DYNAMIC BANDWIDTH ALLOCATION OF OFDMA LTE

SYSTEM WITH GAME THEORY

DPS 861A

Josua Purba Jill O'SullivanRaul Zevallos

Sergio BonicheChina Pankey

OUTLINE What is Resource Management on Cellular

System ? Current Research on LTE Resource Management Research Questions So What? LTE Technology Overview Why use Game Theory? Research Methodology Future Research Conclusion

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 system• Control the capacity of the system to handle the users

Power• Transmit Power of Radio signal• Can cause interference to other user/sector/cell if to big• Different system different requirements

WHAT IS RESOURCE MANAGEMENT ON CELLULAR SYSTEM ?

Code• On Code Division Multiplex technique (CDMA

family, WCDMA, HSPA)• Limited number of code• Could not use too many code – would cause

interference, thus reduce performance. This could make receiver more complex.

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 utilized• Taking advantage of the available adaptation

techniques• Serve users according to their quality of service

(QoS) attributes.• Usually RRM handles Mobility Management

(Handover) from 1 BS to another.

WHAT IS RESOURCE MANAGEMENT ON CELLULAR SYSTEM ?

The mechanisms include [17] Bearer admission control multi-user time and frequency domain packet scheduling QoS-aware Hybrid automatic repeat request (ARQ) management link adaptation with dynamic switching between different

transmission modes. The available transmission modes include single- and

dual-codeword transmissions for multi-antenna configurations

Localized and distributed subcarrier transmission.

WHAT IS RESOURCE MANAGEMENT ON LTE SYSTEM ?

BS User Plane and Control Plane Architecture [17]

CURRENT RESEARCH ON RESOURCE MANAGEMENT

Spectrum pooling [10],[11] Licensed Users (LU) share spectrum with Rental Users (RU) RU get the same Bandwidth size like LU RU needs to detect LU before use the spectrum Interference issue from RU to LU and vice versa Works on FDMA/TDMA and OFDM system Study the packet delay, throughput and the blocking

probability for a spectrum pooling system by using Markov chain. [11]

CURRENT RESEARCH ON RESOURCE MANAGEMENT?

Spectrum pooling [10]

CURRENT RESEARCH ON LTE RESOURCE MANAGEMENT?

Spectrum Pooling + Random Access [13] Spectrum Pooling use Round Robin – not efficient Combine it with Random Access to improve utilization

radio resources and improve throughput Use Wifi for the experiment

Heterogeneous system (TV and Wireless) [14] Share (Sell) TV spectrum to service providers Use double auction game theory One between TV station and service providers One between service providers and users

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.

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.

CURRENT RESEARCH ON LTE RESOURCE MANAGEMENT?

Adaptive [15]

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 interference

The paper provide simpler form of general solution.

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.

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.

RESEARCH QUESTIONS

What 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?

SO 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.html

Operator can increase the capacity and efficiency of the network. Thus increase the revenue … bottom line … make money and customer satisfaction

Why 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)

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)

LTE OVERVIEW – KEY FEATURESSupport for higher throughput and lower latency

User Plane Latency: < 5ms Control 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

LTE OVERVIEW – KEY FEATURESSpectrum Flexibility to achieve higher

spectrum efficiency [18]: where RB: Resource Block

LTE OVERVIEW – KEY FEATURESChannel Bandwidth Definition [18]:

LTE TECHNOLOGY OVERVIEWHigh Level Overview BS Architecture [19]

LTE TECHNOLOGY OVERVIEWLTE scheduler on protocol stack [16]

LTE TECHNOLOGY OVERVIEWChannel quality variations in time and freq [16]

LTE TECHNOLOGY OVERVIEW

Down 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.

LTE TECHNOLOGY OVERVIEW

Down 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.

LTE TECHNOLOGY OVERVIEW

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).

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.

LTE TECHNOLOGY OVERVIEW The DL PHY resource space for one TTI. Pilot symbols

for channel estimation purposes are not illustrated [17].

LTE TECHNOLOGY OVERVIEW [23]

LTE TECHNOLOGY OVERVIEW [23]

WHY USE GAME THEORY?

What is Game theory? [7,12] Mathematical models of interaction between two or more

rational decision makers Study 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.

WHY USE GAME THEORY?

Advantages of Game theorySimplicity

Compare to typical math derivation Dynamic

Decision made based on its condition at the time Different decision for different condition

Distributed Users involved in making decision

WHY USE GAME THEORY?

Limitations of Game theoryReal world conflicts are complex

Model at best can capture important aspectNo unified solution to general conflict resolutionPlayers are (usually) considered rational

determine what is best for them given that others are doing the same (not cooperative)

But it can provide intuitions, suggestions and partial prescriptions

RESEARCH METHODOLOGY

Mathematical 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

RESEARCH METHODOLOGY

System Model: combination cognitive radio and game theory.

INPUT(Context, Profiles,

Policies)

Optimization & Decision

(Game Theory)

LTE Network Element(eNB, segment, cell)

Management Infrastructure

“Learning”Infrastructure

Abstraction

Environment Sensing

Configuration capabilities Decision efficiency User preferences

RESEARCH METHODOLOGY

Assumption: One Sector, One Cell, One BS Multiple Users (N) With Interference and Power Control Multiple or repeated step Auction Theory that include notion of time

Parameter or Variable: Bandwidth size and frequency Time Number of User Type of Service Number of Resource Block Bidding strategy Interference (SINR) Slot number Rate or throughput Number of sub-carriers

RESEARCH METHODOLOGYApply Game theory to system Auction Theorem

Part of Game Theory Definition: 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 seller’s

revenue through the bidding of each player. Show the supply (limited) and demand (a lot). BS has limited resources and many users wants them.

RESEARCH METHODOLOGY

Consider the following scenarios: Non-Cooperative (Competitive) Games: Realistic Cooperative Games: User willing to compromise Repeated and Evolutionary Games: dynamic scenario

Auction 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)

RESEARCH METHODOLOGY

Auction 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 user’s

willingness to pay about an object I 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.

RESEARCH METHODOLOGY

Sealed 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.

RESEARCH METHODOLOGY

Current 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 fairness Most strict fairness criterion since every users data rate are equal. Maximize user who has lowest data rate.

Proportional fairness Trade off between Sum rate maximization and Max-Min

fairness. Maximize sum of logarithmic utility function.

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 Σ Ri = argmax Π Ri Kalai – Smorodinsky fairness algorithmS = argmax {min (Ri / Ri max)}

Need to work the detail more in LTE context.

RESEARCH METHODOLOGY

Key Issues in analysis Steady state characterization Steady state optimality Convergence Stability Scalability

RESEARCH METHODOLOGYOptimization

Find Cost function Cooperative, non-cooperative and repetition. Heuristic: Case by case

• Case by case for few cases • Find common case or case that is used many times• Shorter time frame to develop

General Solution• The goal : find Global optimum and unique solution• Is it possible to find it on multiple step? • General case answer all possibilities• Longer time frame to develop

RESEARCH METHODOLOGY

Use software to help optimization Use Matlab to plot the function Find Optimum point

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

If time permit, simulate with software package

FUTURE RESEARCH

Design and implement the algorithm using network simulation software such as: OPNET or OMNET

Add 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)

CONCLUSION

Dynamic 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.

1. 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.

REFERENCES

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