Predictive Semantic-Aware Hybrid Automatic Repeat Request for Reliable and Efficient 6G Communications

Hybrid automatic repeat request (HARQ) remains the backbone of link-layer reliability, yet it was designed for a setting in which every bit matters equally and the channel of the next slot is unknown. Neither assumption holds in semantic communication over time-varying channels: some parts of a message are decisive for the receiver’s task while others are not, and the deep fade that destroyed a first transmission is usually still present when an immediate retransmission arrives. This article proposes predictive semantic-aware HARQ (PSA-HARQ), a retransmission framework that makes its decisions at the level of individual semantic units and bases them jointly on how much each unit matters and on how the channel is expected to evolve. Semantic importance is extracted from a Transformer semantic encoder, a lightweight recurrent predictor forecasts the channel a few slots ahead, and a finite-horizon optimal-stopping controller decides, for every unit and every slot, whether to transmit, wait for a better slot, or abandon the unit. The forecast enters the controller through a confidence-weighted estimator whose weight is tracked at run time from the observed prediction errors, so that the policy falls back to the statistics-only optimum whenever the predictor becomes uninformative. Simulations over a vehicular situational-awareness task and over a real public record-classification dataset, with finite-blocklength coding and time-correlated Rayleigh fading, show that PSA-HARQ matches or exceeds the task accuracy of conventional HARQ in the low-SNR regime where retransmissions are most frequent, while transmitting far fewer blocks and consuming far less energy at the same channel condition. A cost-matched ablation shows that semantic importance and channel prediction contribute complementary gains. The results indicate that anticipating the channel, rather than merely reacting to it, is a practical and largely untapped lever for reliable and efficient 6G semantic communication.