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Load Distribution and Channel

Assignment in IEEE 802.11Wireless Local Area Networks

Ph.D. Dissertation DefensePresented by Mohamad Haidar

Department of Applied Science

George W. Donaghey College of Engineering and

Information Technology,University of Arkansas at Little Rock

November 9, 2007


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11/09/2007 Ph.D. Defense 2

Presentation Outline

Introduction Wireless Local Area Networks (WLANs)

Access Points (APs) Congestion

Channel Assignment

Related Work Contributions

Problems Statements1. Congestion Problem

Proposed Solution

Problem Formulation

Algorithm

Numerical Analysis and Results

Simulations (OPNET)


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11/09/2007 Ph.D. Defense 3

Presentation Outline (Contd)2. Channel Assignment Problem

Proposed Solution

Problem Formulation

Algorithm


Simulations (OPNET)

Dynamic Model

Scenario 1 (variable data rate)

Scenario 2 (dynamic user distribution)

Conclusion

Future Work


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11/09/2007 Ph.D. Defense 4

Introduction

Wireless Local AreaNetworks (WLANs) Airports

Hotels Campuses

WLANs are divided into 3categories: IEEE 802.11a in the 5 GHz

band (54 Mbps) IEEE 802.11b in the 2 GHz

band (11 Mbps) IEEE 802.11g in the 2 GHz

band (54 Mbps)

Example of WLAN


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11/09/2007 Ph.D. Defense 5

Introduction (Contd) What is Access Point (AP)

congestion? Some times referred to as Hot

Spot

CAP= (R1+ R2+..+ RN)/BW

CAP: Congestion at APR : Data rate of a user connected to the APBW: Bandwidth (11 Mbps for IEEE

802.11b)

Channel Assignment Minimize interference

To improve QoS (less delay andhigher throughput)

3 non-overlapping channels in IEEE802.11b/g (1, 6, and 11) Frequency Spectrum for IEEE 802.11b/g


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11/09/2007 Ph.D. Defense 6

Limitation of Previous Research AP Placement

The main objective was to use a minimum number of APs foradequate coverage of the desired area. Did not account for channel assignment and/or load distribution.

Channel Assignment Based on minimizing co-channel interference.

Limited to either minimizing total interference between APs ormaximizing the sum of interference at a given AP.

When integrated and applied simultaneously with AP placement,

better results were achieved than dealing with them sequentially. User distribution was not accounted for in the channel assignment.


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11/09/2007 Ph.D. Defense 7

(Contd) Load Balancing/Distribution

Balancing the load based on the number of active users performs poorly because the data rate of users was not

taken into consideration.

Minimizing the congestion at the most congested AP byredistributing users. Improves the load ONLY at the MCAP.

Load balanced agents installed at the APs that broadcastperiodically their load. APs are either under-loaded,balanced, or overloaded. Static user distribution and no power management. All APs involved should be equipped with the LBA software.

Cell breathing technique used to reduce the cell size to

achieve a better load distribution. Connects to the next higher RSSI: is not always the best

choice. Static user distribution. No channel assignment was considered. Interference was

not accounted for.


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Contributions of the Current

Research A new Load Balancing scheme based on Power

Management.

As long as the received power exceeds a certain

threshold, that AP is a potential for association.

Channel Assignment based on Maximizing theSIR at the users.

Users involved in the assignment of channels. Different user distributions will lead to different

channel assignment.


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11/09/2007 Ph.D. defense 9

(Contd)

Combining both load balancing based on powermanagement and the channel assignment basedon SIR: A Novel Scheme.

Verified the performance predicted fromoptimization versus realistic OPNET-basednetwork simulations: New contribution

Developed a realistic dynamic model approachthat accounts for variable users data rates andusers behavior: New contribution


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A New Heuristic AlgorithmInitial Channel Assignment

Users enter to network

Load Balancing based on PM

Re-Assign channels based on SIR

Sort arriving users and departing usersin ascending order in a list

Check list

Arrive Depart

Add user to list Remove user from listResults

End of list


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11/09/2007 Ph.D. Defense 11

1st Problem

AP Congestion Problem

Degrades network throughput

Slowest station will make other stations wait longer. Unfair load distribution over the network

causes bottlenecks at hot spots.

Inefficient bandwidth utilization of the network.


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Proposed Solution

Reduce congestion at the hot spots by decrementing thepower transmitted by the Most Congested AP (MCAP) indiscrete steps until one or more users can no longerassociate with any AP or their data rate can no longer beaccommodated.

The final transmitted power of each AP is set to the bestbalance index, , achieved.

