47

CHAPTER 3

PROPOSED SOLUTIONS FOR VERTICAL HANDOVER

DECISION IN 4G NETWORKS AND VANETS

3.1 INTRODUCTION

The various vertical handover decision solutions proposed by this

thesis are presented in this Chapter. A simple handover management process

based on mobile-terminals and network controlled inputs are described. The

various seamless vertical handover decision techniques such as application-

oriented, QoS-centric and congestion-aware approaches are presented.

Seamless Vertical Handover Decision in multimode mobile

terminal is the critical challenge in the 4G networks. The existing solutions

are based on Signal strength and network resources. Hence disruption of

service to the end user (hard handover) happens during the handover. The

proposed system achieves the seamless soft handover by considering the

complex metrics like momentary cost, QoS, user preferences etc. IEEE 802.21

MIHF based network scanning has great impact on improvised handover

performances. Also the game-theory and constrained Markov Decision Process

(MDP) based decision for soft handovers are presented. The seamless soft

handover is the most expected requirement in 4G heterogeneous networks.

3.2 MOTIVATION FOR SEAMLESS VERTICAL HANDOVER

Fourth Generation Networks (4G) enables the integration and

interworking of current wireless systems. With 4G/NGWNs, the user

48

dem

ands

fo

r se

amle

ss

roam

ing

acro

ss

diff

eren

t w

irele

ss

netw

orks

an

d

diff

eren

t op

erat

ors

to p

rovi

de v

ario

us l

evel

s of

bro

adba

nd s

ervi

ces

such

as

voic

e, d

ata

and

mul

timed

ia a

t ve

hicu

lar

spee

ds.

The

verti

cal

hand

over

deci

sion

bas

ed o

n th

e re

ceiv

ed s

igna

l st

reng

th a

s th

e so

le c

riter

ion

is

inef

ficie

nt a

nd im

prac

tical

in h

eter

ogen

eous

net

wor

ks. M

ore

com

plex

met

rics

like

mom

enta

ry c

ost,

band

wid

th, p

ower

con

sum

ptio

n, n

etw

ork

cond

ition

s an

d

user

pre

fere

nces

are

als

o co

nsid

ered

for

det

erm

inin

g th

e se

amle

ss v

ertic

al

hand

over

de

cisi

on.

The

seam

less

ve

rtica

l ha

ndov

er

deci

sion

fo

r 4G

hete

roge

neou

s ne

twor

ks e

nabl

es u

ser t

o se

lect

the

best

net

wor

k w

hich

off

ers

the

max

imal

qua

lity

of se

rvic

e at

min

imal

cos

t.

The

exis

ting

syst

em’s

mob

ility

mod

el d

oes

not

cons

ider

the

lan

e-

chan

ges,

emer

genc

y br

akin

g, s

peed

lim

its a

nd t

opol

ogic

al m

aps

in b

uild

ing

the

V-2

-V a

nd V

-2-I

com

mun

icat

ions

. Hen

ce t

he p

ropo

sed

syst

em p

rovi

des

seam

less

ve

rtica

l ha

ndov

er

deci

sion

fo

r V

AN

ETs

(Veh

icul

ar

Ad

hoc

Net

wor

ks) b

y co

nsid

erin

g th

e re

al-ti

me

mob

ility

mod

el w

hich

is in

turn

use

ful

in b

uild

ing

inte

llige

nt tr

ansp

orta

tion

syst

ems.

3.3

PRO

POSE

D S

OL

UT

ION

SY

STE

MS

FOR

4G

NE

TW

OR

KS

AN

D V

AN

ET

S

The

follo

win

g sy

stem

s ar

e pr

opos

ed i

n or

der

to a

chie

ve t

he

obje

ctiv

es a

nd so

lutio

ns to

the

prob

lem

s des

crib

ed in

the

sect

ion

2.6.

