Near-ML Detection Based on Multilevel SINR Thresholding for Mode Division Multiplexing Transmission With Mode-Dependent Loss

IEEE Access

Siyu Gong¹  Fengju Fan¹  Jianyong Zhang²  Shuchao Mi²  Baorui Yan² 

[1] Institute of Lightwave Technology, Beijing Jiaotong University, Beijing, China;Key Laboratory of All Optical Network and Advanced Telecommunication Network of EMC, Beijing Jiaotong University, Beijing, China;

关键词: Mode division multiplexing;    mode-dependent loss;    MIMO detection;    reduced search;    SINR;   

DOI  :  10.1109/ACCESS.2021.3054783

来源: DOAJ

【 摘 要 】

The probability distribution of the signal-to-interference plus noise ratio (SINR) is analyzed and approximated by the generalized gamma distribution for mode-dependent loss (MDL)-impaired fiber links. Based on the characteristics of SINR, an improved reduced-search algorithm (IRS) based on multilevel SINR thresholding (IRS-MST) is proposed. IRS-MST dynamically determines the size of the search space for each mode based on multiple SINR thresholds. Furthermore, a compounding function is used to balance the size of the search space and performance. Simulation results show that IRS-MST can achieve near ML performance for different MDLs. Compared to the conventional IRS algorithm, the complexity of IRS-MST is approximately 5.4 times smaller than that of the IRS.

【 授权许可】

Unknown