Advantages: Load is fairly distributed. Increase in data rate throughput per user. Less adjacent and co-channel interference.

2

2

( )

( * )

j

j

T

n T


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11/09/2007 Ph.D. Defense 13

Problem Formulation

MCAP NLIP formulation

minijx

1 2max{ , ,..., }MC C C1 i M 1 j N

1

1N

ij

i

x

1

M

i ij

j

j

U x

Cj

BW

forj= 1,, M

fori= 1,,N


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11/09/2007 Ph.D. Defense 14

Algorithm Compute Received Signal Strength Indicator (RSSI)

at each user. Generate a binary matrix that assigns 1 if a users

RSSI exceeds the threshold value or 0 otherwise.

Invoke LINGO to solve the NLIP. Identify the MCAP and compute . Decrement its transmitted power by 1 dBm. Repeat previous steps until one or more user can no

longer associate with an AP or their data rate can nolonger be accommodated. Observe the power levels at each AP and the best

users association at the best .


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11/09/2007 Ph.D. Defense 15


User Number AP1 AP2 AP3 AP4

1 1 1 1 0

2 0 0 1 0

3 0 0 0 1

4 0 0 0 1

5 1 1 1 1

6 1 1 0 0

7 0 1 0 0

8 0 0 1 1

9 0 0 1 0

10 0 1 0 1

Receiver Sensitivity at the user is-90 dBm

Transmitted Power at each AP is

20 dbm4

1

2

User-AP candidate association


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11/09/2007 Ph.D. Defense 16

Numerical Analysis and Results(Contd)

Service Area Map

Traffic is randomly generated between 1 Mbpsand 6 Mbps for each userUser Number Traffic (Kbps)

1 1752

2 5698

3 4265

4 1994

5 3558

6 3176

7 5319

8 1559

9 2982

10 2263

Data rate of users


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11/09/2007 Ph.D. Defense 17


Each user is associated toone and ONLYone AP.

User Number AP1 AP2 AP3 AP4

1 0 1 0 0

2 0 0 1 0

3 0 0 0 1

4 0 0 0 1

5 0 1 0 0

6 1 0 0 0

7 0 1 0 0

8 0 0 0 1

9 0 0 1 0

10 0 1 0 0

1

1

1

Optimal user-AP association


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11/09/2007 Ph.D. Defense 18


(Contd)Initial Congestion factor:

(No Power Mgmt)

Congestion factor solution

according to [2]

Congestion factor with

Power Mgmt

AP1 0.6319 0.5234 0.3793

AP20.4100 0.4100 0.3617

AP3 0.2117 0.2117 0.3167

AP4 0.2026 0.3110 0.3985

81.15% 90.84% 99.31%

Congestion Factor comparison

Load is distributed fairly among APs. Final transmitted power levels at each AP is: 12 dBm, 18

dBm, 20 dBm and 17 dBm, respectively.


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11/09/2007 Ph.D. Defense 19


(Contd) Different radii sizes

after poweradjustment

Users do NOT alwaysassociate to the closestAP.

Service area map after Power Mgmt

N i l A l i d R l


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11/09/2007 *published at IEEE Sarnoff ConferenceMay'07 20

Numerical Analysis and Results(Contd)4 APs 9 APs

16 APs


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11/09/2007 *Not published yet 21

Simulation Scenarios (OPNET)

Unbalanced Load v.s.Balanced Load

20 dBm Transmitted power

-90 dBm Receiver threshold

FTP clients and APs

are stationary

File of 50 Kbytes uploaded

continuously. Simulation time is 40 mins

Steady state after 15 minsWLAN scenario in OPNET, 4 APs and 20 Users


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11/09/2007 Ph.D. Defense 22

Simulation Results (OPNET)

Overall load on the networkwas reduced by loadbalancing Reduced overallcongestion

After applying load balancing,client 9 associated with BSS2,

and improved its throughput.

Overall load at the network

Throughput of FTP client 9


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11/09/2007 Ph.D. Defense 23

2nd Problem

Channel Assignment

Careful consideration must be given to

assigning channels to APs. Otherwise thefollowings may result:

High interference between APs overlapping zones.

Users in the overlapping region of two or more

interfering APs will suffer: Delay

Low data ratesThis is due to the huge increased requests by the userin retransmitting damaged/unsuccessful packets.


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Proposed Solution

Two folds:

Assign channels at the design stage (no

users) with the objective to minimize the totalsumof interference between neighboring APs.

Re-Assign channels when users exist on thenetwork.


