This paper introduces a novel approach to address the challenges of link adaptation in direct air-to-underwater optical communication systems, employing the deep deterministic policy gradient (DDPG) algorithm and the orthogonal frequency division multiplexing (OFDM) technique under noisy channel state information (CSI) conditions. The proposed method encom-passes dynamic adaptations of beam orientation, beam width, and power levels, treating these parameters as continuous variables to account for the inherent randomness in real-world scenarios. To evaluate the effectiveness of our approach, we compare the achieved success rates and consumed energy with our DDPG-based model against a Q-Iearning-based link adaptation strategy as well as two static benchmarks. Remarkably, the proposed model consistently achieved high success rates, nearly approaching 100%, while concurrently reducing energy consumption by a factor of ten compared to the Q-Iearning-based approach, all within the first 100 episodes.
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Romdhane et al. (2024) studied this question.
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