## 2 Simulation Setup  
The simulation setup is schematically illustrated in Figure 1. Single channel transmission is considered. At the TX side, a PRBS-15 pseudorandom binary sequence is generated at bit rate \(R_{b}\) = 200 Gbps, and then coded to generate a PAM-8 sequence. As shown in Figure 1, the CD-DPC algorithm is implemented based on a finite impulse response (FIR) complex filter, which is explained in detail in [15]. The key idea behind this algorithm is the following: the fiber length \(L\) is known in advance and the accumulated CD is \(D\)-\(L\) ps/nm (where \(D\) is the dispersion coefficient). An electrical transmitted signal is sent to the FIR filter-based CD-DPC block, which works at \(m\) samples per symbol (SpS) with \(N_{t}\) taps. The CD-DPC block is placed at the TX side digital signal processing (DSP) and emulates the inverse of the CD accumulated along the link. A proper value of pre-compensated length \(L_{C}\) must be set in the CD-DPC block to design the taps of the FIR filter. As a result, an accumulated CD of \(D\)-\(L_{C}\) ps/nm is assumed to be pre-compensated. There could be a mismatch \(\Delta L\) between \(L\) and \(L_{C}\), (\(\Delta L\) = \(L_{C}-L\)), which the system should tolerate. In [14; 15; 16; 17], we demonstrated a tolerance on \(\Delta L\) of about \(\pm\)2 km in a C-band for a 100 Gbps transmission through simulations and experiments. In this paper, the CD-DPC DD works at \(m\) = 2 SpS and \(N_{t}\) = 80. The I and Q arm of the dual-arm IQ-MZM are driven by two real-valued in-phase \(I(n)\) and quadrature \(Q(n)\) signals biased at quadrature and null point, respectively. The peak-to-peak amplitude \(V_{PP}\) of signal \(I(n)\) and \(Q(n)\), i.e., \(V_{PP,I}\) and \(V_{PP,Q}\) respectively, are measured at the input of the IQ-MZM. \(V_{PP,I}\) and \(V_{PP,Q}\) must be optimized to obtain the best system performance by optimizing a scaling factor (the parameter \(k\) in Figure 1, which is the same for both \(I(n)\) and \(Q(n)\) signal). The simulator is explained in detail in [15]. The bias voltage of the IQ-MZM \(V_{\pi}\) is 5 V.  
The modulated optical signal in C-band at wavelength \(\lambda\) = 1550 nm is propagated over a conventional ITU-T G.652 single mode fiber (SMF) with length \(L\) = 20 km (typical for PON). The fiber attenuation, chromatic dispersion \(D\) and non- linear coefficient \(n_{2}\) are set to 0.22 dB/km, 17 ps/(nm\(\cdot\)km) and 26\(\times\)10\({}^{-21}\) m\({}^{2}\)/W, respectively. The effective area is 80 \(\upmu\)m\({}^{2}\)[28]. Kerr nonlinearities are introduced using the conventional nonlinear Schrodinger equation (NLSE) solved numerically by the split-step Fourier method. The received optical power (ROP) is measured after a variable optical attenuator (VOA) is used to emulate the ODN loss. Second order low-pass super Gaussian filters (SGF) are used to emulate the O/E bandwidth limitations with the same \(-\)3 dB bandwidth \(f_{3 dB}\) both at TX and RX side. We analyze the impact of transceiver bandwidth limitations varying\(f_{3 dB}\) from 30% to more than 100% of the baud rate, i.e., from 20 GHz to 70 GHz. At the RX side, an optical filter with a 75 GHz bandwidth is placed between the SOA and PIN. The receiver simulated parameters are SOA gain \(G\) = 11 dB, SOA noise figure \(NF\) = 7 dB, photodiode responsivity \(R\) = 0.7 A/W, and transimpedance amplifier (TIA) input referred noise density \(IRND\) = 12 pA/sqrt(Hz). A digital-to-analog converter (DAC) and an analog-to-digital converter (ADC) with a 6 bits resolution for quantization are used to emulate the arbitrary waveform generator (AWG) and real-time oscilloscope (RTO), respectively.