Bita na JLT Sadarwa takardan gani, Janairu 2022. Part 1

Sadarwar fiber na gani
Irene Estebanez et al. daga Cibiyar Nazarin Kimiyyar Kimiyya da Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwararren Ƙwallon Ƙwallon Ƙwallon Ƙwallon Ƙwallon Ƙasa ta Spain ta yi amfani da na'ura mai mahimmanci na Learning Machine (ELM) don dawo da bayanan da aka karɓa na tsarin watsa fiber na gani, kamar yadda aka nuna a cikin Hoto 1. Ana gudanar da bincike na gwaji a cikin 100km tsarin watsa fiber na gani ta amfani da 56GBand Matsayi huɗu na bugun jini amplitude daidaitawa (PAM-4) da gano kai tsaye. Masu bincike sun gabatar da algorithm na jinkiri (TDRC) a matsayin tsarin kwatanta, kuma sun tabbatar da cewa ɗaukar ELM algorithm na iya ƙara sauƙaƙe tsarin tsarin, kawar da iyakancewar tasirin lissafin da ke haifar da jinkirin lokaci, kuma suna da kusan aikin transceiving iri ɗaya kamar ɗaukar tsarin TDRC [1] ]. Tsarin yana goyan bayan ƙaddamarwa mara kuskure lokacin da siginar siginar-zuwa-amo rabo (OSNR) ya fi 31dB, kuma yana da mafi kyawun aikin kuskure fiye da tsarin karɓar KK wanda aka aiwatar ta hanyar sarrafa siginar dijital ta layi (DSP).