Wireless heterogeneous transmitter placement using multiobjective variable-length genetic algorithm

Authors:
Chuan-Kang Ting;Chung-Nan Lee;Hui-Chun Chang;Jain-Shing Wu
Affiliations:
Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan;Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan;Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan;Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Year:
2009

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Abstract

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.