Optimal Network and

Frequency Planning for WLAN

Abhishek Verma Dr.-Ing. Michael Reyer

Lehrstuhl für Theoretische InformationstechnikUniv.-Prof. Dr. rer. nat. Rudolf Mathar

RWTH Aachen University

Master’s Thesis Final Talk 18th Feb, 2016

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Outline

Introduction WLAN planning Objectives Design components ILP model Results Summary and future work

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Introduction Why WLANs are popular?

Easy to deploy Stable future migration Low cost Effective services for indoor/outdoor Easy access to Internet

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Problem Scenario

Works

?• Limited coverage range of each access point.• Limited frequency bandwidth/capacity.• And so many users to satisfy!!

Access point (AP)

Needs some planning

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WLAN Planning

For any given design requirements, planning a wireless network means to determine

1. An optimal number of APs.2. The locations of those APs.3. Frequency channels associated to them.

Inputs• Access points : Candidate locations (j), # available APs (b) capacities (Pj), costs (mj)• Users (i) : data rates (ti), priorities (pi)• Received signal strengths (sij)

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Demand Node Concept Service area is divided into demand point grid. Assumption – data rate demand at each point is constant.

Candidate location for an AP j

Demand point i

Inputs• Signal strength, • Demand rate,• Priority,• AP Cost,Where,

i : demand pointsj : candidate APs

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ObjectivesWe have three competing objectives

Signal Strength

• sij• Maximize the sum

of signal strengths of all demand points ‘i’.

Interference

• Minimize at each demand point from all interfering APs.

• Depends upon channel distance between APs.

Cost

• mj• Minimize the

number of installed APs ‘j’.

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WLAN Design Components

Coverage area (in dBm): receiver sensitivity threshold. (in dBm) : calculated using the log distance path loss.

Where, is the transmit power of AP j

• User traffic• Provide minimum required data rate, .• Varies with the type of user application.

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WLAN Design Components

• Limited number of channels.• Need adequate channel distances between APs.• (in dBm) : detection threshold.

Frequency spectrum

• Different channels --- different overlaps• The effect of interfering signal depends upon the channel distance ‘d’ between the two APs. This attenuation factor is given by:

where, ko is a constant

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Objective function

• Related Constraints

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Integer Linear Program Model

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• Related Constraints

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Signal strength maximization

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Parameters• Number of demand points, N = 196• Number of candidate AP locations, M = 12• Number of available channels, K = 13• Number of available APs, b = 10• Demand rate, ti = 1• Priority, pi = 1• = 6.02 dBm

• = 7.95 dBm• Transmit power, = 20 dBm

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Results

• Random channel selection possible.• Overlapping of frequencies.• Bigger dots represents ‘bad points’ suffering from interference more than the .• Lead to more collisions, increased sensing time and low throughput.

• decreases with increasing distance.• Demand points are assigned to APs closer to them.

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Minimizing Interference • Subtracting interference from the objective

• Related Constraints

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Results

• = 0.9, = 0.1• Number of ‘bad points’ decreases.• Number of APs drops to 6.• Coverage area drops by only 2%.

• But this trade of between coverage area and interference depends upon the values of and .

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Minimizing Cost• Subtracting cost of APs from the objective

• Related Constraints

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Final Optimal Solution

• = 0.6, = 0.1, = 0.3• Number of APs further drops to 4• Area covered = 82 %.• # of ‘Bad points’ = 0.

How to choose values of ??

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The competing objectives are weighted by trade-off parameters . Each triplet of lambdas may produce different optimal solutions of the ILP model while maximizing the total objective sum.

We can compare these solutions with one another in terms of : Area covered (in %) Number of ‘bad nodes’ Number of APs installed

are varied in the steps of 0.1 from 0 to 1 keeping . From the results, we can focus on those triplets which jointly gives

maximum coverage area and minimum number of ‘bad nodes’ and number of APs.

Resulting into the triplet, . But, a designer may choose a different set of lambdas depending the

results and wireless environment.

Final Optimal Solution

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Summary WLAN planning is important due to the huge popularity and large

scale deployment of wireless networks. 3 major problems related to planning are finding the number of APs,

their locations and frequency allocation. The optimization objectives signal strength, interference and cost are

jointly included in our ILP model and are weighted by tunable trade-off parameters.

For the considered planning scenario, the values of the trade-off parameters which jointly produces maximum signal strength, minimum interference and minimum cost is

= 0.6, = 0.1, = 0.3. For a different planning scenario this may be different.

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Future Work The model assumes constant data rate throughout the basic service

area. Because of the IEEE 802.11 fallback protocols, the data rate may change according to the SIR levels.

We have assumed the effective AP capacities. Since, an access to a wireless medium is a random event and depends upon the number of users, we could use capacity analytical method to estimate more practical AP capacity.

The optimal trade-off values could not be found due the computational limitations. Work can be done in developing more efficient algorithms for solving linear optimization problems.

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Thank you!

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Questions?