Performance analysis of PDMA-based hybrid satellite–terrestrial networks with decode-and-forward relaying

As one of the most promising non-orthogonal multiple access (NOMA) technologies in 5G communication, pattern division multiple access (PDMA) has theoretically higher spectrum utilization and a larger communication capacity than conventional orthogonal multiple access (OMA) technologies. In this letter, PDMA is applied to hybrid satellite–terrestrial networks with decode-and-forward (DF) relaying in the downlink, and an in-depth study on the performance of outage probability (OP), ergodic capacity and system throughput is performed. For a more comprehensive analysis, hybrid satellite–terrestrial relay networks (HSTRNs) with conventional OMA technology are used in the comparative analysis. Analysis and simulation results show that PDMA-based hybrid satellite–terrestrial relay networks outperform the other system in terms of OP and ergodic capacity.     

An efficient packet parser architecture for software-defined 5G networks

Software-defined networks (SDN) has emerged with the capability to program in order to enhance flexibility, management, and testing of new ideas in the next generation of networks by removing current network limitations. Network virtualization and functionalization are critical elements supporting the delivery of future network services, especially in 5G networks. With the integration of virtualization and functionalization, network resources can be provisioned on-demand, and network service functions can be composed and chained dynamically to cater to various requirements. 5G networks are expected to rely heavily on SDN, which has been widely applied in core network design. To have a software-defined 5G network, not only is new spectrum and interface needed from SDN, but also a programmable and efficient hardware infrastructure is required. Admittedly, hardware components and infrastructure play an important role in supporting 5G networks. In other words, the software-defined 5G network data plane must have the required flexibility and programmability to support upcoming needs and technologies. Technological solutions need to respond to actual requests in infrastructure. Packet parsers in the data plane of software-defined 5G networks are one of the most important components because of the variation in the type of network headers and protocols. Each SDN switch needs to identify headers for processing input packets in the data plane, where the packet parser operates. Multiple implementations of packet parsers have been done on different substrates that occupy large hardware resources and areas on chip. However, they are not suitable for software-defined 5G networks. Certain architectures have been presented for packet parsing, aimed at accelerating the process of header parsing, however no attention has been paid toward reducing the area and the volume of the needed hardware resources and programmability in the data plane. This paper presents a new and efficient architecture for packet parsers on Field Programmable Gate Arrays (FPGA), called Efficient FPGA Packet Parser (EFPP) in a designed software-defined 5G network. This architecture emphasizes the removal of Ternary Content Addressable Memory (TCAM) to decrease hardware resources and efficiency in the data plane. Moreover, this architecture uses the chip’s processing speed and reconfiguration capabilities to support new protocols and network headers while maintaining flexibilities on software-defined 5G networks. EFPP is applied to chips on FPGA Xilinx ZedBoard Zynq, and the resources consumed around 7.5% LookUp Table, 1.9% Flip-Flops, and 5.8% of the memory. EFPP was also more area efficient. According to our results, EFPP would reduce the area and volume of hardware compared to other peer works.     

基于SDN的TDMA体制星间网络架构设计

TDMA(时分多址)体制的导航星间网络既可以实现导航测距,也具备较高的数据传输速率,具有较为广泛的业务适应能力。然而,TDMA体制的星间网络系统也存在着星上处理复杂与卫星节点处理能力低的矛盾。借鉴SDN(软件定义网络)将网络系统控制层面与数据层面相分离的思想,在TDMA体制的星间网络中引入SDN技术,设计了基于SDN的TDMA体制星间网络架构,将控制功能从卫星节点抽离出来,使其可以专注于星间数据转发,控制管理信息主要由卫星地面站(后续为高轨道卫星)扮演的SDN控制节点制定并分发,从而简化了卫星的业务负担,同时可以借鉴成熟的地面网络技术制定高效的控管策略。对所设计架构的主要的控管流程进行了仿真模拟,仿真结果表明,该架构具有一定的可行性。     

Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications

Satellite communication is expected to play a vital role in realizing Internet of Remote Things (IoRT) applications. This article considers an intelligent reflecting surface (IRS)-assisted downlink low Earth orbit (LEO) satellite communication network, where IRS provides additional reflective links to enhance the intended signal power. We aim to maximize the sum-rate of all the terrestrial users by jointly optimizing the satellite’s precoding matrix and IRS’s phase shifts. However, it is difficult to directly acquire the instantaneous channel state information (CSI) and optimal phase shifts of IRS due to the high mobility of LEO and the passive nature of reflective elements. Moreover, most conventional solution algorithms suffer from high computational complexity and are not applicable to these dynamic scenarios. A robust beamforming design based on graph attention networks (RBF-GAT) is proposed to establish a direct mapping from the received pilots and dynamic network topology to the satellite and IRS’s beamforming, which is trained offline using the unsupervised learning approach. The simulation results corroborate that the proposed RBF-GAT approach can achieve more than 95% of the performance provided by the upper bound with low complexity.     

High-performance networks for broadband multimedia services

Research and development in Advanced Communications technologies for Europe (RACE) played a key role in developing the crucial technology of Asynchronous Transfer Mode (ATM), which can provide a high-performance networking platform for broadband multimedia communications while allowing access to the existing worlds of voice, data, and broadcasting. The functionalities of high-performance networks in the user plane, control plane, and management planes to provide integral performance for the satisfaction of the users have been tested in accompanying measures such as the TEN-IBC projects of the European Commission. The European Union (EU) is now starting Advanced Communications Technologies and Services (ACTS)—the follow-up to RACE—as one of the major specific programs in the fourth research framework, involving 630 million ECUs of European Union contribution over four years. High-performance networking is a key development area within ACTS. It has a clear objective of enabling the deployment of a coherent and comprehensive trans-European information highway consisting of a terrestrial (optical), mobile, and satellite network infrastructure supporting broadband multimedia communications with maximum flexibility and a cost-effective evolution approach. Operational trials of high-performance networks involving different types of users, applications, network operators (national hosts), and the European ATM pilot network are planned as a part of the new ACTS projects. This article summarizes the projects involved and their activities toward the objectives of provisioning the high-performance network information highway for broadband multimedia applications.     

DRL-M4MR: An intelligent multicast routing approach based on DQN deep reinforcement learning in SDN

Traditional multicast routing methods have some problems in constructing a multicast tree. These problems include limited access to network state information, poor adaptability to dynamic and complex changes in the network, and inflexible data forwarding. To address these defects, the optimal multicast routing problem in software-defined networking (SDN) is tailored as a multiobjective optimization problem, and DRL-M4MR, an intelligent multicast routing algorithm based on the deep Q network (DQN) deep reinforcement learning (DRL) method is designed to construct a multicast tree in a software-defined network. First, combining the characteristics of SDN global network-aware information, the multicast tree state matrix, link bandwidth matrix, link delay matrix and link packet loss rate matrix are designed as the state space of the reinforcement learning agent to solve the problem in that the original method cannot make full use of network status information. Second, the action space of the agent is all the links in the network, and the action selection strategy is designed to add the links to the current multicast tree in four cases. Third, single-step and final reward function forms are designed to guide the agent to make decisions to construct the optimal multicast tree. The double network architectures, dueling network architectures and prioritized experience replay are adopted to improve the learning efficiency and convergence of the agent. Finally, after the DRL-M4MR agent is trained, the SDN controller installs the multicast flow entries by reversely traversing the multicast tree to the SDN switches to implement intelligent multicast routing. The experimental results show that, compared with existing algorithms, the multicast tree constructed by DRL-M4MR can obtain better bandwidth, delay, and packet loss rate performance after training, and it can make more intelligent multicast routing decisions in a dynamic network environment. Code and DRL model are available at https://github.com/GuetYe/DRL-M4MR.     

