PTS Technique Based on Micro-Genetic Algorithm with Low Computational Complexity 


Vol. 33,  No. 6, pp. 480-486, Jun.  2008


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  Abstract

The high peak-to-average power ratio (PAPR) of the transmitted signals is one of major drawbacks of the orthogonal frequency division multiplexing (OFDM). A partial transmit sequences (PTS) technique can improve the PAPR statistics of OFDM signals. However, in a PTS technique, the search complexity to select phase weighting factors increases exponentially with the number of sub-blocks. In this paper, a PTS technique with low computational complexity is presented, which adopts micro-genetic algorithm (μ-GA) as a search algorithm. A search on the phase weighting factors starts with a population of five randomly generated individuals. An elite having the largest fitness value and the other four individuals selected through the tournament selection strategy are determined, and then the next generation members are generated through the crossover operations among those. If the new generation converges, all the four individuals except the elite are randomly generated again. The search terminates when there has been no improvements on the PAPR during the predefined number of generations, or the maximum number of generations has been reached. To evaluate the performance of the proposed PTS technique, the complementary cumulative distribution functions (CCDF) of the PAPR are compared with those of the conventional PTS techniques.

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  Cite this article

[IEEE Style]

M. H. Kong and M. K. Song, "PTS Technique Based on Micro-Genetic Algorithm with Low Computational Complexity," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 6, pp. 480-486, 2008. DOI: .

[ACM Style]

Min Han Kong and Moon Kyou Song. 2008. PTS Technique Based on Micro-Genetic Algorithm with Low Computational Complexity. The Journal of Korean Institute of Communications and Information Sciences, 33, 6, (2008), 480-486. DOI: .

[KICS Style]

Min Han Kong and Moon Kyou Song, "PTS Technique Based on Micro-Genetic Algorithm with Low Computational Complexity," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 6, pp. 480-486, 6. 2008.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880