A Fast Carrier Frequency Offset Position Detection Algorithm for Passive Backscatter Communication System

WANG Gongpu; XU Yating; XU Rongtao; CHEN Xia; AI Bo

doi:10.11999/JEIT221558

Volume 45 Issue 7

Jul. 2023

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(7): 2311-2316

WANG Gongpu, XU Yating, XU Rongtao, CHEN Xia, AI Bo. A Fast Carrier Frequency Offset Position Detection Algorithm for Passive Backscatter Communication System[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2311-2316. doi: 10.11999/JEIT221558

Citation:

WANG Gongpu, XU Yating, XU Rongtao, CHEN Xia, AI Bo. A Fast Carrier Frequency Offset Position Detection Algorithm for Passive Backscatter Communication System[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2311-2316. doi: 10.11999/JEIT221558

Citation:

PDF( 1170 KB)

A Fast Carrier Frequency Offset Position Detection Algorithm for Passive Backscatter Communication System

doi: 10.11999/JEIT221558

1.
School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
2.
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Funds: The National Key R&D Program of China (2021YFB3901302)

Received Date: 2022-12-19
Rev Recd Date: 2023-06-08

Available Online: 2023-06-14

Publish Date: 2023-07-10

Abstract

Abstract

Recently, passive backscatter communication technology has attracted extensive attention as one key technology for green Internet of Things. In one typical backscatter communication system, there may exist Carrier Frequency Offset (CFO) between the receiver and the transmitter due to the relative motion or the difference in oscillators or environmental changes. CFO has an important impact on signal detection and system performance, but most current studies ignore the CFO. In this paper, a fast CFO detection method suitable for Frequency Shift Keying (FSK) modulation is designed, which can quickly and effectively detect without pilots whether there exists CFO and find out the location where the CFO begins. Specifically, this paper designs one detector amplitude-taking method. Next, based on CUmulative SUM (CUSUM) algorithm a fast detection algorithm is designed to detect the location of CFO. Finally, simulation results are provided to corroborate the proposed studies. The simulation results show that the designed detector can effectively locate the position where CFO appears.
- Backscatter communication,
- Carrier frequency offset,
- Fast detection,
- Internet of things

FullText(HTML)

References(18)

References

[1]	张晓茜, 徐勇军. 面向零功耗物联网的反向散射通信综述[J]. 通信学报, 2022, 43(11): 199–212. doi: 10.11959/j.issn.1000-436x.2022199 ZHANG Xiaoxi and XU Yongjun. Survey on backscatter communication for zero-power IoT[J]. Journal on Communications, 2022, 43(11): 199–212. doi: 10.11959/j.issn.1000-436x.2022199
[2]	XING Chengwen, JING Yindi, WANG Shuai, et al. New viewpoint and algorithms for water-filling solutions in wireless communications[J]. IEEE Transactions on Signal Processing, 2020, 68: 1618–1634. doi: 10.1109/TSP.2020.2973488
[3]	CAO Yinwen, YU Song, SHEN Jing, et al. Frequency estimation for optical coherent MPSK system without removing modulated data phase[J]. IEEE Photonics Technology Letters, 2010, 22(10): 691–693. doi: 10.1109/LPT.2010.2044170
[4]	LEVEN A, KANEDA N, KOC U V, et al. Frequency estimation in intradyne reception[J]. IEEE Photonics Technology Letters, 2007, 19(6): 366–368. doi: 10.1109/LPT.2007.891893
[5]	FATADIN I and SAVORY S J. Compensation of frequency offset for 16-QAM optical coherent systems using QPSK partitioning[J]. IEEE Photonics Technology Letters, 2011, 23(17): 1246–1248. doi: 10.1109/LPT.2011.2158994
[6]	HUANG Dezhao, CHENG T H, and YU Changyuan. Accurate two-stage frequency offset estimation for coherent optical systems[J]. IEEE Photonics Technology Letters, 2013, 25(2): 179–182. doi: 10.1109/LPT.2012.2232288
[7]	YANG Tao, SHI Chen, CHEN Xue, et al. Hardware-efficient multi-format frequency offset estimation for M-QAM coherent optical receivers[J]. IEEE Photonics Technology Letters, 2018, 30(18): 1605–1608. doi: 10.1109/LPT.2018.2863739
[8]	KIM J W, LEE Y S, JIN M Y, et al. Carrier frequency offset estimation for OFDM system with large oscillator phase noise[C]. 2021 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Korea, 2021: 368–370.
[9]	ZHENG Shuai, CHEN Jian, KUO Yonghong, et al. Statistical histogram-based blind frequency offset estimation for MPSK and MQAM signal[C]. 2022 International Conference on Machine Learning and Knowledge Engineering (MLKE), Guilin, China, 2022: 125–129.
[10]	JAYAPRAKASH A and REDDY G R. Covariance-fitting-based blind carrier frequency offset estimation method for OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2016, 65(12): 10101–10105. doi: 10.1109/TVT.2016.2542181
[11]	PAGE E S. A test for a change in a parameter occurring at an unknown point[J]. Biometrika, 1955, 42(3/4): 523–527. doi: 10.2307/2333401
[12]	KESHAVARZ H, SCOTT C, and NGUYEN X. Optimal change point detection in Gaussian processes[J]. Journal of Statistical Planning and Inference, 2018, 193: 151–178. doi: 10.1016/j.jspi.2017.09.003
[13]	KO S I M, CHONG TT L, and GHOSH P. Dirichlet process hidden Markov multiple change-point model[J]. Bayesian Analysis, 2015, 10(2): 275–296. doi: 10.1214/14-BA910
[14]	KOKOSZKA P and LEIPUS R. Change-point in the mean of dependent observations[J]. Statistics & Probability Letters, 1998, 40(4): 385–393. doi: 10.1016/S0167-7152(98)00145-X
[15]	NA O, LEE Y, and LEE S. Monitoring parameter change in time series models[J]. Statistical Methods & Applications, 2011, 20(2): 171–199. doi: 10.1007/s10260-011-0162-3
[16]	LING Jin, LI Xiaoqin, YANG Wenzhi, et al. The CUSUM statistic of change point under NA sequences[J]. Applied Mathematics-A Journal of Chinese Universities, 2021, 36(4): 512–520. doi: 10.1007/s11766-021-4015-z
[17]	YU Yuncai and CHEN Zhicheng. Strong convergence rates of multiple change-point estimator for ρ-mixing sequence[J]. Communications in Statistics - Theory and Methods, 2023, 52(13): 4605–4621. doi: 10.1080/03610926.2021.1998532
[18]	KIM K, PARK J H, LEE M, et al. Unsupervised change point detection and trend prediction for financial time-series using a new CUSUM-based approach[J]. IEEE Access, 2022, 10: 34690–34705. doi: 10.1109/ACCESS.2022.3162399