By Topic

Optimization of Antenna Placement in 3G Networks Using Genetic Algorithms

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
$31 $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)
Munyaneza, J. ; French South African Tech. Inst. of Electron. (F''SATIE), Tshwane Univ. of Technol. (TUT), Tshwane ; Kurien, Anish ; Van Wyk, B.

Third generation (3G) cellular networks are being implemented in many countries at high rate. Due to the fact that manual cell planning is a time consuming process and prone to a degree of error and inefficiency, there is a need for automated approaches to optimise coverage, capacity and quality of cellular networks in a fraction of the time. This paper studies the application of genetic algorithms to solve the antenna placement problem (APP) in universal mobile telecommunication system (UMTS) networks. The parameters of the genetic algorithm are tuned so that the algorithm converges optimally. The main task of the algorithm is to find the best set of base station locations so as to maximise coverage and quality of service measured as the signal-to-interference and noise ratio (SINR), as well as minimise the network cost by using fewer base stations. Assuming that a flat area is considered, the performance of the proposed algorithm was evaluated with 98% of the users in the network being covered with a good quality signal.

Published in:

Broadband Communications, Information Technology & Biomedical Applications, 2008 Third International Conference on

Date of Conference:

23-26 Nov. 2008