1.A

pplic

atio

n ba

sed

Seam

less

Ver

tical

Han

dove

r

2.A

dapt

ive

Ban

dwid

th A

lloca

tion

(AB

A)

and

Cal

l A

dmis

sion

Con

trol (

CA

C)

3.C

onge

stio

n-A

war

e V

ertic

al H

ando

ver

4.M

ulti-

Play

er G

ame-

Theo

retic

Nas

h-eq

uilib

rium

Han

dove

r

49

5.EM

DP

base

d M

ulti-

attri

bute

Wei

ghte

d-R

anki

ng H

ando

ver

6.Sp

eed

base

d R

eal-t

ime

mob

ility

sup

porte

d V

ertic

al H

ando

ver

with

Em

erge

ncy

Bra

king

In

Four

th

Gen

erat

ion

(4G

) N

etw

orks

, th

e se

amle

ss

verti

cal

hand

over

de

cisi

on

fram

ewor

k is

pr

opos

ed

usin

g IE

EE

802.

21

Med

ia

Inde

pend

ent

Han

dove

r Fu

nctio

n (M

IHF)

. Th

e ad

aptiv

e ba

ndw

idth

man

agem

ent

and

call

adm

issi

on c

ontro

l m

echa

nism

s ar

e al

so i

ncor

pora

ted

with

th

e ha

ndov

er

man

agem

ent

syst

ems.

The

gam

e-th

eore

tic

verti

cal

hand

over

dec

isio

n m

odel

inc

lude

s lo

ad a

nd c

onge

stio

n fa

ctor

s ba

sed

on

Erla

ng lo

ss fo

rmul

ae.

In V

AN

ETs,

the

gam

e-th

eory

bas

ed s

eam

less

ver

tical

han

dove

r

deci

sion

with

hyb

rid E

mer

genc

y-B

raki

ng s

yste

m i

s pr

opos

ed i

n or

der

to

achi

eve

effe

ctiv

e ve

hicu

lar

com

mun

icat

ions

. The

han

dove

r de

cisi

on m

akin

g

prot

ocol

wor

ks a

long

with

hyb

rid m

obili

ty m

odel

s of

EEB

L (E

mer

genc

y

Elec

troni

c B

raki

ng L

ight

s) a

nd ID

M (I

ntel

ligen

t Driv

er M

odel

). It

has

vario

us

emin

ent f

eatu

res s

uch

as:

Prop

agat

ion

of a

ccid

ent a

nd c

ollis

ion

war

ning

s to

am

bula

nce

or p

olic

e st

atio

ns

Red

uctio

n of

spe

ed o

f th

e ve

hicl

es b

efor

e cr

ashi

ng t

o av

oid

acci

dent

s.

50

3.4

HA

ND

OV

ER

MA

NA

GE

ME

NT

PR

OC

ESS

A

wire

less

ne

twor

k w

hich

co

nnec

ts

usin

g di

ffer

ent

acce

ss

tech

nolo

gies

is

ca

lled

a he

tero

gene

ous

netw

ork

sinc

e it

mai

ntai

ns

its

conn

ectio

ns

whi

le

switc

hing

fr

om

one

netw

ork

to

anot

her

netw

ork.

Het

erog

eneo

us n

etw

orks

util

izin

g a

dive

rse

set

of b

ase-

stat

ions

can

be

depl

oyed

to

impr

ove

spec

tral

effic

ienc

y pe

r un

it ar

ea.

H

eter

ogen

eous

netw

orks

mus

t ha

ve t

he a

bilit

y to

man

age

and

cont

rol

inte

rfer

ence

in

netw

orks

whi

ch p

rovi

des

subs

tant

ial g

ains

in th

e ca

paci

ty a

nd p

erfo

rman

ce o

f

wire

less

syst

ems i

n th

e fu

ture

.

51

The handover management process is shown in Figure 3.1. The

various strategic metrics for handover decisions are network-controlled,

mobile-terminal controlled and both network and mobile terminal controlled.

In this context, a network selection decision is made at call setup and

subsequently the decision is re-made if a handover is triggered.

The process consists of the following three main steps:

Handover Discovery - this step can play different roles:

monitoring the network conditions, listing the available

networks, predicting/estimating the characteristics for each

network, etc. and using the monitored data to trigger a HO

decision.

