the capacity and efficiency of the network. Thus increase the revenue bottom line make money and customer satisfactionWhy LTE ?People/customer use the technology not only research but also commercial (real implementation)Majority market use LTE compare to Wimax and Ultra Mobile Broadband (UMB)18 Lte Overview key featuresSupport for, and mobility between, Multiple heterogeneous systems: legacy system (GSM, GPRS, EDGE, WCDMA, HSPA)Non-3GPP system (Wifi, Wimax, EV-DO, satellite)All IP Network Enhanced Air Interface allow increased data rate With Mobility: 100 MBps (DL) and 50 MBps(UL)Stationary: 1GBps (DL) and 500 MBps (UL)19 Lte Overview key featuresSupport for higher throughput and lower latencyUser Plane Latency: < 5msControl Plane Latency (Transition Time to Active State): < 100ms (from idle to active)Increase Control Plane Capacity: > 200 users per cell (for 5MHz Spectrum)Mobility Support:Up to 500 Kmph Optimized for low speed from 0 to 15 Kmph

20 Lte Overview key featuresSpectrum Flexibility to achieve higher spectrum efficiency [18]: where RB: Resource Block

21 Lte Overview key featuresChannel Bandwidth Definition [18]:

22 LTE Technology OverviewHigh Level Overview BS Architecture [19]

23 LTE Technology OverviewLTE scheduler on protocol stack [16]

24 LTE Technology OverviewChannel quality variations in time and freq [16]

25LTE Technology OverviewDown Link (DL) OFDM (Orthogonal Frequency Division Multiplexing) use a large number of narrowband sub-carrier for multi carrier transmission. OFDM avoids the problem with multipath reflections by sending message bits slow enough so it has high tolerance for multipath delay spread.OFDMA: assigning different sub channel to different user.Use the same principle as HSPA for scheduling of share channel data and fast link adaptation.

26 LTE Technology OverviewDown Link (DL) OFDM symbols are grouped into resource block which has 180KHz in frequency domain and 0.5 ms in time domain. Each user is allocated a number of resource block in time-frequency grid.The more resource block the higher the rate.The scheduling mechanism control the number of resource block at any given time.

27 LTE Technology Overview

28 LTE Technology OverviewUp Link (UL) Use SC-FDMA(Single Carrier Frequency Division Multiple Access). It adds DFT/IDFT to OFDMA architecture.It groups the resource block in away reduce PAPR (Peak Average Power Ratio).

29 LTE Technology OverviewMultiple Antenna [16]Use Multiple Input Multiple Output (MIMO) to increase data rate, diversity, increase capacity and beam forming.It use 2x2 or 4x4 MIMO system.

30 LTE Technology OverviewThe DL PHY resource space for one TTI. Pilot symbols for channel estimation purposes are not illustrated [17].

31 LTE Technology Overview [23]

32 LTE Technology Overview [23]

33 Why use game theory?What is Game theory? [7,12]Mathematical models of interaction between two or more rational decision makersStudy and analysis of situations where conflict of interests are present.Game theory concepts apply whenever the actions of several agents are interdependent. These agents may be individuals, groups, firms, or any combination of these. The concepts of game theory provide a model to formulate, structure, analyze, and understand strategic scenarios.34 Why use game theory?Advantages of Game theorySimplicityCompare to typical math derivationDynamicDecision made based on its condition at the timeDifferent decision for different conditionDistributedUsers involved in making decision

35 Why use game theory?Limitations of Game theoryReal world conflicts are complexModel at best can capture important aspectNo unified solution to general conflict resolutionPlayers are (usually) considered rationaldetermine what is best for them given that others are doing the same (not cooperative)But it can provide intuitions, suggestions and partial prescriptions

36 Research MethodologyMathematical derivation and optimizationStart from system model (still evolve)Assumption and important parameterApply Game theory to systemFind optimizationUse software to help optimizationFormulize the algorithmIf time permit, simulate with software package

