In this paper,a contention-based connection-free transmission scheme is proposed to meet the stringent requirements of ultra-reliability and low-latency for critical machine-type communication(cMTC).To improve reliability,we design multiple in-dependent sparse orthogonal pilots(MISOP)to signif-icantly reduce the probability of pilot collision to the order of 10-5.Besides,the advancements of massive MIMO(mMIMO)are exploited to further enhance the reliability.To achieve low latency,connection-free slot-based one-shot transmission without retransmis-sions is adopted.On the receiver side,single round of multi-user detection(MUD)without interference can-cellation(IC)can reduce the processing delay.The im-precise synchronization between cMTC device and the gNB in connection-free transmission,e.g.,time and frequency offsets,are also considered.The simula-tion results shows that the proposed scheme can well satisfy the ambitious requirements of cMTC,and has the potential applications in supporting massive cMTC devices in 6G.
A mobile edge computing (MEC) aided cell-free massive MIMO network is investigated in this paper that aims at optimizing the task offloading process from the wireless devices to the MEC server. Partial computation offloading strategies are designed that aim at optimizing either the aggregated latency or the energy consumption by considering the finite computational capability of the MEC server and assuming that the tasks are subject to a maximum latency constraint. The proposed optimization approach considers the joint optimization of both the per-task offloading ratio and the corresponding computational resources allocated to the tasks at the MEC server. This optimization is performed by taking into account the computing capabilities of both the wireless devices and the MEC server and both the UL and DL spectral efficiencies provided by the cell-free massive MIMO network. The proposed optimization problems are shown to be convex and, inspired by the well-known waterfilling algorithm, optimal solutions based on low-complexity iterative algorithms are devised. Extensive numerical results reveal the potential of the proposed MEC-enabled cell-free massive MIMO network.
新兴超低时延场景的出现以及6G技术与人工智能技术的发展,促使网络智能传输成为研究热点.分析了传输层和应用层的时延组成及影响因素,对机器学习技术与传输层、应用层流媒体传输相结合的智能传输协议的发展和优缺点进行了综述.从传统网络传输协议的发展、人工智能技术的发展、网络传输和人工智能结合3个方面展望了网络智能传输面临的机遇与挑战.认为分布式机器学习训练场景的传输性能、训练数据的质量、模型的泛化能力、模型大规模部署的开销是未来网络智能传输技术的重点研究方向.
In recent years, semantic communications has received wide attention from academia and industry, but a complete and effective framework of semantic information theory has not been fully established. The semantic information theory is divided into three parts: semantic entropy, semantic rate-distortion, and semantic channel capacity, and the measurement of semantic information, semantic coding and distortion, and the maximum semantic traffic are then discussed. At the same time, the related work in semantic information theory is sorted out, and some open problems with high probabilities about the future of semantic information theory are discussed. It is believed that the development of semantic communications is in its initial stage, and there are still many unsolved problems.
智能内生已成为6G网络的重要特征之一,也是当前业界关注的重点.首先解析了6G智能内生网络(IEN)的概念和特征,并对分层分面设计理念和典型架构进行了分析.之后,总结和展望了6G IEN架构的标准化进展.结合这些研究和进展,总结6G IEN面临的挑战,从知识表征与构建、意图驱动、分布式人工智能(AI)和AI可解释性4个角度分析了6G IEN的关键技术,为6G IEN架构的进一步演进提供了参考依据.