Handover Decision - handles the Network Selection process

and is initiated either by an automatic trigger for a HO for an

existing call or by a request for a new connection by the

mobile device. The selection of the best network is decided

based on the decision criteria provided by the device, the

application and the monitoring process. After the target

network is selected, the call is set up on the target candidate

network. Traditionally, this decision was made by the network

operators both for mobility and load balancing reasons. This

decision was based mainly on a single parameter (i.e.,

Received Signal Strength (RSS)). Whereas the proposed

system uses the Bayesian Game Theory concept for network

selection.

Handover Execution -After the target network is selected, the

connection is set up in the target candidate network. In case of

an existing connection, HO is executed and the original

52

connection is torn down and the call data is re-routed to the

new connection. If the first choice network is unavailable,

then the next listed candidate is chosen as the target network.

Connection setup (and teardown in the case of handover) will

be handled by a mobility management protocol.

3.4.1 Vertical Handover Decision Parameters

The application level vertical handover decision parameters and

triggering handoffs are explained as follows:

Decision Processing Delay is the processing time needed by a

mobile node to decide the network to which it has to

handover.

Handover Blocking Rate: It represents the percentage of

calls that do not finish their services. Lower level of blocking

rate reflects the overall system service continuity and scheme

efficiency.

Packet Loss is the amount of data lost during the handover

process. This depicts the efficiency of the scheme in terms of

availability.

Transmission Delay is the amount of time taken for

switching from a existing network to a foreign network during

handover. It is also a measure of the service continuity during

the handover process.

3.4.2 Triggering Handoffs

The Upward-Initiate begins when several beacons from the current

overlay network are not received. The Downward-Initiate begins when

53

several beacons are heard from a lower overlay’s network interfaces (NI). The

handoff starts when the lower overlay becomes reachable or unreachable, and

ends when the first data packet forwarded from the new overlay network

arrive at the MH.

The cross-layer information available in the different layers is

considered for vertical handover decision. The cross-layered handoff solution

scheme is more effective and it is explained in the subsequent section.

3.5 SEAMLESS VERTICAL HANDOVER DECISION

TECHNIQUES

There are many solution strategies for providing seamless vertical

handover support in 4G networks and VANETs which are:

Seamless integration of Mobile WiMAX in 3GPP Networks to

provide efficient seamless broadband wireless access.

Vertical Handoff algorithms for connection management and

optimal resource allocation using link-layer MIHF for

Seamless Mobility at vehicular speeds.

All-IP principle which hides heterogeneity and achieve

convergence of various networks. The IP at layer-3 and MIHF

at layer-2 make network assisted/mobile controlled seamless

mobility. If the mobile device capabilities are limited, handoff

decisions are taken by mobility agents (IDE) on the network

side.

There is an existence of handover decision taxonomy module.

There are the four following handover strategies - network-controlled,

mobile-controlled, network-assisted and mobile-assisted handover. The

54

netw

ork-

cont

rolle

d an

d m

obile

-ass

iste

d so

ft-co

mpu

ting

verti

cal

hand

over

deci

sion

(VH

D) a

ppro

ache

s are

pre

sent

ed in

the

follo

win

g se

ctio

ns.

3.5.

1 N

etw

ork

Para

met

ers B

ased

Ver

tical

Han

dove

r D

ecis

ion

The

netw

ork

disc

over

y m

odul

e re

ports

the

Net

wor

ks’

Rec

eive

d

Sign

al S

treng

th (

RSS

), ba

ndw

idth

, jit

ter,

dela

y, e

tc.,

para

met

ers

of e

very

avai

labl

e ne

twor

k in

the

cov

erag

e ar

ea o

f th

e M

obile

Nod

e (M

N).

The

hand

over

nec

essi

ty e

stim

ator

mod

ule

com

pare

s th

e ne

twor

k re

sour

ces

with

user

’s re

quire

men

t and

dec

ides

the

nece

ssity

of h

ando

ver.