37 Research MethodologySystem Model: combination cognitive radio and game theory.

INPUT(Context, Profiles, Policies)Optimization & Decision (Game Theory)LTE Network Element(eNB, segment, cell)Management InfrastructureLearningInfrastructure AbstractionEnvironment SensingConfiguration capabilities Decision efficiency User preferences38 Research MethodologyAssumption:One Sector, One Cell, One BSMultiple Users (N)With Interference and Power ControlMultiple or repeated step Auction Theory that include notion of timeParameter or Variable:Bandwidth size and frequencyTimeNumber of UserType of ServiceNumber of Resource BlockBidding strategyInterference (SINR)Slot numberRate or throughputNumber of sub-carriers39 Research MethodologyApply Game theory to system Auction TheoremPart of Game TheoryDefinition: A public sale of property or merchandise to the highest bidder. Auctions have rules and bidders.Auctioneer decides what rules to use but takes bidders as given.Auction mechanism tries to maximize the sellers revenue through the bidding of each player.Show the supply (limited) and demand (a lot).BS has limited resources and many users wants them.

40 Research MethodologyConsider the following scenarios:Non-Cooperative (Competitive) Games: RealisticCooperative Games: User willing to compromiseRepeated and Evolutionary Games: dynamic scenarioAuction model:N: number of users (i=1..N)B: Bidding strategy (Bi= bidding strategy of user i)P: Pay off function (Pi = Pay off function of user i)R: Rate or throughput (Ri = Rate of user i)

41 Research MethodologyAuction model (continued):K: number of sub-carrier (Ki= sub-carrier of user i)SIR: Signal-to-Interference Ratio (SIRi of user i) Bidding function model :The goal is to maximize the revenue by extracting each users willingness to pay about an objectI plan to use Sealed bid: bidders tell auctioneer their bids without interacting with each other. Sealed bid has the following rules: First-price. Winner pays its own bid. Losers pay nothing. 42 Research MethodologySealed bid has the following rules (continued): Second-price. Winner pays highest losing bid. Losers pay nothing. All-pay. Each bidder (including losers) pays its own bid. Have not decided what strategy to use, but my candidate might be Second-price.

43 Research MethodologyCurrent auction model for throughput and fairness analysis [22]:Sum rate maximization Does not consider fairness.Assign sub carrier to user that has best channel condition.Max-Min fairnessMost strict fairness criterion since every users data rate are equal.Maximize user who has lowest data rate.Proportional fairnessTrade off between Sum rate maximization and Max-Min fairness.Maximize sum of logarithmic utility function.

44 Research MethodologyProposed the new method and utility function:Find utility functionF = [N, K, {Bi}, Pi{.}, SIRi]Include scheduling to equation:Proportional fairness: Nash SolutionS = argmax Ri = argmax RiKalai Smorodinsky fairness algorithmS = argmax {min (Ri / Ri max)}Need to work the detail more in LTE context.45 Research MethodologyKey Issues in analysisSteady state characterizationSteady state optimalityConvergenceStabilityScalability46 Research MethodologyOptimization

Find Cost functionCooperative, non-cooperative and repetition.Heuristic: Case by caseCase by case for few cases Find common case or case that is used many timesShorter time frame to develop

General SolutionThe goal : find Global optimum and unique solutionIs it possible to find it on multiple step? General case answer all possibilitiesLonger time frame to develop47 Research MethodologyUse software to help optimizationUse Matlab to plot the functionFind Optimum point

Formulize the algorithm in terms of steps to LTE protocol stack procedures.

If time permit, simulate with software package48 Future ResearchDesign and implement the algorithm using network simulation software such as: OPNET or OMNETAdd the fading and multipath on the analysis.Add power control restriction on the analysisAdd case with 2 sectors, 2 cell, 2 BS and handover as part of the analysisAdd MIMO to BS only.Add MIMO to BS and terminals (users)

