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| 1 | 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 |
| 2 | 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 |
| 3 | 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 |
| 4 | 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 |
| 5 | Deep reinforcement learning based computation offloading and resource allocation for low-latency fog radio access networks显示文摘Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing.However,the current contributions in computation offloading and resource allocation are inefficient;moreover,they merely consider the static communication mode,and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs.A joint problem of mode selection,resource allocation,and power allocation is formulated to minimize latency under various constraints.We propose a Deep Reinforcement Learning(DRL)based joint computation offloading and resource allocation scheme that achieves a suboptimal solution in F-RANs.The core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or offload the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving tier.Simulation results show that the proposed approach significantly minimizes latency and increases throughput in the system. | G.M.Shafiqur Rahman Tian Dang Manzoor Ahmed | 2020 | Intelligent and Converged Networks2020，1，3： | 5 |
| 6 | Space-air-ground integrated vehicular network for connected and automated vehicles:Challenges and solutions显示文摘Unlimited and seamless coverage as well as ultra-reliable and low-latency communications are vital for connected vehicles,in particular for new use cases like autonomous driving and vehicle platooning.In this paper,we propose a novel Space-Air-Ground integrated vehicular network(SAGiven)architecture to gracefully integrate the multi-dimensional and multi-scale context-information and network resources from satellites,High-Altitude Platform stations(HAPs),low-altitude Unmanned Aerial Vehicles(UAVs),and terrestrial cellular communication systems.One of the key features of the SAGiven is the reconfigurability of heterogeneous network functions as well as network resources.We first give a comprehensive review of the key challenges of this new architecture and then provide some up-to-date solutions on those challenges.Specifically,the solutions will cover the following topics:(1)space-air-ground integrated network reconfiguration under dynamic space resources constraints;(2)multi-dimensional sensing and efficient integration of multi-dimensional context information;(3)real-time,reliable,and secure communications among vehicles and between vehicles and the SAGiven platform;and(4)a holistic integration and demonstration of the SAGiven.Finally,it is concluded that the SAGiven can play a key role in future autonomous driving and Internet-of-Vehicles applications. | Zhisheng Niu Xuemin S.Shen Qinyu Zhang Yuliang Tang | 2020 | Intelligent and Converged Networks2020，1，2： | 4 |
| 7 | Backscatter t echnologies and the future of Internet of Things:Challenges and opportunities显示文摘Energy source and circuit cost are two critical challenges for the future development of the Internet of Things(IoT).Backscatter communications offer a potential solution to conveniently obtain power and reduce cost for sensors in IoT,and researchers are paying close attention to the technology.Backscatter technology originated from the Second World War and has been widely applied in the logistics domain.Recently,both the academic and industrial worlds are proposing a series of new types of backscatter technologies for communications and IoT.In this paper,we review the history of both IoT and backscatter,describe the new types of backscatter,demonstrate their applications,and discuss the open challenges. | Chaochao Yao Yang Liu Xusheng Wei Gongpu Wang Feifei Gao | 2020 | Intelligent and Converged Networks2020，1，2： | 4 |
| 8 | Artificial intelligence for satellite communication: A review显示文摘Satellite communication offers the prospect of service continuity over uncovered and under-covered areas,service ubiquity,and service scalability.However,several challenges must first be addressed to realize these benefits,as the resource management,network control,network security,spectrum management,and energy usage of satellite networks are more challenging than that of terrestrial networks.Meanwhile,artificial intelligence(AI),including machine learning,deep learning,and reinforcement learning,has been steadily growing as a research field and has shown successful results in diverse applications,including wireless communication.In particular,the application of AI to a wide variety of satellite communication aspects has demonstrated excellent potential,including beam-hopping,anti-jamming,network traffic forecasting,channel modeling,telemetry mining,ionospheric scintillation detecting,interference managing,remote sensing,behavior modeling,space-air-ground integrating,and energy managing.This work thus provides a general overview of AI,its diverse sub-fields,and its state-of-the-art algorithms.Several challenges facing diverse aspects of satellite communication systems are then discussed,and their proposed and potential AI-based solutions are presented.Finally,an outlook of field is drawn,and future steps are suggested. | Fares Fourati Mohamed-Slim Alouini | 2021 | Intelligent and Converged Networks2021，2，3： | 4 |
