  The performance of conventional interference management strategies degrades
when interference power is comparable to signal power. We consider a new
perspective on interference management using semantic communication.
Specifically, a multi-user semantic communication system is considered on
moderate interference channels (ICs), for which a novel framework of deep
learning-based prompt-assisted semantic interference cancellation (DeepPASIC)
is proposed. Each transmitted signal is partitioned into common and private
parts. The common parts of different users are transmitted simultaneously in a
shared medium, resulting in superposition. The private part, on the other hand,
serves as a prompt to assist in canceling the interference suffered by the
common part at the semantic level. Simulation results demonstrate that the
proposed DeepPASIC outperforms conventional interference management strategies
under moderate interference conditions.
