Lassaad K. Smirani1, Leila Jamel2,*, Latifah Almuqren2
CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1315-1337, 2024, DOI:10.32604/cmes.2024.047551
- 20 May 2024
Abstract This study presents a layered generalization ensemble model for next generation radio mobiles, focusing on supervised channel estimation approaches. Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout. The model, called Stacked Generalization for Channel Estimation (SGCE), aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput. The SGCE model incorporates six machine learning methods: random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LGBM), support vector regression (SVR), extremely randomized tree (ERT), and extreme gradient boosting (XGB). By generating meta-data from five… More >
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