Blockchain-based group authentication scheme for 6G communication network

The ultimate objective in this period is to turn present technology into intelligent global habitats that ease daily interactions. The emerging Industry 4.0 has provided exciting potential technologies that have sped up the transition from the Internet of Things (IoT) to the Internet of Everything using advancements in artificial intelligence (IoE). A secure data transmission method and much higher networking rates are required by the exponential increase in the development and implementation of various 4.0-related industries, even if a blockchain currently employs a fast network like 5G. This highlights how 6G is required to meet the requirements of real-time applications. This research suggests a group-based handover authentication strategy for 6G heterogeneous networks, taking into account the handover of group users in real-world scenarios, to increase the efficiency and guarantee the security of the authentication process. The system consists of four components: the user UE, the access points gNB and eNB, the servers AAA and AAA*, and the widely used blockchain. Additionally, it is split into the EPC (evolved packet core) and 6GC domains by various network topologies (6G core network). To access network services, the UE must first carry out initial authentication and key negotiation with the local server. The system then performs handover authentication as well as batch authentication for individual and group users in handover scenarios, depending on the user count. The suggested scheme accomplished global switching authentication without making the switching process more difficult, accomplished group switching authentication by utilizing blockchain and aggregated signature technologies, and decreased the one-by-one authentication time by Yan using the D–H key exchange idea to accomplish known randomness security. Through formal examination and additional security analysis of the suggested protocol using the AVISPA tool, the results demonstrate that the protocol is secure.     

A survey on 5G: The next generation of mobile communication

The rapidly increasing number of mobile devices, voluminous data, and higher data rate are pushing to rethink the current generation of the cellular mobile communication. The next or fifth generation (5G) cellular networks are expected to meet high-end requirements. The 5G networks are broadly characterized by three unique features: ubiquitous connectivity, extremely low latency, and very high-speed data transfer. The 5G networks would provide novel architectures and technologies beyond state-of-the-art architectures and technologies. In this paper, our intent is to find an answer to the question: “what will be done by 5G and how?” We investigate and discuss serious limitations of the fourth generation (4G) cellular networks and corresponding new features of 5G networks. We identify challenges in 5G networks, new technologies for 5G networks, and present a comparative study of the proposed architectures that can be categorized on the basis of energy-efficiency, network hierarchy, and network types. Interestingly, the implementation issues, e.g., interference, QoS, handoff, security–privacy, channel access, and load balancing, hugely effect the realization of 5G networks. Furthermore, our illustrations highlight the feasibility of these models through an evaluation of existing real-experiments and testbeds.     

Stochastic modelling and analysis of mobility models for intelligent software defined internet of vehicles

Data traffic forwarding and network optimization is essential to effective congestion management in software-defined vehicular networks, and it is necessary for software-defined vehicle networks (SDVN). SDVN is needed to optimize connection performance and network controls in dense and sparse networks to govern data flow between nodes as effectively as possible. Intelligent software-defined internet of vehicles (iSDIoVs) has recently emerged as a potential technology for future vehicular networks. It manages the vehicular ad hoc networks systematically. The link connection of moving vehicles from the central SDN controller may fail. It impacts the efficiency and communication performance because of the lack of connection between vehicles and infrastructure (V2I). The researchers have analyzed the network performance and mobility models in a dense and sparse network to maximize network performance by iSDIoVs. By integrating heterogeneous systems such as IEEE 802.11p and cellular networks into vehicular ad-hoc networks, it is possible to reduce buffer occupancy in iSDIoV and control the mobility and delay bound analysis in V2V communication. The SDN will provide flexibility and reliability to the vehicular networks. An SDN controller manages the data flow in the vehicular network and controls the flow matching rules in the control plane. The iSDIoV and queuing models improve the response time and resource utilization and enhance the network complexity analysis for traffic management services.     

CEAR: A cooperation based energy aware reward scheme for next generation green cognitive radio networks

Cognitive Radio (CR) networks are envisioned as a key empowering technology of the fifth-generation (5G) wireless communication networks, which solves the major issues of 5G, like high-speed data transmission, seamless connectivity, and increased demand for mobile data. Another significant characteristic of the 5G network is green communications, as energy consumption from the communication field is predicted to rise remarkably by the year 2030. In this work, we are concerned about energy-related issues and propose a cooperation-based energy-aware reward scheme (CEAR) for next-generation green CR networks. The proposed CEAR scheme is based on the antenna and temporal diversity of the primary users (PUs). For providing the service to the PUs, the users of another network called cognitive users (CUs) work as a cooperative relay node, and, in return, they get more spectrum access opportunities as a reward from the primary network. The CUs with delay-tolerant data packets take a cooperative decision by recognizing the availability and traffic load of PUs, channel state information, and data transmission requirements. We utilize the optimal stopping protocol for solving the decision-making problem and use the backward induction method to obtain the optimal cooperative solution. The simulation results reveal notable enhancements in energy efficiency (EE) of CUs compared with other cooperative schemes. The proposed CEAR scheme is more energy-efficient for ultra-dense network deployment because results show that the CU’s EE, spectral efficiency (SE), and throughput improved with the increase of PUs.     

