TY - GEN
T1 - A Frequency Offset Estimation Algorithm Based on Under-Sampling for THz Communication
AU - Song, Shiqi
AU - Liu, Dekang
AU - Wang, Fei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/9
Y1 - 2018/10/9
N2 - The frequency offset estimation algorithm for terahertz (THz) communication is not only required to deal with estimation accuracy, SNR (signal-to-noise ratio) threshold and estimation range, but also needs to take high Doppler shift caused by high operating band, the complexity of real-signal processing and large hardware cost into consideration. A carrier frequency offset estimation algorithm based on under sampling for THz communication is proposed in this paper. This algorithm utilizes methods including narrow band filtering (the bandwidth of filtered signal is only about 0.1% of the original signal bandwidth), under-sampling based on coprime sampling and second time estimation. For signal processing, we use FFT (Fast Fourier Transform) to achieve correlation operation on the frequency domain, which effectively reduce the computational complexity. The method we proposed significantly reduce the sampling rate as well as improve the estimation accuracy and thus can be applied to THz communication. The simulation results show that the algorithm can estimate a large dynamic range of the frequency offset at a low SNR with a low sampling rate, which reduce the difficulty of signal processing and hardware design.
AB - The frequency offset estimation algorithm for terahertz (THz) communication is not only required to deal with estimation accuracy, SNR (signal-to-noise ratio) threshold and estimation range, but also needs to take high Doppler shift caused by high operating band, the complexity of real-signal processing and large hardware cost into consideration. A carrier frequency offset estimation algorithm based on under sampling for THz communication is proposed in this paper. This algorithm utilizes methods including narrow band filtering (the bandwidth of filtered signal is only about 0.1% of the original signal bandwidth), under-sampling based on coprime sampling and second time estimation. For signal processing, we use FFT (Fast Fourier Transform) to achieve correlation operation on the frequency domain, which effectively reduce the computational complexity. The method we proposed significantly reduce the sampling rate as well as improve the estimation accuracy and thus can be applied to THz communication. The simulation results show that the algorithm can estimate a large dynamic range of the frequency offset at a low SNR with a low sampling rate, which reduce the difficulty of signal processing and hardware design.
KW - THz communication
KW - co-prime sampling
KW - frequency offset estimation
KW - narrowband filtering
KW - second time estimation
UR - http://www.scopus.com/inward/record.url?scp=85056403864&partnerID=8YFLogxK
U2 - 10.1109/ICCSN.2018.8488301
DO - 10.1109/ICCSN.2018.8488301
M3 - Conference contribution
AN - SCOPUS:85056403864
T3 - 2018 10th International Conference on Communication Software and Networks, ICCSN 2018
SP - 215
EP - 220
BT - 2018 10th International Conference on Communication Software and Networks, ICCSN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Communication Software and Networks, ICCSN 2018
Y2 - 6 July 2018 through 9 July 2018
ER -