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| 1 | Service-aware 6G:An intelligent and open network based on the convergence of communication,computing and caching显示文摘With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular networks(5G).The future sixth generation of mobile cellular networks(6G)is expected to have the capability to support new and unknown services with changing requirements.Hence,in addition to enhancing its capability by 10–100 times compared with 5G,6G should also be intelligent and open to adapt to the ever-changing services in the IoT,which requires a convergence of Communication,Computing and Caching(3C).Based on the analysis of the requirements of new services for 6G,this paper identifies key enabling technologies for an intelligent and open 6G network,all featured with 3C convergence.These technologies cover fundamental and emerging topics,including 3C-based spectrum management,radio channel construction,delay-aware transmission,wireless distributed computing,and network self-evolution.From the detailed analysis of these 3C-based technologies presented in this paper,we can see that although they are promising to enable an intelligent and open 6G,more efforts are needed to realize the expected 6G network. | Yiqing Zhou Ling Liu Lu Wang Ning Hui Xinyu Cui Jie Wu Yan Peng Yanli Qi Chengwen Xing | 2020 | Digital Communications and Networks2020，6，3： | 57 |
| 2 | Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing显示文摘The rapid growth of mobile internet services has yielded a variety of computation-intensive applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which enables mobile terminals to offload computation tasks to servers located at the edge of the cellular networks, has been considered as an efficient approach to relieve the heavy computational burdens and realize an efficient computation offloading. Driven by the consequent requirement for proper resource allocations for computation offloading via MEC, in this paper, we propose a Deep-Q Network (DQN) based task offloading and resource allocation algorithm for the MEC. Specifically, we consider a MEC system in which every mobile terminal has multiple tasks offloaded to the edge server and design a joint task offloading decision and bandwidth allocation optimization to minimize the overall offloading cost in terms of energy cost, computation cost, and delay cost. Although the proposed optimization problem is a mixed integer nonlinear programming in nature, we exploit an emerging DQN technique to solve it. Extensive numerical results show that our proposed DQN-based approach can achieve the near-optimal performance。 | Liang Huang Xu Feng Cheng Zhang Liping Qian Yuan Wu | 2019 | Digital Communications and Networks2019，5，1： | 25 |
| 3 | Visible light communication: applications, architecture, standardization and research challenges显示文摘 | Latif Ullah Khan | 2017 | Digital Communications and Networks2017，3，2： | 18 |
| 4 | A network security situation prediction model based on wavelet neural network with optimized parameters显示文摘 | Haibo Zhang Qing Huang Fangwei Li Jiang Zhu | 2016 | Digital Communications and Networks2016，2，3： | 15 |
| 5 | Performance analysis and comparison of PoW,PoS and DAG based blockchains显示文摘In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application.To this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure probability.The results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load conditions.In addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions. | Bin Cao Zhenghui Zhang Daquan Feng Shengli Zhang Lei Zhang Mugen Peng Yun Li | 2020 | Digital Communications and Networks2020，6，4： | 15 |
| 6 | Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems显示文摘Mobile Edge Computing(MEC)is one of the most promising techniques for next-generation wireless communication systems.In this paper,we study the problem of dynamic caching,computation offloading,and resource allocation in cache-assisted multi-user MEC systems with stochastic task arrivals.There are multiple computationally intensive tasks in the system,and each Mobile User(MU)needs to execute a task either locally or remotely in one or more MEC servers by offloading the task data.Popular tasks can be cached in MEC servers to avoid duplicates in offloading.The cached contents can be either obtained through user offloading,fetched from a remote cloud,or fetched from another MEC server.The objective is to minimize the long-term average of a cost function,which is defined as a weighted sum of energy consumption,delay,and cache contents’fetching costs.The weighting coefficients associated with the different metrics in the objective function can be adjusted to balance the tradeoff among them.The optimum design is performed with respect to four decision parameters:whether to cache a given task,whether to offload a given uncached task,how much transmission power should be used during offloading,and how much MEC resources to be allocated for executing a task.We propose to solve the problems by developing a dynamic scheduling policy based on Deep Reinforcement Learning(DRL)with the Deep Deterministic Policy Gradient(DDPG)method.A new decentralized DDPG algorithm is developed to obtain the optimum designs for multi-cell MEC systems by leveraging on the cooperations among neighboring MEC servers.Simulation results demonstrate that the proposed algorithm outperforms other existing strategies,such as Deep Q-Network(DQN). | Samrat Nath Jingxian Wu | 2020 | Intelligent and Converged Networks2020，1，2： | 13 |
| 7 | Edge computing technologies for Internet of Things: a primer显示文摘 | Yuan Ai Mugen Peng Kecheng Zhang | 2018 | Digital Communications and Networks2018，4，2： | 11 |
| 8 | Wireless sensor networks: a survey显示文摘 | I.F. Akyildiz W. Su Y. Sankarasubramaniam E. Cayirci | 2002 | Computer Networks2002，，4： | 10 |
| 9 | 3D depth image analysis for indoor fall detection of elderly people显示文摘 | Lei Yang Yanyun Ren Wenqiang Zhang | 2016 | Digital Communications and Networks2016，2，1： | 10 |
| 10 | A blockchain future for internet of things security: a position paper显示文摘 | Mandrita Banerjee Junghee Lee Kim-Kwang Raymond Choo | 2018 | Digital Communications and Networks2018，4，3： | 10 |