If I can find new and break through method, Ill apply for pattent.49 ConclusionDynamic resource allocation research is very important as the demand for bandwidth increase rapidly. Different kind of methodology can be applied to find optimum solution on dynamic bandwidth allocation.Many researchers use game theory for dynamic resource allocation since it has dynamic, less complexity and distributed characteristic. 501. 3GPP Standard and Specification (http://www.3gpp.org/)2. UMTS Forum (http://www.umts-forum.org/) 3. 3GPP Long Term Evolution on Wiki (http://en.wikipedia.org/wiki/3GPP_Long_Term_Evolution)4. LTE Tutorial from Radio Electronics (http://www.radio-electronics.com/info/cellulartelecomms/lte-long-term-evolution/lte-ofdm-ofdma-scfdma.php).5. Ericsson, LTE Overview, 284 23-3124 Uen Rev B, June 2009. 6. The Mobile Broadband Evolution: 3GPP Release 8 and Beyond, 3G Americas, February 2009. 7. Martin Shubik, Game theory, complexity and simplicity part 1: a tutorial, Publisher John Wiley & Sons, Inc. New York, NY, USA, Pages: 39 - 46, Volume 3 , Issue 2 (Nov./Dec. 1997), Pages: 39 - 46, ISSN:1076-2787, 1997.8. Saatsakis, A., Tsagkaris, K., von-Hugo, D., Siebert, M., Rosenberger, M., Demestichas, P,Cognitive Radio Resource Management for Improving the Efficiency of LTE Network Segments in the Wireless B3G World, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008. DySPAN 2008.9. Ksairi, N.; Bianchi, P.; Ciblat, P.; Hachem, W., Resource Allocation for Downlink Cellular OFDMA Systems: Part 1- Optimal Allocation, Signal Processing, IEEE Transactions on : Accepted for future publication Volume PP, Forthcoming, 2009.

references5110. T.A. Weiss and F.K. Jondral,Spectrum Pooling: An Innovative Strategy for the Enhancement of Spectrum Efficiency, IEEE Radio Communication, March 2004. 11. Fatih Capar, Friedrich Jondral , Resource Allocation in a Spectrum Pooling System for Packet Radio Networks Using OFDM/TDMA, IST Mobile & Wireless Telecommunications Summit June 16-19, Thessaloniki, Greece 2002.12. Game Theory on wiki (http://en.wikipedia.org/wiki/Game_theory) 13. Shimizu,Yoshitaka; Nuno, Fusao,Performance Evaluation of Novel DSA Scheme that Combines Polling Method with Random Access Method,The 17th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'06),Helsinki, Finland, 2006.14. Dusit Niyato, Ekram Hossain, Zhu Han, Dynamic Spectrum Access in IEEE 802.22-Based Cognitive Wireless Networks: A Game Theoretic Model for Competitive Spectrum Bidding and Pricing, IEEE Wireless Communications, April 2009. 15. Xing Zhang, En Zhou, Renshui Zhu, Shiming Liu, Wenbo Wang, Adaptive multiuser radio resource allocation for OFDMA systems, IEEE Global Telecommunications Conference, 2005. GLOBECOM '05, St. Louis, MO, 23 January 2006.16. David Astly, Erik Dahlman, Anders Furuskr, Ylva Jading, Magnus Lindstrm, Stefan Parkvall, "LTE: The Evolution of Mobile Broadband", IEEE Communications Magazine, Vol. 47, no. 4, April 2009

References - Continued5217. Klaus I. Pedersen, Troels E. Kolding, Frank Frederiksen, Istvn Z. Kovcs, Daniela Laselva, and Preben E. Mogensen, " An Overview of Downlink Radio Resource Management for UTRAN Long-Term Evolution ", IEEE Communications Magazine, Vol. 47, no. 7, July 2009 18. 3GPP TS 36.101: "Evolved Universal Terrestrial Radio Access (E-UTRA); User Equipment (UE) radio transmission and reception, V9.2.0 (2009-12).19. 3GPP TS 36.300: "Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; , V9.2.0 (2009-12).20. Jun Sun, Eytan Modiano, Lizhong Zheng, Wireless Channel Allocation Using an Auction Algorithm, IEEE Journal on Selected Areas in Communications, Vol. 24, No. 5, May 2006. 21. Ibing, A.; Boche, H., Fairness vs. Efficiency: Comparison of Game Theoretic Criteria for OFDMA Scheduling, Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers (ACSSC), 4-7 Nov. 2007, Pages:275 279, Pacific Grove, CA.22. Sang-Wook Han, Youngnam Han, A Competitive Fair Subchannel Allocation for OFDMA System Using an Auction Algorithm, IEEE 66th Vehicular Technology Conference (VTC), pp. 1787-1791, Sept. 30 2007-Oct. 3 2007 Baltimore, MD.

References - Continued5323. Reshef, Ehud, LTE & WIMAX Evolution to 4G, Comsys, 29 October 2008.

References - Continued54