The

hand

over

dec

isio

n m

odul

e de

cide

s an

d ch

oose

s th

e ne

twor

k

whi

ch o

ffer

s hi

ghes

t Q

oS a

t m

inim

al c

ost

whe

n th

e M

N i

s in

the

ove

rlay

cove

rage

of

the

netw

orks

. Th

e ha

ndov

er e

xecu

tor

mod

ule

exec

utes

the

hand

over

pro

cess

in L

2 (li

nk-la

yer)

or

L3 (n

etw

ork-

laye

r) o

r bot

h L2

and

L3

cros

s-la

yer b

ased

seam

less

Ver

tical

Han

dove

r.

The

follo

win

g ne

twor

k pa

ram

eter

s na

mel

y re

ceiv

ed s

igna

l stre

ngth

(RSS

), ba

ndw

idth

, con

gest

ion

and

cost

are

con

side

red

for

verti

cal h

ando

ver

deci

sion

. The

follo

win

g ap

proa

ches

are

use

d to

ach

ieve

the

seam

less

ver

tical

hand

over

dec

isio

n an

d al

so g

over

n th

e Q

ualit

y of

Exp

erie

nce

(QoE

) of

the

user

by

usin

g Q

ualit

y of

Ser

vice

(QoS

) par

amet

ers.

1.Se

amle

ss M

edia

Inde

pend

ent R

esili

ence

Trig

gerin

g (S

MIR

T)

2.A

pplic

atio

n-or

ient

ed M

edia

-Ind

epen

dent

Ver

tical

Han

dove

r

Dec

isio

n (A

MIV

HD

)

3.A

dapt

ive

Ban

dwid

th A

lloca

tion

(AB

A)

and

Cal

l A

dmis

sion

Con

trol (

CA

C)

4.C

onge

stio

n-A

war

e V

ertic

al H

ando

ver D

ecis

ion

(CA

VH

D)

55

The seamless vertical handover can also be achieved using soft

computing approaches which are explained in the subsequent section.

3.5.2 Soft Computing Based Vertical Handover Decision

The soft-computing techniques like neural networks and fuzzy

logic, Grey-Relational Analysis, Nash-equilibrium game-theoretic approach,

MDP based Ranking approaches are used to achieve the handover decision.

Soft computing based vertical handover approaches are:

1. Weighted – SAW and MEW Vertical handover

2. GRA – Grey Relational Analysis Vertical handover

3. TOPSIS based Vertical handover

4. Game-Theoretic Nash-Equilibrium based Vertical handover

5. Extended MDP (EMDP) based Vertical handover

6. Real-Time Mobility Models Framework for VANETs

The above mentioned network parameters based VHD and soft

computing based VHD design details and its implementations are provided in

Chapter 5, Chapter 6 and Chapter 7 respectively.

3.6 SEAMLESS MEDIA INDEPENDENT RESILIENCE

TRIGGERING (SMIRT)

The dual-mode mobile stations (MSs) which roam between

wireless local area network (WLAN) and cellular networks. The act of

transitioning from WLAN to cellular is commonly referred to as a vertical

handoff (VHO). The Seamless Media Independent Resilience Triggering

(SMIRT) framework is developed to achieve Vertical Handover Decision

56

(VHD) in Heterogeneous 4G Wireless Overlay Networks. Figure 3.1 shows

the SMIRT architecture for VHD.

A call admission control (CAC) algorithm is another key factor

that enables efficient system resource utilization while ensuring that

connection-level QoS requirements are satisfied. CAC is always performed

when a mobile initiates communication in a new cell, either through a new

call or a handoff.

3.6.1 SMIRT Framework

SMIRT framework helps to do handover for heterogeneous

networks and has the following modules as shown in Figure 3.2.

Figure 3.2 SMIRT Framework Architecture

57

Network Discovery: MT searches for reachable wireless networks.

Handover Decision:

Handover necessity estimation: It determines whether a

handover is necessary or not from the current network.

Handover target selection: It chooses the “best”

network among the available network based on a set of

criteria.

Handover triggering condition: It determines the right

moment to initiate a handover out of the currently

connected network.

