Peak-to-Average Power Ratio Reduction Algorithm Based on Double Optimization in FBMC-OQAM System

Hui ZHAO; Wei WANG; Jinrong MO; Zhenjiang SUN; Tianqi ZHANG

doi:10.11999/JEIT200369

Volume 43 Issue 6

Jun. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(6): 1742-1749

Hui ZHAO, Wei WANG, Jinrong MO, Zhenjiang SUN, Tianqi ZHANG. Peak-to-Average Power Ratio Reduction Algorithm Based on Double Optimization in FBMC-OQAM System[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1742-1749. doi: 10.11999/JEIT200369

Citation:

Hui ZHAO, Wei WANG, Jinrong MO, Zhenjiang SUN, Tianqi ZHANG. Peak-to-Average Power Ratio Reduction Algorithm Based on Double Optimization in FBMC-OQAM System[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1742-1749. doi: 10.11999/JEIT200369

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Peak-to-Average Power Ratio Reduction Algorithm Based on Double Optimization in FBMC-OQAM System

doi: 10.11999/JEIT200369

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61671095)

Received Date: 2020-05-08
Rev Recd Date: 2020-10-14

Available Online: 2020-10-21

Publish Date: 2021-06-18

Abstract

Abstract

The Partial Transmission Sequences (PTS) algorithm is affected by symbol overlap in the Filter Bank MultiCarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM), resulting in peak value regeneration, which leads to high Peak-to-Average Power Ratio (PAPR) and computational complexity. In this paper, a PTS algorithm based on Double Optimization (DO-PTS) is proposed, which searches two-layer phase factor for signal data blocks to obtain better PAPR suppression performance. The first layer takes full account of the overlap characteristics and combines the previous overlapping data blocks for initial optimization. The second layer groups the signals, and in each group, the data blocks that have the greatest impact on the peak value are optimized to reduce the number of data blocks for phase factor search. The search range of phase factor is reduced in the first layer optimization to reduce the calculation complexity. Through the analysis of computational complexity and simulation results, it is shown that compared with other mainstream PTS optimization methods, this algorithm can not only offer good PAPR reduction performance, but also have low computational complexity, and also ensure the transmission data rate of the system.

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References(15)

References

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