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11/09/2007 *Formulation not yet published 25

Problem Formulation (initial stage)

Objective

Subject to

1

,

1

max for eachmin { }MAX iji

M M

SUM ij

i j

jW I iW I j

( )

ij jij

ij

w PI

PL d

1 |Ch Ch | 0.2, for 0where =

0 otherwise

i j ij

ij

ww

i =1, , Mj =1,, Mi j

, {1,.., }

{1,..,11}

j kCh Ch K

K


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11/09/2007 Ph.D. Defense 26

Problem Formulation (with users)

Objective

Subject to

1 1

( )N M

ij

i j

Max SIR k

1

( ),M

ij ij jk

j

I P w j k

1 |Ch Ch | 0.2, for 0where =

0 otherwise

i j ij

ij

ww

( ) ,ikijij

PSIR k i jI

, {1, .., }j k M

{1,.. }i N

, {1,.., }

{1,..,11}

j kCh Ch K

K


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11/09/2007 Ph.D. Defense 27

Heuristic Algorithm

Apply initial channel assignment

Users enter the networkApply load balancing algorithm based on

power management.

Save final transmitted powers at APs.

Re-compute received signal at users.

Compute SIR.Apply Channel Assignment algorithm based on

SIR.


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Numerical Analysis and Results Initial Approach (based

on min AP interference)

AP Number FCA: Equal PowerFCA: Power

Management

AP1 1 7

AP2 8 1

AP3 3 11

AP4 11 3

Interference (dB) -21.17 -22.02

Scenario 1: 4 APs (12, 18, 20, 17 (dBm))


Management

AP1 11 11

AP2 1 1

AP3 8 7

AP4 4 5

AP5 11 2

AP6 1 10

Interference (dB) -19.15 -25.49

Scenario2: 6 APS (16, 16, 11, 6, 6, 1 (dBm))

AP3AP2

AP1 AP4

4 APs

AP1 AP4 AP5

AP2 AP3 AP6

6 APs

4%

33%


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11/09/2007

* Published at IEEE PIMRC conference

Jun'07 29


Initial Approach (Contd)

Scenario 3: 9 APs (4, 12, 20, 16, 20, 16, 17, 8, 19 (dBm))


Management

AP1 11 11

AP2 4 1

AP3 8 6

AP4 1 1

AP5 11 10

AP6 4 1

AP7 11 11

AP8 1 1

AP9 11 11

Interference (dB) -17 -19.86

9 APs

AP7 AP8 AP9

AP6AP3AP2

AP1 AP4 AP5

* Published at IEEE ICSPC conference Nov07

17%


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Second Approach (based on max SIRat users)

Two special cases:

Many users in the overlapping zone

Users are not in the overlapping zone


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11/09/2007

*Submitted to IEEE WCNC conference

Apr'08 31


AP NumberFCA: No Users

(minimize interference

between APs)

FCA: With Users(Maximize SIR at the

Users)

AP1 1 6

AP2 8 11

AP3 3 2

AP4 11 1

Avg. SIR (dB) 6.51 7.66

AP Number FCA: No users FCA: with users

AP1 11 2

AP2 1 11

AP3 8 6

AP4 4 6

AP5 11 8

AP6 1 1

Avg. SIR (dB) 4.22 4.47AP Number FCA: No users FCA: With Users

AP1 11 6

AP2 4 1

AP3 8 11

AP4 1 8

AP5 11 11

AP6 4 4

AP7 11 6

AP8 1 8

AP9 11 11

Avg. SIR (dB) 0.44 2.86

Scenario 1: 4 APs (12, 18, 20, 17 (dBm))

Scenario2: 6 APS (16, 16, 11, 6, 6, 1 (dBm))

Scenario 3: 9 APs (4, 12, 20, 16, 20, 16, 17, 8, 19 (dBm))

17%

6%

540%


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Simulation Scenarios (OPNET)

4-AP WLAN

4-AP WLAN

Scenario1 Scenario2 Scenario3 Scenario4

AP1 1 1 1 6

AP2 2 6 8 11

AP3 3 1 3 2

AP4 4 11 11 1

Summary of the 4 Scenarios


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11/09/2007 *Results not yet published 33

Simulation Results (OPNET)

Same assumptions from the load balancing scenariosapply EXCEPT for the channel assignment.

Zoomed in ViewOverall Upload Response TimeOverall Throughput


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Dynamic Model

Background

No such application of a dynamic user behavior modelon a full scale dynamic network.

Published work related to user behavior reported theuser behavior through monitoring network traffic andbehavior for long periods of time (10 months ormore).

Such a model is significant for future researchers inthe WLAN field or industry where load distributionand channel assignment algorithms can beimplemented and tested on a dynamic scale .


