Since 5G new radio comes with non-standalone (NSA) and standalone (SA) versions in 3GPP, research on 6G has been on schedule by academics and industries. Though 6G is supposed to have much higher ...capabilities than 5G, yet there is no clear description about what 6G is. In this article, a comprehensive discussion of 6G is given based on the review of 5G developments, covering visions and requirements, technology trends and challenges, aiming at tackling the challenge of coverage, capacity, the user data rate and movement speed of mobile communication system. The vision of 6G is to fully support the development of a Ubiquitous Intelligent Mobile Society with intelligent life and industries. Finally, the roadmap of the 6G standard is suggested for the future.
It is widely acknowledged that network slicing can tackle the diverse use cases and connectivity services of the forthcoming next-generation mobile networks (5G). Resource scheduling is of vital ...importance for improving resource-multiplexing gain among slices while meeting specific service requirements for radio access network (RAN) slicing. Unfortunately, due to the performance isolation, diversified service requirements, and network dynamics (including user mobility and channel states), resource scheduling in RAN slicing is very challenging. In this paper, we propose an intelligent resource scheduling strategy (iRSS) for 5G RAN slicing. The main idea of an iRSS is to exploit a collaborative learning framework that consists of deep learning (DL) in conjunction with reinforcement learning (RL). Specifically, DL is used to perform large time-scale resource allocation, whereas RL is used to perform online resource scheduling for tackling small time-scale network dynamics, including inaccurate prediction and unexpected network states. Depending on the amount of available historical traffic data, an iRSS can flexibly adjust the significance between the prediction and online decision modules for assisting RAN in making resource scheduling decisions. Numerical results show that the convergence of an iRSS satisfies online resource scheduling requirements and can significantly improve resource utilization while guaranteeing performance isolation between slices, compared with other benchmark algorithms.
Open access: Despite the exceptional level of sophistication in cross‐coupling chemistry, reactions of substrates that incorporate the leaving group as an integral part into a heterocyclic scaffold ...are scarce. The title reaction outlines the utility of this reaction format (see scheme; acac=acetylacetonate), provides a convenient entry into stereodefined diene carboxylates, and adds a new chapter to the field of iron catalysis.
Enol and phenol functionalities are very common in organic molecules. Utilization of these materials is very appealing in organic synthesis because they are important alternatives to organohalides in ...cross‐coupling reactions. In this review, we summarize the transition‐metal‐catalyzed cross‐coupling of enol‐ and phenol‐based electrophiles, including phosphates, sulfonates, ethers, carboxylates, and phenolates.
Coupled up! Protected enol and phenol compounds are important alternatives to organohalides in cross‐coupling reactions. The transition‐metal‐catalyzed cross‐coupling of enol‐ and phenol‐based electrophiles, including phosphates, sulfonates, ethers, carboxylates, and phenolates, have been summarized (see scheme; PG=protecting group).
The direct functionalization of C-H bonds has drawn the attention of chemists for almost a century. C-H activation has mainly been achieved through four metal-mediated pathways: oxidative addition, ...electrophilic substitution, σ-bond metathesis and metal-associated carbene/nitrene/oxo insertion. However, the identification of methods that do not require transition-metal catalysts is important because methods involving such catalysts are often expensive. Another advantage would be that the requirement to remove metallic impurities from products could be avoided, an important issue in the synthesis of pharmaceutical compounds. Here, we describe the identification of a cross-coupling between aryl iodides/bromides and the C-H bonds of arenes that is mediated solely by the presence of 1,10-phenanthroline as catalyst in the presence of KOt-Bu as a base. This apparently transition-metal-free process provides a new strategy with which to achieve direct C-H functionalization.
We consider a homogeneous cellular network where a multi-antenna base station (BS) in each cell transmits messages to its intended user over a common frequency band. To improve the system capacity of ...this multi-cell multi-input single-output (MISO) interference channel, one of the state-of-the-art algorithms, namely, downlink-beamforming coordination, allows all BSs to cooperate with one another to mitigate the effect of inter-cell interference. However, most existing algorithms are suboptimal and impractical in a dynamic wireless environment, due to the high computational complexity and the overhead involved in collecting global channel state information (CSI). In this study, we exploit deep reinforcement learning (DRL) and propose a distributed dynamic downlink-beamforming coordination (DDBC) method with partial observability of the CSI. Each BS is able to train its own deep Q-network and employs appropriate beamformer depending on its environment, which is observed through a designed limited-information exchange protocol. The simulation results show that the proposed DRL-based DDBC method, with a considerably lower system overhead, achieves a system capacity that is very close to that of the fractional programming algorithm with global and instantaneous CSI measurements. In addition, this work demonstrates the potential of utilizing DRL to solve DDBC problems in a more practical manner.
Network slicing (NS) has been widely identified as a key architectural technology for 5G-and-beyond systems by supporting divergent requirements in a sustainable way. In radio access network (RAN) ...slicing, due to the device-base station (BS)-NS three layer association relationship, device association (including access control and handoff management) becomes an essential yet challenging issue. With the increasing concerns on stringent data security and device privacy, exploiting local resources to solve device association problem while enforcing data security and device privacy becomes attractive. Fortunately, recently emerging federated learning (FL), a distributed learning paradigm with data protection, provides an effective tool to address this type of issues in mobile networks. In this paper, we propose an efficient device association scheme for RAN slicing by exploiting a hybrid FL reinforcement learning (HDRL) framework, with the aim to improve network throughput while reducing handoff cost. In our proposed framework, individual smart devices train a local machine learning model based on local data and then send the model features to the serving BS/encrypted party for aggregation, so as to efficiently reduce bandwidth consumption for learning while enforcing data privacy. Specifically, we use deep reinforcement learning to train the local model on smart devices under a hybrid FL framework, where horizontal FL is employed for parameter aggregation on BS, while vertical FL is employed for NS/BS pair selection aggregation on the encrypted party. Numerical results show that the proposed HDRL scheme can achieve significant performance gain in terms of network throughput and communication efficiency in comparison with some state-of-the-art solutions.
Although iron‐catalyzed cross‐coupling reactions of arylmagnesium halides with alkyl halides are well established and proceed effectively under a variety of experimental conditions, they often find ...limitations when working with sterically hindered aryl‐Grignard reagents. Outlined in this paper is a practical solution that allows this gap in coverage to be filled. Specifically, it is shown that bis(diethylphosphino)ethane (depe) crafts an effective coordination environment about Fe(+2). This commercially available ligand is slim enough not to interfere with the loading of the iron center even by ortho,ortho‐disubstituted arylmagnesium halides, yet capable of preventing premature reductive coupling of the resulting organoiron species, which seem to be hardly basic either. The reaction is compatible with various polar functional groups as well as with substrates containing β‐heteroatom substituents. Moreover, the procedure even allows encumbered neopentylic electrophiles to be arylated with donors as bulky as mesitylmagnesium bromide, whereas secondary alkyl halides tend to eliminate.
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