[简介] 目前的语义通信研究尚未阐明语义编码与经典信道编码之间的关系、语义编码在现有通信框架中的可行性，以及影响语义编码的关键因素等。文章对基于联合信源信道编码的语义通信系统进行了理论分析，设计了语义编码与经典信道编码的融合实验，展示了语义编码的潜在优势，并探索了语义编码与经典信道编码之间的关系。

[简介]为更好地发展下一代移动通信技术，加快5G/6G建设，需将发力点由“面向企业”的2B（To Business）向“为了企业”的4B（For Business）转变。从2B到4B，是从供给侧主导向需求侧主导的转变，是从“供给外生赋能”向“供需内生协同”本质的转变。应由垂直行业主导公专网应用的标准制定与生态建设，从顶层设计开始，将数字技术融入到垂直行业数字化转型之中，实现5G/6G公专网发展从2B到4B的转变。

[Introduction] Integrated sensing and communication (ISAC) technology is a promising candidate for next-generation communication systems. However, severe co-site interference in existing ISAC systems limits the communication and sensing performance, posing significant challenges for ISAC interference management. In this work, we propose a novel interference management scheme based on the normalized least mean square (NLMS) algorithm, which mitigates the impact of co-site interference by reconstructing the interference from the local transmitter and canceling it from the received signal. Simulation results demonstrate that, compared to typical adaptive interference management schemes based on recursive least square (RLS) and stochastic gradient descent (SGD) algorithms, the proposed NLMS algorithm effectively cancels co-site interference and achieves a good balance between computational complexity and convergence performance.

[Introduction]As the wireless communication network undergoes continuous expansion, the challenges associated with network management and optimization are becoming increasingly complex. To address these challenges, the emerging artificial intelligence (AI) and machine learning (ML) technologies have been introduced as a powerful solution. They empower wireless networks to operate autonomously, predictively, on-demand, and with smart functionality, offering a promising resolution to intricate optimization problems. This paper aims to delve into the prevalent applications of AI/ML technologies in the optimization of wireless networks. The paper not only provides insights into the current landscape but also outlines our vision for the future and considerations regarding the development of an intelligent 6G network.