By Topic

Wireless Heterogeneous Transmitter Placement Using Multiobjective Variable-Length Genetic Algorithm

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

4 Author(s)
Chuan-Kang Ting ; Dept. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Chiayi ; Chung-Nan Lee ; Hui-Chun Chang ; Jain-Shing Wu

The problem of placing wireless transmitters to meet particular objectives, such as coverage and cost, has proven to be NP-hard. Furthermore, the heterogeneity of wireless networks makes the problem more intractable to deal with. This paper presents a novel multiobjective variable-length genetic algorithm to solve this problem. One does not need to determine the number of transmitters beforehand; the proposed algorithm simultaneously searches for the optimal number, types, and positions of heterogeneous transmitters by considering coverage, cost, capacity, and overlap. The proposed algorithm can achieve the optimal number of transmitters with coverage exceeding 98% on average for six benchmarks. These preferable experimental results demonstrate the high capability of the proposed algorithm for the wireless heterogeneous transmitter placement problem.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:39 ,  Issue: 4 )