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Register a new userJoint timing and frequency synchronization based on weighted CAZAC sequences for reduced-guard-interval CO-OFDM systems
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Added by
Oluyemi Omomukuyo
Publication date
2018
fields
Electronic Engineering
and research's language is
English
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A novel joint symbol timing and carrier frequency offset (CFO) estimation algorithm is proposed for reduced-guard-interval coherent optical orthogonal frequency-division multiplexing (RGI-CO-OFDM) systems. The proposed algorithm is based on a constant amplitude zero autocorrelation (CAZAC) sequence weighted by a pseudo-random noise (PN) sequence. The symbol timing is accomplished by using only one training symbol of two identical halves, with the weighting applied to the second half. The special structure of the training symbol is also utilized in estimating the CFO. The performance of the proposed algorithm is demonstrated by means of numerical simulations in a 115.8-Gb/s 16-QAM RGI-CO-OFDM system.
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A simple data-aided scheme for sampling clock synchronisation in reduced-guard-interval coherent optical orthogonal frequency division multiplexing (RGI-CO-OFDM) systems is proposed. In the proposed scheme, the sampling clock offset (SCO) is estimated by using the training symbols reserved for channel estimation, thus avoiding extra training overhead. The SCO is then compensated by resampling, using a time-domain interpolation filter. The feasibility of the proposed scheme is demonstrated by means of numerical simulations in a 32-Gbaud 16-QAM dual-polarisation RGI-CO-OFDM system.
We propose an algorithm for carrying out joint frame and frequency synchronization in reduced-guard-interval coherent optical orthogonal frequency division multiplexing (RGI-CO-OFDM) systems. The synchronization is achieved by using the same training symbols (TS) employed for training-aided channel estimation (TA-CE), thereby avoiding additional training overhead. The proposed algorithm is designed for polarization division multiplexing (PDM) RGI-CO-OFDM systems that use the Alamouti-type polarization-time coding for TA-CE. Due to their optimal TA-CE performance, Golay complementary sequences have been used as the TS in the proposed algorithm. The frame synchronization is accomplished by exploiting the cross-correlation between the received TS from the two orthogonal polarizations. The arrangement of the TS is also used to estimate the carrier frequency offset. Simulation results of a PDM RGI-CO-OFDM system operating at 238.1 Gb/s data rate (197.6-Gb/s after coding), with a total overhead of 9.2% (31.6% after coding), show that the proposed scheme has accurate synchronization, and is robust to linear fiber impairments.
Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is a key technology component in the evolution towards next-generation communication in which the accuracy of timing and frequency synchronization significantly impacts the overall system performance. In this paper, we propose a novel scheme leveraging extreme learning machine (ELM) to achieve high-precision timing and frequency synchronization. Specifically, two ELMs are incorporated into a traditional MIMO-OFDM system to estimate both the residual symbol timing offset (RSTO) and the residual carrier frequency offset (RCFO). The simulation results show that the performance of an ELM-based synchronization scheme is superior to the traditional method under both additive white Gaussian noise (AWGN) and frequency selective fading channels. Finally, the proposed method is robust in terms of choice of channel parameters (e.g., number of paths) and also in terms of generalization ability from a machine learning standpoint.
Due to the nonlinear distortion in Orthogonal frequency division multiplexing (OFDM) systems, the timing synchronization (TS) performance is inevitably degraded at the receiver. To relieve this issue, an extreme learning machine (ELM)-based network with a novel learning label is proposed to the TS of OFDM system in our work and increases the possibility of symbol timing offset (STO) estimation residing in inter-symbol interference (ISI)-free region. Especially, by exploiting the prior information of the ISI-free region, two types of learning labels are developed to facilitate the ELM-based TS network. With designed learning labels, a timing-processing by classic TS scheme is first executed to capture the coarse timing metric (TM) and then followed by an ELM network to refine the TM. According to experiments and analysis, our scheme shows its effectiveness in the improvement of TS performance and reveals its generalization performance in different training and testing channel scenarios.
A joint frame and carrier frequency synchronization algorithm for coherent optical systems, based on the digital computation of the fractional Fourier transform (FRFT), is proposed. The algorithm utilizes the characteristics of energy centralization of chirp signals in the FRFT domain, together with the time and phase shift properties of the FRFT. Chirp signals are used to construct a training sequence (TS), and fractional cross-correlation is employed to define a detection metric for the TS, from which a set of equations can be obtained. Estimates of both the timing offset and carrier frequency offset (CFO) are obtained by solving these equations. This TS is later employed in a phase-dependent decision-directed least-mean square algorithm for adaptive equalization. Simulation results of a 32-Gbaud coherent polarization division multiplexed Nyquist system show that the proposed scheme has a wide CFO estimation range and accurate synchronization performance even in poor optical signal-to-noise ratio conditions.
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