LAUSR

Space division multiplexing (SDM), as a potential means of enhancing the capacity of optical transmission systems, has attracted widespread attention. However, the adoption of SDM technology has also additionally increased resource dimensions, introduced complex crosstalk, and made it difficult to integrate multi-dimensional fragments. These factors force the transmission constraints to be more complicated. Especially, some factors have a mutual restraint relationship, and excessive consideration of certain factors will cause the deterioration of other ones. Therefore, how to comprehensively consider the associated factors to achieve trade-offs and improve network performance is a problem worthy of study. This paper exploits the advantages of self-organizing feature mapping (SOFM) model to process multi-dimensional data with relevant features. Firstly, multiple constraints will be input into SOFM as mode vectors from the core level. Then, by judging the similarity between the competition layer neuron and the pattern vector, the position of the winning neuron is located, which determines the transmission level of each core. Finally, a routing, core, and spectrum allocation scheme is proposed by preferentially locating the core with higher transmission quality. Along the selected core, the available slots will be classified twice respectively by the number of adjacent cores and crosstalk direction to quickly find the spectrum blocks with relatively small crosstalk. Results indicate the scheme can reduce blocking probability and the resource fragmentation. Further, it can increase the resource utilization within tested network load.