3.6.2 SMIRT Algorithm

The SMIRT algorithm is explained as follows:

Step 1 : Discover the available networks using the

interface services of IEEE 802.21 MIHF.

Step 2 : Calculate the quality of the networks after

analyzing the handover necessity estimation.

Step 3 : Select the network which has highest QoS.

Step 4 : Perform make-before-break soft handover.

Step 5 : Trigger the handover at the right moment.

58

3.7 CROSS-LAYER BASED VERTICAL HANDOVER

DECISION

The proposed handover system is based on cross-layered approach.

It has four new functional modules. Monitoring agent (MA) for each protocol

layer, and profile database (PDB) are the functional modules that facilitate

efficient inter-layer communications. The MAs are the interface for each

legacy protocol layers to monitor and collect protocol specific dynamic status

information as well as to adjust the protocol controls without requiring direct

modification to the existing protocols.

Figure 3.3 Cross-Layered Handover Approach

The PDB maintains both the static and dynamic information

necessary for handover related decisions and processes, and the dynamic part

of the information in the PDB are updated by the MAs. The protocol specific

Application Side

ApplicationNetwork Side

IP Agent

Network

Data Link

Physical

Profile DB(PDB)

Decision Engine (DE)

Transport

59

dynamic status information collected in the PDB greatly facilitates the

availability of cross-layer information necessary for handover decisions. The

decision engine (DE) maintains the per-application handover processing

policies to enable seamless handover of each user session.

A set of rules to determine when to trigger the handover decision

procedure for a certain service flow is also maintained to avoid unnecessary

handover decision processing caused by redundant status reports from

multiple MAs. In making the handover decisions, the DE utilizes the

information of the predefined key parameters across the protocol layers by

obtaining the necessary static/dynamic data from the PDB. IP Agent is

responsible for the mapping of the end point addresses of ongoing sessions to

the addresses corresponding to the current location. It enables the discovery of

a peer’s current location as well as the continuity of data delivery transparent

to the mobility by tracking IP address changes of end points as shown in

Figure 3.3.

This chapter provided the literature survey along with the

limitations of the existing systems and the proposed systems which are

providing the solutions.

3.8 GAME-THEORY BASED VERTICAL HANDOVER

DECISION

The seamless vertical handover decision is based on game-theoretic

Nash-equilibrium. Vertical Handoff Decision Making problem is one of the

significant technical issues in the development of Heterogeneous wireless

networks. This paper presents a vertical handoff decision algorithm based on

game theory approach. In this algorithm, the handoff decision problem is

formulated as a non cooperative game between the mobile users and the

wireless networks that are available in the vicinity of the mobile user. It

60

considers terminal parameters such as QOS requirements of the mobile

application along with the velocity of the mobile terminal. It also considers

network parameters such as available bandwidth and cost per bit offered by

each network. The algorithm chooses the target network with maximum

network utilization that offers services at lower prices.

3.8.1 Game-Theory Based Vertical Handover in VANETs

Thesis focuses on a vertical handoff decision algorithm based on

Bayesian Evolutionary game model. When a mobile host is under the

coverage of more than one wireless network, it performs network selection

iteratively to achieve best quality of service at minimum cost. The decisions

evolve to an equilibrium point at which the quality of a network access

service is maximized and the cost of the service is minimized.

This solution is termed as Bayesian Nash equilibrium and is found

by solving pair-wise matrix. If there is no Nash equilibrium solution for the

game, the algorithm finds the sub-optimal solution. The Game Theory based

Seamless Vertical Handover Decision with hybrid Emergency-Braking in

Vehicular Network follows the following principle:

As long as the vehicles have sufficient inter-vehicular distance

the speed remains the same as set by the user.

Reduce the speed of the vehicle when the inter-vehicular

distance is lesser than safe distance.

Broadcast warning messages to other vehicles behind, when

the vehicle decelerates fast indicating a crash.

The Vehicles receiving the packet broadcasts the packet

before coming to halt.