| 11 | Reconfigurable intelligent surfaces for wireless communications:Overview of hardware designs,channel models,and estimation techniques显示文摘The demanding objectives for the future sixth generation(6G)of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity,as well as revolutionary communication and computing paradigms.Among the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces(RISs),which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of functionalities.Incorporating RISs in wireless networks have been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one,intended for various networking objectives,such as coverage extension and capacity boosting,spatiotemporal focusing with benefits in energy efficiency and secrecy,and low electromagnetic field exposure.Motivated by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments,in this paper,we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal propagation.We also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems,which constitute a prerequisite step for the optimized incorporation of RISs in future wireless networks.Finally,we discuss the relevance of the RIS technology in the latest wireless communication standards,and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches. | Mengnan Jian George C.Alexandropoulos Ertugrul Basar Chongwen Huang Ruiqi Liu Yuanwei Liu Chau Yuen | 2022 | Intelligent and Converged Networks2022，3，1： | 9 |
| 12 | Machine leaming for internet of things data analysis: a survey显示文摘 | Mohammad Saeid Mahdavinejad Mohammadreza Rezvan Mohammadamin Barekatain Peyman Adibi Payam Barnaghi Amit P. Sheth | 2018 | Digital Communications and Networks2018，4，3： | 9 |
| 13 | Wavelet networks for reducing the envelope fluctuations in WirelessMan-OFDM systems显示文摘 | Radouanelqdour Younes Jabrane | 2016 | Digital Communications and Networks2016，2，2： | 8 |
| 14 | An intelligent self-sustained RAN slicing framework for diverse service provisioning in 5G-beyond and 6G networks显示文摘Network slicing is a key technology to support the concurrent provisioning of heterogeneous Quality of Service(QoS)in the 5th Generation(5G)-beyond and the 6th Generation(6G)networks.However,effective slicing of Radio Access Network(RAN)is very challenging due to the diverse QoS requirements and dynamic conditions in the 6G networks.In this paper,we propose a self-sustained RAN slicing framework,which integrates the self-management of network resources with multiple granularities,the self-optimization of slicing control performance,and self-learning together to achieve an adaptive control strategy under unforeseen network conditions.The proposed RAN slicing framework is hierarchically structured,which decomposes the RAN slicing control into three levels,i.e.,network-level slicing,next generation NodeB(gNodeB)-level slicing,and packet scheduling level slicing.At the network level,network resources are assigned to each gNodeB at a large timescale with coarse resource granularity.At the gNodeB-level,each gNodeB adjusts the configuration of each slice in the cell at the large timescale.At the packet scheduling level,each gNodeB allocates radio resource allocation among users in each network slice at a small timescale.Furthermore,we utilize the transfer learning approach to enable the transition from a model-based control to an autonomic and self-learning RAN slicing control.With the proposed RAN slicing framework,the QoS performance of emerging services is expected to be dramatically enhanced. | Jie Mei Xianbin Wang Kan Zheng | 2020 | Intelligent and Converged Networks2020，1，3： | 8 |
| 15 | The anatomy of a large-scale hypertextual Web search engine显示文摘 | Sergey Brin Lawrence Page | 1998 | Computer Networks and ISDN Systems1998，，1： | 7 |
| 16 | A survey of 5G technologies: regulatory, standardization and industrial perspectives显示文摘 | Antonio Morgado Kazi Mohammed Saidul Huq Shahid Mumtaz Jonathan Rodriguez | 2018 | Digital Communications and Networks2018，4，2： | 7 |
| 17 | Research and application of wireless sensor network technology in power transmission and distribution system显示文摘Power is an important part of the energy industry,relating to national economy and people’s livelihood,and it is of great significance to ensure the security and stability in operation of power transmission and distribution system.Based on Wireless Sensor Network technology(WSN)and combined with the monitoring and operating requirements of power transmission and distribution system,this paper puts forward an application system for monitoring,inspection,security,and interactive service of layered power transmission and distribution system.Furthermore,this paper demonstrates the system verification projects in Wuxi,Jiangsu Province and Lianxiangyuan Community in Beijing,which have been widely used nationwide. | Jianming Liu Ziyan Zhao Jerry Ji Miaolong Hu | 2020 | Intelligent and Converged Networks2020，1，2： | 7 |
| 18 | The Internet of Things: A survey显示文摘 | Luigi Atzori Antonio Iera Giacomo Morabito | 2010 | Computer Networks2010，，15： | 6 |
| 19 | Bilayer expurgated LDPC codes with uncoded relaying显示文摘 | Md. Noor-A-Rahim Nan Zhang Sk. Md. Rabiul Islam Y.L. Guan | 2017 | Digital Communications and Networks2017，3，3： | 6 |
| 20 | Recent advances in mobile edge computing and content caching显示文摘The demand for digital media services is increasing as the number of wireless subscriptions is growing exponentially.In order to meet this growing need,mobile wireless networks have been advanced at a tremendous pace over recent days.However,the centralized architecture of existing mobile networks,with limited capacity and range of bandwidth of the radio access network and low bandwidth back-haul network,can not handle the exponentially increasing mobile traffic.Recently,we have seen the growth of new mechanisms of data caching and delivery methods through intermediate caching servers.In this paper,we present a survey on recent advances in mobile edge computing and content caching,including caching insertion and expulsion policies,the behavior of the caching system,and caching optimization based on wireless networks.Some of the important open challenges in mobile edge computing with content caching are identified and discussed.We have also compared edge,fog and cloud computing in terms of delay.Readers of this paper will get a thorough understanding of recent advances in mobile edge computing and content caching in mobile wireless networks. | Sunitha Safavat Naveen Naik Sapavath Danda B.Rawat | 2020 | Digital Communications and Networks2020，6，2： | 6 |
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