Robust timing and frequency joint synchronization method for QNSC-enabled security optical communications system based on CO-OFDM

Guo, Hong; Zhang, Jie; Yang, Xiaokun; Zhang, Huibin

doi:10.1016/j.yofte.2022.103144

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…[16], weighted-conjugate symmetric sequence [17], Park-like conjugate symmetric preamble [18][19], a constant amplitude preamble weighted by PN sequence [20], andconjugate negative image (CNI) with PN and Chu Sequence [21].…”

Section: Introductionmentioning

confidence: 99%

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Kaur

2024

Opt Quant Electron

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The Quantum Noise Stream Cipher (QNSC) is offering very high security in physical layer of optical ber communication network to meet the today's main requirement of secure networks. However, the problem of timing and carrier frequency offset synchronization was higher for CO-OFDM systems using QNSC for network security. For higher-order modulation systems, the algorithms used to overcome this problem are offering very low accuracy. In addition to this, the chances of attack by an illegal receiver are more due to no encryption used for the preamble creation. Existing algorithms used to create a new preamble is: CNI (conjugate, negative, and image) with PN sequence and CNC (conjugate and negative) with Chu sequence. In this paper, ConvNN (Convolutional Neural Network) and CapNN (Capsule Neural Network) based joint synchronization of timing and frequency for CO-OFDM system is proposed. From the experiments, performed at 10Gbps, it has been illustrated that the proposed networks are giving more robust results. In addition to these proposed networks are offering better and secure performance for both timing and frequency offset synchronization by using less training data.

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Section: Introductionmentioning

confidence: 99%

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Kaur

2024

Opt Quant Electron

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“…At lower values of Euclidean distance, it is very di cult to get the proper timing and frequency synchronization [9]. Different synchronization methods were proposed in order to reduce the timing and frequency synchronization errors such as preamble-based synchronization algorithms (Schmidl & Cox, Minn, and Park) [10][11][12][13], constant amplitude zero autocorrelation (CAZAC) sequence [14][15], Zadoff-Chu Sequence [16], weighted-conjugate symmetric sequence [17], Park-like conjugate symmetric preamble [18][19], a constant amplitude preamble weighted by PN sequence [20], andconjugate negative image (CNI) with PN and Chu Sequence [21].…”

Section: Introductionmentioning

confidence: 99%

Neural Network (ConvNN & CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Kaur

2023

Preprint

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The Quantum Noise Stream Cipher (QNSC) is offering very high security in physical layer of optical fiber communication network to meet the today’s main requirement of secure networks. However, the problem of timing and carrier frequency offset synchronization was higher for CO-OFDM systems using QNSC for network security. For higher-order modulation systems, the algorithms used to overcome this problem are offering very low accuracy. In addition to this, the chances of attack by an illegal receiver are more due to no encryption used for the preamble creation. Existing algorithms used to create a new preamble is: CNI (conjugate, negative, and image) with PN sequence and CNC (conjugate and negative) with Chu sequence. In this paper, ConvNN (Convolutional Neural Network) and CapNN (Capsule Neural Network) based joint synchronization of timing and frequency for CO-OFDM system is proposed. From the experiments, performed at 10Gbps, it has been illustrated that the proposed networks are giving more robust results. In addition to these proposed networks are offering better and secure performance for both timing and frequency offset synchronization by using less training data.

show abstract

Robust timing and frequency joint synchronization method for QNSC-enabled security optical communications system based on CO-OFDM

Cited by 2 publications

References 14 publications

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Neural Network (ConvNN & CapNN) based joint synchronization of timing and frequency for CO-OFDM system

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Robust timing and frequency joint synchronization method for QNSC-enabled security optical communications system based on CO-OFDM

Cited by 2 publications

References 14 publications

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Neural network (ConvNN and CapNN) based joint synchronization of timing and frequency for CO-OFDM system

Neural Network (ConvNN &amp; CapNN) based joint synchronization of timing and frequency for CO-OFDM system

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Neural Network (ConvNN & CapNN) based joint synchronization of timing and frequency for CO-OFDM system