61

Choose the best available network for vehicle to roadside

communication with respect to the changing speed values of

the vehicle using game theory and MDP concepts.

The various types of Game Theory models are as follows:

3.8.1.1 User Vs user

Co-operative:

Many nodes with one service provider.

Strategy used: Random arrival value is assigned on a first come

first serve basis. Here, the bandwidth is divided to the users based on their

arrival.

Non co-operative:

Many nodes, many service providers

Strategy used: Evolutionary Game theory

To select the least congested AP. As a node arrives into a new area

with lot of other nodes it simply selects the AP which has less number of

nodes. A weighted sum score function based on the AP’s load, the price and

the distance at which the user must travel to reach the new AP is calculated.

3.8.1.2 User Vs network

Co-operative:

Grim strategy- once the user leaves the network he never

returns back to it.

Non co-operative:

62

Bargain strategy-many nodes compete for a network by

bidding. The node with highest bid gets maximum payoff

from the service provider.

3.8.1.3 Network Vs network

Co-operative:

Bankruptcy game

The node which arrives without any bandwidth is treated as

Bankrupt node. So all the network providers combine and provide the

bandwidth.

Non co-operative:

The networks compete against each other, seeking to maximize

their individual revenues. The solution point is obtained using non-

cooperative Game-theoretic Nash-equilibrium. If multiple solutions exist then

sub-optimal solution is obtained using the ranking approach.

3.8.2 Constrained MARKOV Decision Process (MDP) Based

Vertical Handover

The rank value is calculated by using benefit and penalty values of

the each available network. The Markov chain is a common tool for decision

making. MDP can be used to handle multi objective dynamic decision-

making problem. MDP model solves network selection and VHO decision

at one time by considering both benefit f(st, at) and handover cost g(st, at).If

only f(st, at) is considered, this model tells us the best network at all the

decision epochs.

63

The MDP decision system model is presented and the governing

Equations (3.1) to (3.7) are represented as follows:

EMDP System Model

The system model and the decision approach of the EMDP model

are presented as follows:

1. Decision Epoch (DE)

DE = F x T x P (3.1)

where

F = {fixed(f), mobile(m)}

T = {voice(v), data(d)}

P = {preference: low-cost(lc), high-quality(hq)}

States (S) is defined as

S = DE x M (3.2)

M = N x B1 xD1xJ1xE1x…….x Bn xDnxJnxEn x V x L x C

where

n N

N = Set of available networks

Bn = bandwidth of the network n; Bn ={1,2,….bnmax}

Dn= delay of the network n; Dn ={1,2,….dnmax}

64

Jn = Jitter of the network n; Jn ={1,2,….jnmax}

En= error-rate of the network n; En ={1,2,….enmax}

V = {0,1,2,………vmax}

L = {1,2,3……lmax}

C={ Conversational, Streaming, Interactive, Background}

2. Let us introduce vectors for the current and next-state

Current-State, S = {i , b1, d1, j1, e1, …… b|n|, d|n|, j|n|, e|n| , v, l, c}

Next-State, S’= {j , b’1, d’1, j’1, e’1, …… b’|n|, d’|n|, j’|n|, e’|n| , v’, l’, c’}

3. Actions

A={Conversational, Streaming, Interactive, Background} (3.3)

Example: Conversational – VoIP, Streaming – Video, Interactive – HTTP,

Background –e-mail

4. Transition Probability

DEDE';0DEDE'if];e,j,d,be,j,d,Pr[bl][l'PV][V'P

a]S,[S'P nnnn'n

'n

'n

'nNnrr

r (3.4)

where a A

v’ = v + (1 + 21

1

2

' mr

m-1 m m+1max

m

m-1 m

ALTALT1+ ALT if 1

ALTP / if 2 1ALT ALT ALT

if l = lALT

ALT ALT

ll l l to m

65

ALTi – Area of LTi ; LT-Location Type

5. Policy-Reward function

fr(S, a) = fben(S, a) fpen(S, a) (3.5)

6. Optimal-policy

The optimal policy is governed to provide the maximum QoS with

minimal cost of the selected target network as per the Lagrangian’

approach

Maximize the reward function

)(S'a]S,S'[P)a;(S,rAa

max(S)

