Integrating Pre-Trained Language Model with Physical Layer Communications

arXiv:2402.11656v1 Announce Type: cross
Abstract: The burgeoning field of on-device AI communication, where devices exchange information directly through embedded foundation models, such as language models (LMs), requires robust, efficient, and generalizable communication frameworks. However, integrating these frameworks with existing wireless systems and effectively managing noise and bit errors pose significant challenges. In this work, we introduce a practical on-device AI communication framework, integrated with physical layer (PHY) communication functions, demonstrated through its performance on a link-level simulator. Our framework incorporates …

abstract arxiv challenges communication communications cs.cl cs.it cs.lg devices eess.sp embedded errors foundation frameworks information language language model language models layer lms math.it noise on-device ai robust systems through type wireless