Gerchberg-Saxton Based Finite Impulse Response Filter for Electronic Dispersion Compensation in IM/DD Transmission: Experimental Demonstration

Abstract

<p>In this article, the first experimental demonstration of a non-iterative electronic dispersion compensation (EDC) solution implemented at the transmitter using a finite impulse response (FIR) filter optimized with the Gerchberg-Saxton (GS) algorithm, is presented, for intensity-modulation and direct-detection (IM/DD) systems. The performance of the GS-based FIR filter is compared to the performance of the standard iterative GS algorithm in the transmission of a 56-Gb/s on-off keying (OOK) signal over 80 km of single mode fiber (SMF) with a chirp-free single drive Mach-Zehnder modulator (MZM). The transmitter employed a <em>T</em>/2-spaced <em>N</em>-tap GS based FIR filter with an 8-bit finite-precision arithmetic, while the receiver employed a <em>J</em>-tap adaptive <em>T</em>-spaced or <em>T</em>/2-spaced feed-forward equalizer (FFE) for combating residual inter-symbol interference (ISI). Furthermore, the influence of the pulse shape and modulation format on the measured bit error ratio (BER) is experimentally investigated, while changing the number of FIR taps <em>N</em>, the number of post-FFE taps <em>J</em> and the number of post-FFE samples-per-symbol <em>sps</em><sub><em>Rx</em></sub>. The pulse shapes and modulation formats considered in this work are: raised-cosine (RC) non-return-to-zero (NRZ), rectangular NRZ and rectangular return-to-zero (RZ). It is shown that within the range of target digital extinction ratio (DER) for which the original iterative GS algorithm offers benefit, both methods for calculating the optimum FIR taps, outlined in Part I of this work, produce similar BER performance as predicted theoretically. Furthermore, the measured BER, using rectangular RZ with a 641-tap <em>T</em>/2-spaced static FIR filter at the transmitter and a 3-tap adaptive <em>T</em>-spaced post-FFE at the receiver, is below the 7% hard-decision (HD) forward error correction (FEC) limit of 3.8x10<sup>-3</sup>.</p>

Electronic dispersion compensation and functional link neural network equalization for IM/DD links

“…Recently, the iterative GS algorithm was used in designing a finite impulse response filter (FIR) at the transmitter for mitigating power fading ISI. The theoretical details of the GS-FIR filter is reported in [11], while the first experimental demonstration of such filter is reported in [12]. Although significant complexity reducing can be achieved using the noniterative static GS-FIR in comparison to the original iterative GS algorithm, the performance of the former is lower than that of the latter, as only the linear power fading ISI is addressed, while nonlinear ISI is untreated.…”

“…In this letter, a functional link neural network (FLNN) is proposed for EDC at the receiver with two primary objectives: (i) estimating the benefit of Tx-end pre-EDC with both iterative and FIR approaches, and (ii) partial mitigation of nonlinear ISI in addition to the linear ISI already addressed using the GS-FIR in [11], [12]. We demonstrate that the FLNN is uniquely positioned to meet these objectives as it allows for both linear equalization and the nonlinear expansion of the input samples using a functional expansion block (FEB) with orthogonal basis functions [13].…”