Low-complexity optimized detection with cluster assisting for C-band 64-Gb/s OOK transmission over 100-km SSMF

In this paper, a low-complexity optimized detection scheme consisting of a post filter with weight sharing (PF-WS) and cluster-assisted log-maximum a posteriori estimation (CA-Log-MAP) is proposed. Besides, a modified equal-width discrete (MEWD) clustering algorithm is proposed to eliminate the training process during clustering. After channel equalization, optimized detection schemes improve performance by suppressing the in-band noise raised by the equalizers. The proposed optimized detection scheme was experimentally performed in a C-band 64-Gb/s on-off keying (OOK) transmission system over 100-km standard single-mode fiber (SSMF) transmission. Compared with the optimized detection scheme with the lowest complexity, the proposed method saves 69.23% required number of real-valued multiplications per symbol (RNRM) at 7% hard-decision forward error correction (HD-FEC). In addition, when the detection performance reaches saturation, the proposed CA-Log-MAP with MEWD saves 82.93% RNRM. Compared with the classic k-means clustering algorithm, the proposed MEWD has the same performance without a training process. To the best of our knowledge, this is the first time clustering algorithms have been applied to optimize decision schemes.