QoS-aware resource allocation and fault tolerant operation in hybrid SDN using stochastic network calculus

Mobile edge computing (MEC) is a key feature of next-generation mobile networks aimed at providing a variety of services for different applications by performing related processing tasks closer to the users. With the advent of the next-generation mobile networks, researchers have turned their attention to various aspects of edge computing in an effort to leverage the new capabilities offered by 5G. So, the integration of software defined networking (SDN) and MEC techniques was seriously considered to facilitate the orchestration and management of Mobile Edge Hosts (MEH). Edge clouds can be installed as an interface between the local servers and the core to provide the required services based on the known concept of the SDN networks. Nonetheless, the problem of reliability and fault tolerance will be of great importance in such networks. The paper introduced a dynamic architecture that focuses on the end-to-end mobility support required to maintain service continuity and quality of service. This paper also presents an SDN control plane with stochastic network calculus (SNC) framework to control MEC data flows. In accordance with the entrance processes of different QoS-class data flows, closed-form problems were formulated to determine the correlation between resource utilization and the violation probability of each data flow. Compared to other solutions investigated in the literature, the proposed approach exhibits a significant increase in the throughput distributed over the active links of mobile edge hosts. It also proved that the outage index and the system’s aggregate data rate can be effectively improved by up to 32%.     

Optical networks, last mile access and applications

Free Space Optical (FSO) links can be used to setup FSO communication networks or to supplement radio and optical fiber networks. Hence, it is the broadband wireless solution for closing the “last mile” connectivity gap throughout metropolitan networks. Optical wireless fits well into dense urban areas and is ideally suited for urban applications. This paper gives an overview of free-space laser communications. Different network architectures will be described and investigated regarding reliability. The usage of “Optical Repeaters”, Point-to-Point and Point-to-Multipoint solutions will be explained for setting up different network architectures. After having explained the different networking topologies and technologies, FSO applications will be discussed in section 2, including terrestrial applications for short and long ranges, and space applications. Terrestrial applications for short ranges cover the links between buildings on campus or different buildings of a company, which can be established with low-cost technology. For using FSO for long-range applications, more sophisticated systems have to be used. Hence, different techniques regarding emitted optical power, beam divergence, number of beams and tracking will be examined. Space applications have to be divided into FSO links through the troposphere, for example up- and downlinks between the Earth and satellites, and FSO links above the troposphere (e.g., optical inter-satellite links). The difference is that links through the troposphere are mainly influenced by weather conditions similar but not equal to terrestrial FSO links. Satellite orbits are above the atmosphere and therefore, optical inter-satellite links are not influenced by weather conditions. In section 3 the use of optical wireless for the last mile will be investigated and described in more detail. Therefore important design criteria for connecting the user to the “backbone” by FSO techniques will be covered, e.g., line of sight, network topology, reliability and availability. The advantages and disadvantages of different FSO technologies, as well as the backbone technology are discussed in this respect. Furthermore, the last mile access using FSO will be investigated for different environment areas (e.g., urban, rural, mountain) and climate zones. The availability of the FSO link is mainly determined by the local atmospheric conditions and distance and will be examined for the last mile. Results of various studies will complete these investigations. Finally, an example for realizing a FSO network for the last mile will be shown. In this example FSO transmitters with light emitting diodes (LED) instead of laser diodes will be described. By using LEDs, problems with laser- and eye safety are minimized. Some multimedia applications (like video-conferences, live TV-transmissions, etc.) will illustrate the range of applications for FSO last mile networks.     

