Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable communications. In this approach, bits are treated equally, and the communication system is oblivious to what meaning these bits convey or how they would be used. Future communications towards intelligence and conciseness will predictably play a dominant role, and the proliferation of connected intelligent agents requires a radical rethinking of coded transmission paradigm to support the new communication morphology on the horizon. The recent concept of "semantic communications" offers a promising research direction. Injecting semantic guidance into the coded transmission design to achieve semantics-aware communications shows great potential for further breakthrough in effectiveness and reliability. This article sheds light on semantics-guided source and channel coding as a transmission paradigm of semantic communications, which exploits both data semantics diversity and wireless channel diversity together to boost the whole system performance. We present the general system architecture and key techniques, and indicate some open issues on this topic.
翻译:古老的通信模式侧重于在一个吵闹的频道上准确传输比特,香农理论为可靠的通信速度提供了基本的理论限制。在这一方法中,对比特的处理是平等的,通信系统忽视了这些比特表达的含义或如何使用这些比特。 未来对智能和简洁的通信将可预见地发挥主导作用,而连通智能剂的扩散要求对编码传输模式进行彻底的重新思考,以支持地平线上新的通信形态。 最近的“语义通信”概念提供了一个有希望的研究方向。 将语义指导输入编码传输设计中,以实现语义认知通信,这显示了在有效性和可靠性方面进一步突破的巨大潜力。 文章揭示了语义学引导源和频道连接作为语义通信传输模式的光亮度,它利用数据语义多样性和无线频道多样性共同推动整个系统的业绩。 我们介绍了一般系统架构和关键技术,并指明了这方面的一些开放问题。