| 9 | Interference management in 6G space and terrestrial integrated networks: Challenges and approaches显示文摘The Space-Terrestrial Integrated Network(STIN)is considered to be a promising paradigm for realizing worldwide wireless connectivity in sixth-Generation(6G)wireless communication systems.Unfortunately,excessive interference in the STIN degrades the wireless links and leads to poor performance,which is a bottleneck that prevents its commercial deployment.In this article,the crucial features and challenges of STIN-based interference are comprehensively investigated,and some candidate solutions for Interference Management(IM)are summarized.As traditional IM techniques are designed for single-application scenarios or specific types of interference,they cannot meet the requirements of the STIN architecture.To address this issue,we propose a self-adaptation IM method that reaps the potential benefits of STIN and is applicable to both rural and urban areas.A number of open issues and potential challenges for IM are discussed,which provide insights regarding future research directions related to STIN. | Shi Yan Xueyan Cao Zile Liu Xiqing Liu | 2020 | Intelligent and Converged Networks2020，1，3： | 3 |
| 10 | Reconfigurable intelligent surface-aided wireless communications: An overview显示文摘The reconfigurable intelligent surface(RIS)is an emerging technology,which will hopefully bring a new revolution in wireless communications.The RIS technology can be deployed in an indoor/outdoor environment to dynamically manipulate the propagation environment.The RIS consists of a large number of independently controllable passive elements,and these elements are involved in realizing high passive beamforming gain.Different from the conventional active phased antenna array,there is no dedicated radio-frequency(RF)chain installed at the RIS to perform complex signal processing operations.Therefore,it does not incur additional noise while retransmitting the incident wave,which is substantially a unique feature from the conventional wireless communication systems.Taking advantage of its working principle,RIS has been deployed in various practical scenarios.In this tutorial,at first we will review the latest advances in RIS,including the application scenarios such as the system and channel model,the information theoretic analysis,the physical realization and design,key signal processing techniques such as precoding and channel estimation,and prototyping.Finally,we discuss interesting future research problems for the RIS-aided communications. | Muhammad Zain Siddiqi Talha Mir | 2022 | Intelligent and Converged Networks2022，3，1： | 3 |
| 11 | Wireless recommendations for internet of vehicles:Recent advances,challenges,and opportunities显示文摘Internet of Vehicles(IoV)is a distributed network of connected cars,roadside infrastructure,wireless communication networks,and central cloud platforms.Wireless recommendations play an important role in the IoV network,for example,recommending appropriate routes,recommending driving strategies,and recommending content.In this paper,we review some of the key techniques in recommendations and discuss what are the opportunities and challenges to deploy these wireless recommendations in the IoV. | Tan Li Congduan Li Jingjing Luo Linqi Song | 2020 | Intelligent and Converged Networks2020，1，1： | 2 |
| 12 | Convergence of computing,communication,and caching in internet of things显示文摘Internet of Things(IoTs)is a big world of connected objects,including the small and low-resources devices,like sensors,as well as the full-functional computing devices,such as servers and routers in the core network.With the emerging of new IoT-based applications,such as smart transportation,smart agriculture,healthcare,and others,there is a need for making great efforts to achieve a balance in using the IoT resources,including Computing,Communication,and Caching.This paper provides an overview of the convergence of Computing,Communication,and Caching(CCC)by covering the IoT technology trends.At first,we give a snapshot of technology trends in communication,computing,and caching.As well,we describe the convergence in sensors,devices,and gateways.Addressing the aspect of convergence,we discuss the relationship between CCC technologies in collecting,indexing,processing,and storing data in IoT.Also,we introduce the three dimensions of the IoTs based on CCC.We explore different existing technologies that help to solve bottlenecks caused by a large number of physical devices in IoT.Finally,we propose future research directions and open problems in the convergence of communication,computing,and cashing with sensing and actuating devices. | Mohammed Amine Bouras Fadi Farha Huansheng Ning | 2020 | Intelligent and Converged Networks2020，1，1： | 2 |
