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Moreover, it has been considered that a second UAV interferes with the intended UAV. The operation of the UAVs has been represented considering the small scale fading, path loss, 3\u2010D location, and probability of maintaining line\u2010of\u2010sight (LoS) and non line of sight (NLoS) links, while FSO link undergoes Malaga distributed turbulence. Using the aforementioned model, the closed form expressions for the outage probability and bit error rate (BER) have been derived. The exact expressions have been extended to obtain the high signal\u2010to\u2010noise ratio (SNR) results for the outage probability and BER. The analytical expressions have been numerically evaluated and the results obtained through these expressions have been verified using the Monte Carlo simulations. More importantly, long short\u2010term memory (LSTM)\u2010based deep learning model has been trained for prediction of outage probability. The model is trained offline and then utilized to predict the values of the outage probability in online mode with mean square error (MSE) and root mean square error (RMSE) of <jats:italic>MSE<\/jats:italic>\u2009=\u2009\u221245.02 and <jats:italic>RMSE<\/jats:italic>\u2009=\u2009\u221218.34\u2009dB.<\/jats:p>","DOI":"10.1002\/dac.5881","type":"journal-article","created":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T23:44:27Z","timestamp":1719359067000},"update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Practical downlink satellite\u2010FSO\/RF cooperative relays: Performance analysis and LSTM prediction"],"prefix":"10.1002","volume":"37","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-4069-8576","authenticated-orcid":false,"given":"Anu","family":"Goel","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication 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