Intensity modulation/direct detection (IM/DD) optical interconnect systems are susceptible to waveform distortion caused by complex nonlinearities. To reduce the effect of waveform distortion on signal transmission accuracy, in this paper, a random forest (RF) equalization algorithm based on decision tree (DT) integration is proposed for cost-sensitive IM/DD systems, which has the characteristics of nonlinear classification and regression. The performance of the RF equalizer is verified by simulation experiments on a 120 Gbps 8-level pulse amplitude modulation (PAM8) transmission system using an electro-absorption-modulated laser (EML). Simulation studies show that whether it is a back-to-back (B2B) transmission system or a 10 km optical fiber transmission system, the RF equalization scheme can achieve much better bit error rate (BER) performance than the traditional equalization scheme. In addition, in both transmission cases, the RF equalization scheme enables efficient classification of signals and is much less simpler than the artificial neural network (ANN) equalization scheme.

强度调制/直接检测（IM/DD）光学互连系统容易受到复杂非线性引起的波形失真的影响。为了减少波形失真对信号传输精度的影响，针对成本敏感的IM/DD系统，提出一种基于决策树（DT）集成的随机森林（RF）均衡算法，该算法具有非线性分类的特点和回归。通过使用电吸收调制激光器（EML）的 120 Gbps 8 级脉冲幅度调制（PAM8）传输系统的仿真实验验证了射频均衡器的性能。仿真研究表明，无论是背靠背（B2B）传输系统还是10 km光纤传输系统，射频均衡方案都能获得比传统均衡方案更好的误码率（BER）性能。此外，在两种传输情况下，RF均衡方案都能够实现信号的有效分类，并且比人工神经网络（ANN）均衡方案简单得多。