Enabling 5G indoor services for residential environment using VLC technology

Visible light communication (VLC) has emerged as a viable complement to traditional radio frequency (RF) based systems and as an enabler for high data rate communications for beyond-5G (B5G) indoor communication systems. In particular, the emergence of new B5G-based applications with quality of service (QoS) requirements and massive connectivity has recently led to research on the required service-levels and the development of improved physical (PHY) layer methods. As part of recent VLC standards development activities, the IEEE has formed the 802.11bb “Light Communications (LC) for Wireless Local Area Networking” standardization group. This paper investigates the network requirements of 5G indoor services such as virtual reality (VR) and high-definition (HD) video for residential environments using VLC. In this paper, we consider such typical VLC scenarios with additional impairments such as light-emitting diode (LED) nonlinearity and imperfect channel feedback, and propose hyperparameter-free mitigation techniques using Reproducing Kernel Hilbert Space (RKHS) methods. In this context, we also propose using a direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM)-based adaptive VLC transmission method that uses precomputed bit error rate (BER) expressions for these RKHS-based detection methods and performs adaptive BER-based modulation-order switching. Simulations of channel impulse responses (CIRs) show that the adaptive transmission method provides significantly improved error rate performance, which makes it promising for high data rate VLC-based 5G indoor services.     

Quality of Service based resource allocation in D2D enabled 5G-CNs with network slicing

With the rapid new advancements in technology, there is an enormous increase in devices and their versatile need for services. Fifth-generation (5G) cellular networks (5G-CNs) with network slicing (NS) have emerged as a necessity for future mobile communication. The available network is partitioned logically into multiple virtual networks to provide an enormous range of users’ specific services. Efficient resource allocation methods are critical to delivering the customers with their required Quality of Service (QoS) priorities. In this work, we have investigated a QoS based resource allocation (RA) scheme considering two types of 5G slices with different service requirements; (1) enhanced Mobile Broadband (eMBB) slice that requires a very high data rate and (2) massive Machine Type Communication (mMTC) slice that requires extremely low latency. We investigated the device-to-device (D2D) enabled 5G-CN model with NS to assign resources to users based on their QoS needs while considering the cellular and D2D user’s data rate requirements. We have proposed a Distributed Algorithm (DA) with edge computation to solve the optimization problem, which is novel as edge routers will solve the problem locally using the augmented Lagrange method. They then send this information to the central server to find the global optimum solution utilizing a consensus algorithm. Simulation analysis proves that this scheme is efficient as it assigns resources based on their QoS requirements. This scheme is excellent in reducing the central load and computational time.     

Integration of multi access edge computing with unmanned aerial vehicles: Current techniques,open issues and research directions

During the last decade, research and development in the field of multi access edge computing (MEC) has rapidly risen to prominence. One of the factors propelling MEC’s evolution is the ability to deploy edge servers capable of providing both communication and computational services in close proximity to the mobile user terminal. MEC has been regarded as a potentially transformative technique for fifth-generation (5G) and beyond 5G (B5G) wireless communication systems, as well as a possible complement to traditional cloud computing. Additionally, unmanned aerial vehicles (UAVs) integrated with MEC will play a critical role by introducing an additional mobility based computational layer to provide more secure, efficient and faster services. UAV enabled MEC offers seamless connectivity, fulfilling the promise of 5G’s ubiquitous connectivity. Due to the enormous interest in UAV enabled MEC, there has been a tremendous increase in the number of published research articles in this domain; however, the research area still lacks a systematic study and categorization. We present a systematic literature review (SLR) on UAV enabled MEC, examining and analyzing data on the current state of the art using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. To streamline our assessment, this study analyzes several research papers carefully selected through a multi-stage process satisfying the eligibility criteria defined in the paper. One of the SLR’s primary contributions is to broadly classify the research in the UAV enabled MEC domain into different categories including energy efficiency, resource allocation, security, architecture, and latency. We have identified key findings, technology, and pros and cons for the selected articles under each category. Additionally, we discuss the key open issues related to scalability and fairness, resource allocation and offloading optimization, service delivery with a focus on quality of experience (QoE) and quality of service (QoS), and standardization. Finally, we discuss several future research directions that would address the aforementioned issues and emerging use cases for UAV enabled MEC.     

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.     

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%.     

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.     