UAV caching in 6G networks: A Survey on models,techniques, and applications

The rapid development road map of 6G networks has posed a new set of challenges to both industrial and academic sectors. On the one hand, it needs more disruptive technologies and solutions for addressing the threefold issues including enhanced mobile broadband, massive machine-type communications, and ultra-reliable and low-latency communications. On the other hand, the ever-massive number of mobile users and Internet of Things devices conveys the huge volume of traffic throughout the 6G networks. In this context, caching is one of the most feasible technologies and solutions that does not require any system architecture changes nor costly investments, while significantly improve the system performance, i.e., quality of service and resource efficiency. Ground caching models deployed at macro base stations, small-cell base stations, and mobile devices have been successfully studied and currently extended to the air done by unmanned aerial vehicles (UAVs) to deal with the challenges of 6G networks. This paper provides a comprehensive survey of UAV caching models, techniques, and applications in 6G networks. In particular, we first investigate the entire picture of caching models moving from the ground to the air as well as the related surveys on UAV communications. Then, we introduce a typical UAV caching system and describe how it works in connection with all types of the transceivers, end users, and applications and services (A&Ss). After that, we present the recent advancements and analyses of the UAV caching models and common system performance metrics. Furthermore, the UAV caching with assisted techniques, UAV caching-enabled mechanisms, and UAV caching A&Ss are discussed to demonstrate the role of UAV caching system in 6G networks. Finally, we highlight the ongoing challenges and potential research directions toward UAV caching in 6G networks.     

Deep learning based physical layer security for terrestrial communications in 5G and beyond networks: A survey

The key principle of physical layer security (PLS) is to permit the secure transmission of confidential data using efficient signal-processing techniques. Also, deep learning (DL) has emerged as a viable option to address various security concerns and enhance the performance of conventional PLS techniques in wireless networks. DL is a strong data exploration technique which can be used to learn normal and abnormal behavior of 5G and beyond wireless networks in an insecure channel paradigm. Also, since DL techniques can successfully predict future new instances by learning from existing ones, they can successfully predict new attacks, which frequently involve mutations of earlier attacks. Thus, motivated by the benefits of DL and PLS, this survey provides a comprehensive review that overviews how DL-based PLS techniques can be employed for solving various security concerns in 5G and beyond networks. The survey begins with an overview of physical layer threats and security concerns in 5G and beyond networks. Then, we present a detailed analysis of various DL and deep reinforcement learning (DRL) techniques that are applicable to PLS applications. We present the specific use-cases of PLS design for each type of technique, including attack detection, physical layer authentication (PLA), and other PLS techniques. Then, we present an in-depth overview of the key areas of PLS where DL can be used to enhance the security of wireless networks, such as automatic modulation classification (AMC), secure beamforming, PLA, etc. Performance evaluation metrics for DL-based PLS design are subsequently covered. Finally, we provide insights to the readers about various challenges and future research trends in the design of DL-based PLS for terrestrial communications in 5G and beyond networks.     

A vision towards integrated 6G communication networks: Promising technologies,architecture, and use-cases

The evolution of the previous mobile communication generations has led to innovative goals of the Internet of Everything (IoE) in the 5G. However, addressing all IoE-associated problems in 5G is difficult and a long-term process. As the key performance indicators (KPIs) of the 5G services are highly diverse, it is an intimidating task to develop a single platform enabling all KPIs. The vision of next-generation 6G wireless communications lies not only in enhancing these targets but also in providing new services. Numerous extensively envisaged future services, including life-critical services and wireless brain–computer interactions, will be critically dependent on an instant, virtually unlimited wireless connectivity. In this direction, the 6G is envisioned to have primely five service objectives; further-enhanced mobile broadband (FeMBB), ultra-massive machine type communication (umMTC), extremely reliable low latency communication (ERLLC), long-distance and high-mobility communications (LDHMC), and extremely low-power communications (ELPC). The 3D global integration of the wireless communication networks is lacking in the 5G, which is targeted by the future 6G. In this paper, we present an exhaustive review of the 6G wireless communication network. We explore the various existing mobile communication generations concerning data rate, frequency band, bandwidth allotted, latency, and applications. We also highlight various current trends and issues in the 5G communication network, which drives research for the 6G communication network. Our focus is to provide a comprehensive survey on the future 6G. So, we explored the objectives and design principles for 6G. This paper highlights the key 6G technology drivers. This paper also proposes an architectural design for 6G. Moreover, we carry out a case-study of 6G architecture operational design and compare the result with previous generation architecture designs. Further, 6G envisioned open research challenges, research directions, and recent advancements are also highlighted in this paper. Furthermore, we discuss possible use-cases in terms of real-time interactions of the biological, physical, and digital world, and also how these use-cases are going to serve in 6G.     

