具有少量候选消息的语义通信系统的信号整形
Signal Shaping for Semantic Communication Systems with A Few Message Candidates
摘要：
语义通信的目标是可靠地传达消息的语义含义。它与现有的专注于可靠比特传输的通信系统不同。为了实现语义通信的目标，我们提出了一种信号整形方法，通过最大限度地减少语义损失，这是衡量从变压器（BERT）模型的预训练的双向编码器表示。研究了语义通信系统中具有少量候选消息的信号集优化问题。我们提出了一个有效的投影梯度下降方法来解决这个问题，并证明了它的收敛性。仿真结果表明，该方法在最小化语义损失方面优于现有的信号整形方法。
英文摘要：
Semantic communications target to reliably convey the semantic meaning of messages. It is different from existing communication systems focusing on reliable bit transmission. To achieve the goal of semantic communications, we propose a signal shaping method by minimizing the semantic loss, which is measured by the pretrained bidirectional encoder representation from transformers (BERT) model. The signal set optimization problem for semantic communication systems with a few message candidates is investigated. We propose an efficient projected gradient descent method to solve the problem and prove its convergence. Simulation results show that the proposed method outperforms existing signal shaping methods in minimizing the semantic loss.
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