SS'r

S

(3.6)

– discount-factor (ie., 0 to 1)

The Q-learning algorithm gives the proper .

maxCCk1

zk1k )

where z varires from 1 to N

and

Minimize the cost

Ctotal = min {Cjtotal /j=1,2,…N} (3.7)

66

The sample QoS offered and requested values are presented below:

Table 3.1 Offered QoS Parameters

Table 3.2 QoS Threshold Parameters

BTh DTh VTh JTh ETh

80 100 60 50 150

Table 3.3 QoS Required Parameters

Parameter / QoS Classes

Bandwidth (Mbps)

Packet Delay(msec)

Supported Velocity (Kmph)

Jitter(msec)

BER (per 108)

UGS

(Voice – VoIP)

10 200 5 60 400

rtPS(Streaming-Video)

25 300 5 60 400

nrtPS

(Interactive-HTTP)

15 300 5 200 250

BE

(Background-Email)

20 400 5 300 250

Parameter / Network

Bandwidth (Mbps)

Delay(msec)

Supported Velocity (Kmph)

Jitter(msec)

BER(per 108)

WiFi 54 160 10 50 200 WiMAX 70 120 20 40 150 LTE-A 150 70 50 30 100

67

Table 3.4 Cost per bit Offered by Each Network

Network WiFi WiMAX LTE-A

Cost 0.2 0.4 0.6

Table 3.5 Pair-Wise Nash-Equilibrium Matrix

Network /

QoS Classes

WiFi WiMAX LTE-A

UGS

(Voice – VoIP)

0.094, 0.128, 0.170,0.6

rtPS (Streaming-Video)

0.106, 0.133, 0.129,0.6

nrtPS

(Interactive-HTTP)

0.056, 0.065,0.4 0.122,0.6

BE

(Background-Email)

0.056,0.2 0.071,0.4 0.130,0.6

It is observed from the pair-wise matrix that the equilibrium is

achieved for various traffic classes and hence the decision can be made

optimally. For example, VoIP calls select LTE-A network by using Nash-

equilibrium solution point.

68

Figure 3.4 Delay Vs Network-Utility

Figure 3.5 Delay Vs QoS-Ratio

0

0.05

0.1

0.15

0.2

0.25

0.3

200 400 600 800

Net

wor

kut

ility

DELAY

Conversation-varying Delay

LTE

WIMAX

WIFI

0

0.05

0.1

0.15

0.2

0.25

0.3

40 80 120 160 200

QoS

RATI

O

DELAY

VIDEO- QoS vs DELAY

LTE

WIMAX

WIFI

69

The performance graph shows that Network-Utilization and QoS ratio

are relatively high in LTE networks which is shown in Figure 3.4 and

Figure 3.5 respectively. The pair-wise solution matrix shows that equilibrium

solutions arrived for VoIP, Straming and Intreactive traffic classes at LTE-A,

LTE-A and WiMAX networks respectively. But there is no solution point for

E-mail services, hence the sub-optimal solution is obtained using MDP based

ranking method.

Example: Conversational – VoIP, Streaming – Video, Interactive – HTTP,

Background –e-mail

The selection of the best network is based on the highest reward

with minimal penalty value of that network in order to maximize the objective

function. In this work, a vertical handoff decision algorithm for 4G wireless

networks is presented. The problem is formulated as a constrained Markov

decision process. The objective is to maximize the expected total reward per

connection subject to the expected total access cost constraint.

3.9 SUMMARY

This Chapter presented the various vertical handover decision

solutions proposed by this thesis. A simple handover management process

based on mobile-terminals and network controlled inputs were discussed. The

various seamless vertical handover decision techniques such as application-

oriented, QoS-centric and congestion-aware approaches for 4G networks were

presented. Also the Game-theoretic and MDP approaches were applied to

vertical handover decision for vehicular networks and explored. The general

vertical handover decision frameworks for 4G networks and VANETs are

presented in Chapter 4.