D2D-assisted user-centric adaptive video transmission in next generation cellular networks

Next-generation cellular networks need to provide seamless connectivity with higher data rates, increased capacity, and enhanced network coverage. As multimedia service demands in various heterogeneous devices grow rapidly compared to the underlying network’s capacity and bandwidth, the adaptation in multimedia streaming services is essential for providing satisfactory Quality of Experience (QoE). This paper develops a Device-to-Device (D2D)-assisted Utility-based Adaptive Multimedia (video) Streaming scheme (UAMS) using D2D communication in a 5th Generation (5G) cellular network where low-battery users may extend their streaming duration by spending lower reception energy with the help of D2D-assisted communication. The adaptation algorithm considers four utility functions: quality, power consumption, packet error ratio, and remaining battery of the user devices to adapt the bitrate dynamically and augment viewers’ experience. We formulate an optimization problem to maximize the joint utility function to provide the best adaptive multimedia content selected for transmission to the end-users either directly or via D2D Relay Nodes (DRNs) in every scheduling interval. We use a graph theoretic approach for choosing the best DRNs. Extensive simulations show the efficacy of the proposed scheme in terms of saved battery energy, churn rate, and QoE metrics compared to a few well-known existing schemes in the literature that do not use D2D communication.     

An Information-Theoretic View of Mixed-Delay Traffic in 5G and 6G

Fifth generation mobile communication systems (5G) have to accommodate both Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) services. While eMBB applications support high data rates, URLLC services aim at guaranteeing low-latencies and high-reliabilities. eMBB and URLLC services are scheduled on the same frequency band, where the different latency requirements of the communications render their coexistence challenging. In this survey, we review, from an information theoretic perspective, coding schemes that simultaneously accommodate URLLC and eMBB transmissions and show that they outperform traditional scheduling approaches. Various communication scenarios are considered, including point-to-point channels, broadcast channels, interference networks, cellular models, and cloud radio access networks (C-RANs). The main focus is on the set of rate pairs that can simultaneously be achieved for URLLC and eMBB messages, which captures well the tension between the two types of communications. We also discuss finite-blocklength results where the measure of interest is the set of error probability pairs that can simultaneously be achieved in the two communication regimes.     

Joint User Scheduling,Relay Selection,and Power Allocation for Multi-Antenna Opportunistic Beamforming Systems

Opportunistic beamforming (OBF) is a potential technique in the fifth generation (5G) and beyond 5G (B5G) that can boost the performance of communication systems and encourage high user quality of service (QoS) through multi-user selection gain. However, the achievable rate tends to be saturated with the increased number of users, when the number of users is large. To further improve the achievable rate, we proposed a multi-antenna opportunistic beamforming-based relay (MOBR) system, which can achieve both multi-user and multi-relay selection gains. Then, an optimization problem is formulated to maximize the achievable rate. Nevertheless, the optimization problem is a non-deterministic polynomial (NP)-hard problem, and it is difficult to obtain an optimal solution. In order to solve the proposed optimization problem, we divide it into two suboptimal issues and apply a joint iterative algorithm to consider both the suboptimal issues. Our simulation results indicate that the proposed system achieved a higher achievable rate than the conventional OBF systems and outperformed other beamforming schemes with low feedback information.     

动态Web服务组合的选择策略

为了提高光网络资源的利用率,提出一种基于Petri网的Web服务组合最优化选择的方法.根据用户需求使用Petri网对服务组合之间的数据依赖关系建模,利用Petri网的T-不变量得到各种可能组合方案,并对于每种组合方案使用广义随机Petri网分析其性能.实验结果表明：该方法充分利用Petri网善于描述、分析、评价分布式系统的优点,得到性能最优的基于光网络资源的服务组合方案.     

Adaptive dynamic bandwidth allocation algorithm supporting multi-services over Ethernet passive optical networks

In order to ensure fairness of each optical networks unit (ONU) in access network and meet quality of service (QoS) requirements of differentiated service such as voice, video and data, Ethernet passive optical network (EPON) dynamic bandwidth allocation (DBA) algorithm should avoid light load penalty, choose different scheduling scheme according to light loading or heavy loading circumstances, adaptively adjust the order of ONUs at the case heavy loading in order to guarantee QoS. Aiming at this problem, an adaptive dynamic bandwidth allocation algorithm supporting multi-services is presented. The algorithm guarantees QoS through dividing service into voice, video and data putting them into different queues, optical line terminal (OLT) collects all requests of different services from different ONUs, divides the adopted scheduling scheme according to loading, adaptively adjusts the order of ONUs queue based on minimum delay at the case heavy load. Therefore, it can really guarantee QoS. Simulation results of the algorithm show that the algorithm not only can support multi-service and avoid light load penalty, but also can guarantee the fairness of each ONUs and QoS. It has a better performance than other algorithms particularly at the case of heavy loading.     

