By Topic

A multiobjective optimization framework for IEEE 802.16e network design and performance analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Fernando Gordejuela-Sanchez ; Univ. of Bedfordshire, Luton ; Alpar Juttner ; Jie Zhang

In this paper, a multiobjective optimization framework that tackles the problem of mobile WiMax access network design is presented. In the first stage of the network development, the most important issue is to find an appropriate solution to the base station location from a given set of candidate sites. The network can be considerably improved if the base station location solution found during the planning phase is designed to achieve optimal performance, and also reliable and cost-effective mobile WiMax networks. The design process is done through computer simulation to predict the network performance, and it is often carried out by planning and optimization tools similar to those used in the development of 2nd generation cellular networks (2G) with a few adaptations. The multiobjective optimization framework gives network providers a new perspective in mobile WiMax access network design, providing a clear and comprehensive description of different options and solutions to achieve an optimal base station location. Also, it analyzes the network performance with the mobile WiMax-specific parameters that most importantly affect the access network design process. It simplifies the problem and translates it into a formal optimization routine with consideration of economic factors in mobile WiMax networks. This has been done by using the method of the Pareto front, and the use of an optimization strategy based on a modified version of the metaheuristic Tabu search adapted to multiobjective optimization.

Published in:

IEEE Journal on Selected Areas in Communications  (Volume:27 ,  Issue: 2 )