低轨道量子卫星通信星上交换算法及仿真

量子卫星通信能够解决量子移动通信在航海、航空领域中对于远距离和大范围的需求,而星上交换是量子卫星通信的关键技术之一.本文以低轨道量子卫星通信星上交换为研究对象,提出了一种新的星上交换算法——终端测距法.利用该算法测得终端到相邻小区中心的距离,并将测得的数据上传给当前服务卫星系统,再由卫星系统通过比较距离大小决定终端是否切换.数学分析和仿真结果表明,该算法可靠性高、操作方便,能够在各卫星之间实现平稳切换.     

A novel deep deterministic policy gradient model applied to intelligent transportation system security problems in 5G and 6G network scenarios

Traffic congestion has been an actual problem in large cities, causing personal inconvenience and environmental pollution. To solve this problem, new applications for Intelligent Transportation System (ITS) have been created, to monitor actual traffic conditions. Therefore, fast, reliable and safe systems are desirable for creating a real intelligent transportation environment. Deep learning algorithms have been proposed for a better understanding of traffic behavior from a security-related perspective. Thus, we aim to maximize the safety problems using a deep learning algorithm, where a novel policy gradient model is presented for detecting vehicular misuse. The proposed model uses a triple network replay algorithm, maximizing the network convergence speed. Three networks are selected to optimize the policy network variables. Finally, the replay algorithm is partitioned with the aim of obtaining a faster model. Simulations on a real urban map are performed in a scenario with the integration of 5G or 6G networks. An architectural model for the integration of a Vehicular Ad-hoc Network (VANET) and cellular networks is determined in software-defined networking (SDN). The results show that the accuracy prediction of the proposed system presents better performance compared to related studies, where the proposed model increases its convergence speed and cumulative reward. Thus, the ITS improvement by the proposed deep learning algorithm increases the prediction accuracy, and reduces the transmission delay, treating the traffic path according to the congestion.     

低轨道量子卫星通信星上交换算法及仿真

量子卫星通信能够解决量子移动通信在航海、航空领域中对于远距离和大范围的需求,而星上交换是量子卫星通信的关键技术之一.本文以低轨道量子卫星通信星上交换为研究对象,提出了一种新的星上交换算法—终端测距法.利用该算法测得终端到相邻小区中心的距离,并将测得的数据上传给当前服务卫星系统,再由卫星系统通过比较距离大小决定终端是否切换.数学分析和仿真结果表明,该算法可靠性高、操作方便,能够在各卫星之间实现平稳切换.     

Performance analysis of a novel 5G architecture via Content-Centric Networking

Content-Centric Networking (CCN) is a recent paradigm conceived for future Internet architectures, where communications are driven by contents instead of host addresses. It binds the storage capacity into the network by using the in-network caching, which can reduce the transmission delay in the network. In this paper, a novel architecture of 5G via CCN, named as CCN-5G, is proposed. Meanwhile, the performance of CCN-5G are tested in the high-speed mobile environment. The simulation results show that the CCN-5G can achieve excellent performance and satisfy the future requirements of 5G.     

Group mobility assisted network selection framework in 5G vehicular cognitive radio networks

The heterogeneity nature of networks is the most eminent characteristic in 5G vehicular cognitive radio networks across complex radio environments. Since multiple communicating radios may be in motion at the same time in a vehicle. So, group mobility is the most prominent characteristic that requires to be a deep investigation. Therefore, different communication radios that are moving on a train/bus needed to select the networks simultaneously. Without considering the group mobility feature, there is a possibility that the same network may be selected by each moving node and cause congestion in a particular network. To overcome this problem, a novel network selection technique considering the group mobility feature is proposed to improve the throughput of the network. In this work, a 5G vehicular cognitive radio network scenario is also realized using USRP-2954 and LabVIEW communications system design suite testbed. The performance metrics like transmission delay, packet loss rate, reject rate and, channel utilization for vehicular nodes, are gained to analyze the proposed technique in vehicular cognitive radio networks environment. The proposed technique demonstrates a remarkable improvement in channel utilization for vehicular nodes and outperformed conventional schemes.