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.     

Improving spectral efficiency via pilot assignment and subarray selection under realistic XL-MIMO channels

The main requirements for 5G and beyond connectivity include a uniform high quality of service, which can be attained in crowded scenarios by extra-large MIMO (XL-MIMO) systems. Another requirement is to support an increasing number of connected users in (over)crowded machine-type communication (mMTC). In such scenarios, pilot assignment (PA) becomes paramount to reduce pilot contamination and consequently improve spectral efficiency (SE). We propose a novel quasi-optimal low-complexity iterative pilot assignment strategy for XL-MIMO systems, based on a genetic algorithm (GA). The proposed GA-based PA procedure turns the quality of service more uniform, taking into account the normalized mean-square error (NMSE) of channel estimation from each candidate of the population. The simulations reveal that the proposed iterative procedure minimizes the channel estimation NMSE averaged over the UEs. The second procedure is the subarray (SA) selection. In XL-MIMO systems, commonly a UE is close to an SA antenna subset such that a sufficient data rate can be achieved if only a specific SA serves that UE. Thus, an SA selection procedure is investigated to make the system scalable by defining the maximum number of UEs each SA can help. Hence, the SA clusters are formatted based on the PA decision. Furthermore, we introduce an appropriate channel model for XL-MIMO, which considers a deterministic LoS component with a distance-dependent probability of existence combined with a stochastic spatially correlated Rayleigh NLoS fading component. The developed simulations and analyses rely on this suitable channel model under realistic assumptions of pilot contamination and correlated channels.     

An optimal protection and restoration scheme (OPARS) for optical networks

Protection and restoration are critical network design issues for optical networks since even a single failure for a short duration may result in huge data loss due to the large capacity of optical fibers. However, few studies have been done on these issues for optical burst switching (OBS) networks. Protection and restoration are essential mechanisms for guaranteeing more reliable traffic delivery services. But it is not easy to apply existing mechanisms to optical burst switching (OBS) networks due to its one-way reservation signaling and the statistical burst multiplexing. Thus, to achieve the high transmission performance and reliability simultaneously, unique properties of OBS must be considered in the design of protection scheme. In this paper, an optimal protection and restoration scheme (OPARS) has been introduced that not only optimizes the number of provisioned protection wavelengths adaptively based on the traffic load as well as the quality of service (QoS) requirements of bursts in high speed networks but also minimizes burst loss rates. In addition, the proposed scheme has been used as an efficient contention resolution technique. The simulation results verify that the proposed scheme improve the network resource and channel utilization while guaranteeing the targeted protection reliability and QoS requirements of bursts.     

Using partial correlation to enhance structural equation modeling of functional MRI data

In functional magnetic resonance imaging (fMRI) data analysis, effective connectivity investigates the influence that brain regions exert on one another. Structural equation modeling (SEM) has been the main approach to examine effective connectivity. In this paper, we propose a method that, given a set of regions, performs partial correlation analysis. This method provides an approach to effective connectivity that is data driven, in the sense that it does not require any prior information regarding the anatomical or functional connections. To demonstrate the practical relevance of partial correlation analysis for effective connectivity investigation, we reanalyzed data previously published [Bullmore, Horwitz, Honey, Brammer, Williams, Sharma, 2000. How good is good enough in path analysis of fMRI data? NeuroImage 11, 289–301]. Specifically, we show that partial correlation analysis can serve several purposes. In a pre-processing step, it can hint at which effective connections are structuring the interactions and which have little influence on the pattern of connectivity. As a post-processing step, it can be used both as a simple and visual way to check the validity of SEM optimization algorithms and to show which assumptions made by the model are valid, and which ones should be further modified to better fit the data.     

