Weighted finite impulse response filter for chromatic dispersion equalization in coherent optical fiber communication systems

Abstract

Time-domain chromatic dispersion (CD) equalization using finite impulse response (FIR) filter is now a common approach for coherent optical fiber communication systems. The complex weights of FIR filter taps are calculated from a truncated impulse response of the CD transfer function, and the modulus of the complex weights is constant. In our work, we take the limited bandwidth of a single channel signal into account and propose weighted FIR filters to improve the performance of CD equalization. A raised cosine FIR filter and a Gaussian FIR filter are investigated in our work. The optimization of raised cosine FIR filter and Gaussian FIR filter are made in terms of the EVM of QPSK, 16QAM and 32QAM coherent detection signal. The results demonstrate that the optimized parameters of the weighted filters are independent of the modulation format, symbol rate and the length of transmission fiber. With the optimized weighted FIR filters, the EVM of CD equalization signal is decreased significantly. The principle of weighted FIR filter can also be extended to other symmetric functions as weighted functions.OCIS codes: (060.4510) Optical communications; (230.3670) optical fiber；(040.5160) chromatic dispersion.

Design and Development of GUI for the Mitigation of Chromatic Dispersion: A New Approach

“…This produces losses in the signal and performance is further degraded. In this work, the chromatic dispersion is mitigated in the electric way, which is far better compare to existing techniques [12] for low dispersion system. The chromatic dispersion is taken in account from (1) and it is defined that chromatic dispersion is calculated as in (2) by abandoning the nonlinear effects from the transmission because no pump signal is used and there was no spikes in the signal recorded [13]:…”

“…In this work, the Raised Cosine Filter improves the shape of pulse. The filter is designed and constructed via (10) [12]:…”

“…The error rate depends on signal to noise ratio determined by Q factor. BER was calculated via (12) [13]: (12) As the Q or Quality factor is increased BER decreased and it is defined that by mitigating the chromatic dispersion, the Qfactor is increased and BER Furthermore, the performance is setup via Eye diagram. It gives visual of signal in the shape of an eye to asses maximum transmission rate of a system, it is related to BER as the chromatic dispersion is more the eye will be close and if chromatic dispersion mitigation is archived the eye will be open [27][28].…”

“…Not only this, the GUI also gives the information about BER that was calculated via (12) along with eye diagram. These all measurements defines that signal has the chromatic dispersion during the transmission and via developing the GUI it easily describe the response of all optical communication under one system.…”

“…Chromatic Dispersion (CD) is key parameter that is considered well when designing the optical communication [11]. The more CD in the signal will increase the Inter Symbol Interference (ISI) that will cause increase in error in transmissions [12]. In result, more bit are corrupted and system performance is highly degraded.…”