Journal of Northeastern University Natural Science ›› 2018, Vol. 39 ›› Issue (5): 619-623.DOI: 10.12068/j.issn.1005-3026.2018.05.003

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Improved SLM Algorithm for Reducing OFDM System Complexity

JI Ce, JIA Dian-xia, ZHANG Chao, ZHU Wen-jing   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110169, China.
  • Received:2016-12-08 Revised:2016-12-08 Online:2018-05-15 Published:2018-05-25
  • Contact: JIA Dian-xia
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Abstract: In order to reduce the computational complexity of the traditional selective mapping(SLM)algorithm in OFDM(orthogonal frequency division multiplexing) systems, and improve the spectral efficiency of the system, a CR-SLM algorithm based on the combination of conversion vectors and random selection sequences was proposed. In this algorithm, the data sequence is equally divided into two parts. For the first half of the data sequence IFFT(inverse fast Fourier transform) is taken, and then circular convolution is performed. Random sequence screening is applied for the second half section to reduce the complexity. Finally, the two output sequences are grouped together to generate candidate sequences, and the optimal sequence is selected for transmission. The simulation results show that the CR-SLM algorithm greatly reduces the computational complexity while maintaining the PAPR(peak to average power ration) close to that of the conventional SLM algorithm.

Key words: orthogonal frequency division multiplexing(OFDM), SLM algorithm, conversion vector, random selection sequence, peak to average power ratio(PAPR)

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