移动计算环境下远程用户体验数据挖掘方法研究

在移动计算环境下,通过对远程用户的体验数据优化挖掘,满足远程用户的个性化需求,提高对远程用户QoS服务质量。传统的数据挖掘方法采用显著特征关联信息提取算法,当远程用户体验数据之间的差异性特征不明显时,挖掘的准确性不好。提出一种基于关联用户自适应链路跟踪补偿的移动计算环境下远程用户体验数据挖掘模型,进行远程用户体验数据挖掘模型的总体设计和数据结构特征分析,对采集的远程用户体验数据进行非线性时间序列分解,对数据序列通过自相关特征匹配和特征压缩实现挖掘数据的指向性信息优化提取,采用关联用户自适应链路跟踪补偿方法实现对数据挖掘误差的控制和补偿,提高了数据挖掘的准确性和有效性。仿真结果表明,采用该挖掘方法进行移动计算环境下远程用户体验数据挖掘的准确度高,实时性较好,满足了移动远程用户的个性化需求,提高了对用户服务的针对性。     

Modeling,validation and performance evaluation of body shadowing effect in ultra-wideband networks

Ultra-Wideband (UWB) is an emerging wireless technology with high data rates and low transmission power, which is very suitable for high-speed, short-range multimedia applications such as the Internet Protocol Television (IPTV) indoor distribution. However, human body shadowing is very common in any office or household environment, and can dramatically affect the UWB link performance when the significant propagation paths are blocked. In this paper, we build an analytical model for the Body Shadowing Effect (BSE) on indoor UWB channels based on the IEEE 802.15.3a standard and the channel reciprocity property. The BSE model and the reciprocity property of UWB channels in both the baseband and the radio frequency band are validated with extensive measurement. We further apply the extended BSE model in the analysis of application-layer Quality-of-Service (QoS) metrics for IPTV services, and derive the packet loss rate of the IPTV streams analytically and obtain the admission region to ensure the QoS. The work is of particular importance for the performance evaluation of UWB networks and the service provisioning for IPTV indoor distribution.     

面向服务的AI-ESTATE故障诊断系统建模

测试和诊断的融合可以提高武器系统的维护效率,但是随着武器装备的升级改造就带来了原有的诊断知识难共享、诊断推理软件难以互操作、难重用,诊断功能难扩展的问题;AI-ESTATE标准规范了诊断知识和数据的标准化描述和诊断推理机的服务接口,为知识互换和软件可移植提供了条件;论文研究了面向服务的AI-ESTATE开放式故障诊断系统的体系结构和信息传递模式,分析了推理机模型管理服务和互操作服务;然后运用静态诊断模型服务关系图和UML时序图分析了AI-ESTATE服务在诊断模型编辑、索引等功能实现中的交换流程,运用动态诊断模型的UML时序图分析了AI-ESTATE互操作服务在故障诊断系统运行中推理机与其它组件的动态交互过程,为开放式AI-ESTATE智能诊断系统的开发奠定了基础。     

Improving quality of service in four-channel WDM ethernet passive optical network

Energy-efficiency and green communications have become dominant topics related to access network implementation, since their energy consumption is a major contributor of energy consumption within the Internet. In this paper we analyze an implementation of a new energy-efficient dynamic bandwidth algorithm in a four-channel Wavelength Division Multiplexing Ethernet Passive Optical Network (WDM EPON), in which wavelength assignments take place per service class and not per Optical Network Unit (ONU). The improved Dynamic Bandwidth Allocation (DBA) algorithm introduces independent bandwidth allocation for each wavelength, which results in efficient bandwidth management and utilization. The mathematical model for new DBA algorithm is described, as are changes to the Multi-Point Control Protocol (MPCP), necessary for its implementation. The obtained results show that the redefined DBA algorithm improves Key Performance Indicators (KPIs) and as a consequently enables delivery of enhanced services to end-users. Significant energy savings are achieved without Quality of Service (QoS) degradation, and without network or equipment architecture changes.     

大数据服务深度需求与SOA协作集成的异构系统融合机制

大数据服务需求的认知深度和服务架构的融合度直接影响多业务大数据应用的资源管理和服务质量,本文提出了一种基于大数据服务深度需求分析和面向服务的协作集成架构的异构系统融合机制。该机制,一方面,在分析大数据源多样化、差异化大数据组织形式及其存储方式,结合不同类型用户的需求差异化特征,建立了大数据服务需求分析模型。另一方面,对于多态异构的移动互联网大数据服务,经过结构化和开放性处理后,给出大数据通信和服务调用描述定义,提出了SOA协作集成的异构系统融合架构。仿真实验结果表明,所提出的算法在大数据服务响应成功率、执行时间和代价比等方面具有明显优势。