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Dynamic Scenario 1

Scenario 1: Varying data rate with time

4 APs and 20 users.

Data rate of users vary with time according to a normal

distribution (= 4 Mbps, = 2 Mbps). Data rate is captured every 5 minutes.

All users are continuously active.

All APs and users are stationary.

Default AP transmitted power is 20 dBm.

Receivers threshold is -90 dBm.

Simulation period is 2 hours.



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Initial user-AP association

Initial CF Final CF

Final

transmitted

power

(dBm)

Final FCA

AP1 0.2563 0.2464 16 1

AP2 0.0669 0.2721 20 6

AP3 0.3752 0.2502 12 11

AP4 0.3445 0.2741 11 11

82.49% 99.77%

Iteration 1

Initial CF Final CF

Final

transmitted

power

(dBm)

Final FCA

AP1 0.2454 0.3023 20 1

AP2 0.1275 0.3979 16 6

AP3 0.7240 0.3968 5 6

AP4 0.3703 0.3703 18 11

72.94% 98.89%

Last iteration

Final user-AP association


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Dynamic Scenario 2

Scenario 2: Dynamic User Behavior Same assumptions as before apply EXCEPT that the

data rate now is fixed over simulation time.

Users arrive to the WLAN according to a Poissondistribution with an arrival rate of.

varies with time. However, in this scenario has aconstant value over the simulation period (2 hours).

Pr( )!

nen

n


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Dynamic Scenario 2 (Contd)

Session lengths of each user ischaracterized by a Bi-Pareto distribution.

When a users session is over, the user isassumed as either no longer active or leftthe network.

i.e. the user no longer has a data rate it does not

constitute any load at its AP.( 1) 1

( ) (1 ) ( ) ( ),P x k c x x kc x kc x k



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11/09/2007 Ph.D. Defense 39


= 4User Number Arrival times(hrs)

Departure

Time(hrs)

21 0.10

22 0.15

23 0.70

24 0.76

25 1.13

26 1.42

10 1.62

27 1.66

3 1.93

28 1.87

29 2.00

Arrival and Departure time Table

4 APs, 20 Users


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FCA:

Arrive 4

FCA:

Arrive 5

FCA:

Arrive 6

FCA:

Leave 1

Final Tx

Power

(dBm):

Arrive 4

Final Tx

Power

(dBm:

Arrive 5

Final Tx

Power

(dBm):

Arrive 6

Final Tx

Power

(dBm):

Leave 1

AP1 1 1 1 1 17 20 15 18

AP2 6 6 6 6 11 14 19 18

AP3 11 11 11 11 12 5 19 12

AP4 6 6 1 1 15 13 13 13

98.75% 99.14% 96.89% 99.62%Avg. SIR

(dB)6.46 6.27 6.08 6.05

FCA and Load Balancing results


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FCA:

Arrive 7

FCA:

Leave 2

FCA:

Arrive 8

FCA:

Arrive 9

Final Tx

Power

(dBm):

Arrive 7

Final Tx

Power

(dBm):

Leave 2

Final Tx

Power

(dBm):

Arrive 8

Final Tx

Power

(dBm):

Arrive 9

AP1 1 1 1 1 20 19 20 18

AP2 6 6 6 6 18 17 15 18

AP3 11 11 11 11 8 15 16 15

AP4 6 6 1 1 10 18 11 9

99.01% 97.69% 98.92% 99.42%

Total SIR

(dB)5.92 5.94 5.77 5.71


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-- Added users

--Removed users

-- Existing users


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Conclusion

A new load balancing algorithm based on powermanagement was developed.

A new channel assignment algorithm based on

maximizing SIR was developed. Results were validated using OPNET simulation

to show the effectiveness of the developedalgorithms.

Dynamic data rate and user behavior wereintroduced to verify the ability of the developedmodels to adapt to these dynamic behaviors.


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Future Work

Extension of the dynamic model tocombine both variable data rate and users

behavior.Application of this work to WiMAX (IEEE

802.16).

Integration of smart antenna technologyat the AP.

Expand developed work to larger WLANs.


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Special Thanks Ph.D. Advising Committee:

Dr.. Hussain Al-Rizzo(Advisor)

Dr. Robert Akl

Dr. Yupo Chan

Dr. Hassan El-Salloukh

Dr. Seshadri Mohan

Dr. Haydar Alshukri

Ph.D. Candidates

Rami Adada Rabindra Ghimire

Graduate Student TJ Calvin

Network Administrator Greg Browning

OPNET Technical Support

LINGO Technical Support

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