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Turbo Receiver Channel Estimation for GFDM-Based Cognitive Radio Networks
Author(s) -
Zhenyu Na,
Zheng Pan,
Mudi Xiong,
Xin Liu,
Weidang Lu,
Yongjian Wang,
Lisheng Fan
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2803742
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Generalized frequency division multiplexing (GFDM) is a promising candidate for 5G waveforms because of its flexibility to meet the requirements of different scenarios and applications. Compared with the orthogonal frequency division multiplexing, the lower out-of-band radiation and higher spectrum efficiency make GFDM the qualified waveform solution for cognitive radio (CR). In CR networks, channel estimation is the necessity and premise to guarantee reliable spectrum sensing. Because of the block modulation structure for GFDM, conventional channel estimation algorithm cannot be applied to GFDM directly. Also, the feedback information in channel decoding is not fully utilized by the conventional algorithm. To solve these problems, in this paper, a modified turbo receiver is designed to utilize the feedback information for channel estimation. The modulator for the pilot insertion is also improved to make pilots orthogonal to data subcarriers. Based on the modified turbo receiver, an iterative channel estimation strategy combined with threshold control is proposed to cope with the noise enhancement. The symbols rebuilt for the iterative channel estimation are verified that only the credible symbols can be retained for the next iteration. Simulation results demonstrate that the proposed channel estimation method has the better bit error rate and mean-squared error performances over Rayleigh fading channel compared with the conventional algorithm.

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