| 13 | Intelligent cognitive spectrum collaboration:Convergence of spectrum sensing,spectrum access,and coding technology显示文摘For a future scenario where everything is connected,cognitive technology can be used for spectrum sensing and access,and emerging coding technologies can be used to address the erasure of packets caused by dynamic spectrum access and realize cognitive spectrum collaboration among users in mass connection scenarios.Machine learning technologies are being increasingly used in the implementation of smart networks.In this paper,after an overview of several key technologies in the cognitive spectrum collaboration,a joint optimization algorithm of dynamic spectrum access and coding is proposed and implemented using reinforcement learning,and the effectiveness of the algorithm is verified by simulations,thus providing a feasible research direction for the realization of cognitive spectrum collaboration. | Peixiang Cai Yu Zhang | 2020 | Intelligent and Converged Networks2020，1，1： | 2 |
| 14 | Convergence of mobile broadband and broadcast services:A cognitive radio sensing and sharing perspective显示文摘With next generation networks driving the confluence of multi-media,broadband,and broadcast services,Cognitive Radio(CR)networks are positioned as a preferred paradigm to address spectrum capacity challenges.CRs address these issues through dynamic spectrum access.However,the main challenges faced by the CR pertain to achieving spectrum efficiency.As a result,spectrum efficiency improvement models based on spectrum sensing and sharing models have attracted a lot of research attention in recent years,including CR learning models,network densification architectures,and massive Multiple Input Multiple Output(MIMO),and beamforming techniques.This paper provides a survey of recent CR spectrum efficiency improvement models and techniques,developed to support ultra-reliable low latency communications that are resilient to surges in traffic and competition for spectrum.These models and techniques,broadly speaking,enable a wide range of functionality ranging from enhanced mobile broadband to large scale Internet of Things(IoT)type communications.In addition and given the strong correlation between the typical size of a spectrum block and the achievable data rate,the models studied in this paper are applicable in ultra-high frequency band.This study therefore provides a good review of CRs and direction for future investigations into newly identified 5G research areas,applicable in industry and in academia. | Kagiso Rapetswa Ling Cheng | 2020 | Intelligent and Converged Networks2020，1，1： | 2 |
| 15 | An intelligent wireless transmission toward 6G显示文摘With the deployment and commercial application of 5G,researchers start to think of 6G,which could meet more diversified and deeper intelligent communication requirements.In this paper,a four physical elements,i.e.,man,machine,object,and genie,featured 6G concept is introduced.Genie is explained as a new element toward 6G.This paper focuses on the genie realization as an intelligent wireless transmission toward 6G,including sematic information theory,end-to-end artificial intelligence(AI)joint transceiver design,intelligent wireless transmission block design,and user-centric intelligent access.A comprehensive state-of-the-art of each key technology is presented and main questions as well as some novel suggestions are given.Genie will work comprehensively in 6G wireless communication and other major industrial vertical,while its realization is concrete and step by step.It is realized that genie-based wireless communication link works with high intelligence and performs better than that controlled manually. | Ping Zhang Lihua Li Kai Niu Yaxian Li Guangyan Lu Zhaoyuan Wang | 2021 | Intelligent and Converged Networks2021，2，3： | 2 |
| 16 | Analysis on the development status of intelligent and connected vehicle test site显示文摘With the development of automobile intelligence and connectivity,Intelligent and Connected Vehicle(ICV)is an inevitable trend in the transformation and upgrading of the automotive industry.The maturity of any advanced technology is inseparable from a large number of test verifications,especially the research and application of automotive technology require a large number of reliable tests for evaluation and confirmation.Therefore,the ICV Test Site(ICVTS)will become a key deployment area.In this paper,we analyze the development status of ICVTS outside and within China,summarize the shortcomings of the existing test sites,and put forward some targeted suggestions,in an effort to guide the development and construction of ICVTS towards the path that seems to be most promising. | Peng Zhi Rui Zhao Haoran Zhou Yanwu Zhou Nam Ling Qingguo Zhou | 2021 | Intelligent and Converged Networks2021，2，4： | 2 |
| 17 | Research on classification mining method of frequent itemset显示文摘 | FAN Lilin | 2010 | Journal of Convergence Information Technology2010，，5： | 1 |
| 18 | A novel niche genetic algorithm for multimodal optimization显示文摘 | Zhang Yi Zhang Hu | 2011 | Journal of Convergence Infor- mation Technology2011，6，6： | 1 |
| 19 | Research on Improved Network Data Fault-Tolerant Transmission Optimization Algorithm显示文摘 | Xia K Cai J Wu Y | 2012 | Journal of Convergence Information Technology2012，7，19： | 1 |
| 20 | A new fault tolerance system for cloud storage显示文摘 | CHEN Z XU Y WANG X | 2011 | Journal of Convergence Information Technology2011，6，4： | 1 |
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