Signal equalization and coding techniques in ultra-high-speed short-reach optical interconnect

Against the backdrop of the vigorous development of artificial intelligence (AI) large models, the demand for the data center optical module rate continues to rise. To meet the requirements of high rate, low power consumption, low latency, and high integration for ultra-high-speed short-reach optical interconnect, the development trend of the optical module industry was introduced, and relevant equalization and coding technologies were discussed. In terms of equalization technology, a low-complexity Volterra equalization method based on the least angle regression strategy (LaNLE) and a deep neural network equalization method based on hidden feature extraction (HFE) were proposed. Under the 120 Gbit/s PAM-8 signal transmission, the complexity of LaNLE was reduced by 70.1% compared with traditional methods at the same bit error rate; HFE improved the neural network training efficiency and achieved 288 Gbit/s PAM-8 signal transmission. In terms of coding technology, the optimization method of QC-LDPC codes in the optical interconnection system and the LDPC joint equalization and decoding method based on deep learning were introduced. Experimental results show that the proposed methods can effectively optimize the bit error rate and improve the system performance. At the same time, the future research directions were prospected.