22-08-2014, 04:02 PM
An Optimum Vertical Handoff Decision Algorithm for UMTS-WiMAX Project Report
An Optimum Vertical.pdf (Size: 829.93 KB / Downloads: 10)
Abstract
The integration of diverse but complementary cellular
and wireless technologies in the next generation of wireless
communication systems requires the design of intelligent vertical
handoff decision algorithms to enable mobile users to seamlessly
switch network access and experience uninterrupted service
continuity anywhere and anytime. This paper provides an adaptive
multiple attribute vertical handoff decision algorithm that enables
wireless access network selection at a mobile terminal using fuzzy
logic concepts and a genetic algorithm. A performance study using
the integration of wireless wide area networks (WWANs) and
wireless metropolitan area networks (WMANs) as an example shows
that our proposed vertical handoff decision algorithm is able to
determine when a handoff is required, and selects the best access
network that is optimized to network conditions, quality of service
requirements, mobile terminal conditions, user preferences, and
service cost.
INTRODUCTION
The next generation of wireless communication systems,
called beyond third generation (B3G) or fourth generation
(4G), will involve the integration of diverse but
complementary cellular and wireless technologies, all of
which will coexist in a heterogeneous wireless access
environment and use a common IP core to offer a diverse
range of high data rate multimedia services to end users since
the networks have characteristics that complement each other.
For example, IEEE 802.16 or WiMAX (World-wide
Interoperability for Microwave Access) can be used as a
complementary access technology to third-generation (3G)
cellular WWAN such as Universal Mobile
Telecommunications System (UMTS) where users are always
connected to access dynamic and powerful applications such
as the Internet, voice and video. While 3G systems are
designed primarily for mobile voice and data users, WiMAX
systems are optimized to provide high-rate wireless
connectivity for services and applications that require quality
of service (QoS) guarantees. In addition, a mobile WiMAX
overlay to a 3G wireless system can provide mobile operators
with low cost additional capacity in spectrum and
infrastructure limited regions, new real-time high speed data
services, a proven and available path to an all-IP future
OVERVIEW OF THE VERTICAL HANDOFF DECISION ALGORITHM (VHDA)
A vertical handoff decision in a next generation wireless
network environment (including WWAN, WLAN, WMAN,
and Digital Video Broadcasting) must solve the following
problem: given a mobile user equipped with a contemporary
multi-interfaced mobile device connected to an access
network, determine whether a vertical handoff should be
initiated and dynamically select the optimum network
connection from the available access network technologies to
continue with an existing service or begin another service.
Hence, our proposed VHDA consists of two parts [9]:
(a) A Fuzzy Logic Handoff Initiation Algorithm which uses a
fuzzy logic inference system (FIS) to process a multi-criteria
vertical handoff initiation metrics, and
(b) An Access Network Selection Algorithm which applies a
unique fuzzy multiple attribute decision making (FMADM)
access network selection function to select a suitable wireless
access network.
NETWORK SELECTION ALGORITHM
A suitable access network has to be selected once the
handoff initiation algorithm indicates the need to handoff from
the current access network to a target network. We formulate
the network selection decision process as a MADM problem
that deals with the evaluation of a set of alternative access
networks using a multiple attribute access network selection
function (ANSF) defined on a set of attributes. The ANSF is
an objective function that measures the efficiency in utilising
radio resources and the improvement in quality of service to
mobile users gained by handing off to a particular network. It
is defined for all alternative target access networks that cover
the service area of a user. The network that provides the
highest ANSF value is selected as the best network to handoff
from the current access network according to the mobile
terminal conditions, network conditions, service and
application requirements, cost of service, and user preferences
GA OPTIMIZATION OF THE ANSF
This section explores the use of GAs for solving the
optimization problem of maximizing the ANSF in equation
(5). We do not use mathematical optimization (e.g., the
MATLAB Optimization toolbox) because it always selects the
upper bounds of a solution vector x as the optimum solution.
The GA is a search method for solving both constrained and
unconstrained optimization problems that is based on natural
selection, the process that drives biological evolution [12].
Each solution is associated with a fitness measure that reflects
how good it is, compared with other solutions in the
population. The measure could be an objective function that is
a mathematical model or a computer simulation. In the
following, we assume a function minimization problem.
Hence, a good solution is one that has low relative fitness.
We can use a GA to evolve solutions to a problem by the
following steps