An Efficient FIR Filter Based on Hardware Sharing Architecture Using CSD Coefficient Grouping for Wireless Application

Current research emphasis on IoT (Internet-of-Things) to enable physical objects to connect, co-ordinate among themselves in a ubiquitous manner. Specifically, for this type of applications, the quality of wireless communication is indeed considered vital to enhance the reliability of battery operated IoT devices. Moreover, these devices operate on unlicensed bands creating heavy congestion on spectrum. Interestingly operating these devices on Cognitive Radio band avoids the spectrum shortage problem by exploiting the dynamic spectrum access capabilities. Cognitive relaying for IoT applications ensures reliable communication through interference mitigation among co-existing IoT devices. In this paper, we therefore propose spectrally efficient two-path decode and amplify relaying technique in three time slots through network-coded co-operation of Primary user and Secondary User. To address the interference issues, optimum power allocation is formulated as a convex optimization problem solved through a modeling system named CVX. Thereby we achieve co-operative diversity without the need for additional antennas for IoT networks. Performance evaluation compares the Bit Error Rate for different relaying schemes with and without optimum power allocation. Our simulation results ensure that the probability of error is minimized and rate is maximized by our proposed algorithm.

     

联合网络容量与认知用户满意度的资源分配优化方案

机会频谱接入技术是提高频谱利用率的一种有效方法,论文综合考虑信道的时变性、子信道空闲的检测可信度、认知网络与主网络间的互干扰等因素,建立了一种最大化认知网络有效容量和认知用户满意度的多目标优化模型,提出了一种联合资源分配和用户调度的PAUS算法.仿真结果表明,在主用户分布密度较低的环境中,该模型较最大化网络有效容量模型具有更高的用户满意度;较最大化认知用户满意度模型可获得更高的网络有效容量.     

Energy-efficient resource allocation model for device-to-device communication in 5G wireless personal area networks

In general, there are several many devices that can overload the network and reduce performance. Devices can minimize interference and optimize bandwidth usage by using directional antennas and by avoiding overlapping communication ranges. In addition, devices need to carefully manage their use of resources, such as bandwidth and energy. Bandwidth is limited in wireless personal area networks (WPANs), so devices need to carefully select which data to send and receive. In this paper, an intelligent performance analysis of energy-efficient resource optimization model has been proposed for device-to-device (D2D) communication in fifth-generation (5G) WPAN. The proposed energy-efficient resource allocation in D2D communication is important because it helps reduce energy consumption and extend the lifespan of devices that are communicating with each other. By allocating resources in an efficient manner, communication between two devices can be optimized for maximum efficiency. This helps reduce the amount of energy needed to power the communication, as well as the amount of energy needed to power the device that is communicating with another device. Additionally, efficient resource allocation helps reduce the overall cost of communication, as the use of fewer resources results in a lower overall cost. The proposed efficient resource allocation helps reduce the environmental impact of communication, as less energy is used for communication. The proposed energy-efficient resource allocation model (EERAM) has reached 92.97% of energy allocation, 88.72% of power allocation, 87.79% of bandwidth allocation, 87.93% of spectrum allocation, 88.43% of channel allocation, 25.47% of end-to-end delay, 94.33% of network data speed, and 90.99% of network throughput.     

基于多门限预留机制的自适应带宽分配算法

针对异构无线网络融合环境提出了一种基于多门限预留机制的自适应带宽分配算法,从而为多业务提供QoS保证。该算法采用多宿主传输机制,通过预设各个网络中不同业务的带宽分配门限,并基于各个网络中不同业务和用户的带宽分配矩阵,根据业务k支持的传输速率等级需求和网络状态的变化,将自适应带宽分配问题转化为一个动态优化问题并采用迭代方法来求解,在得到各个网络中不同业务和用户优化的带宽分配矩阵的同时,在带宽预留门限和网络容量的约束条件下实现网络实时吞吐量的最大化,以提高整个异构网络带宽的利用效率。数值仿真结果显示,所提算法能够支持满足QoS需求的传输速率等级,减小了新用户接入异构网络的阻塞概率,提高了平均用户接入率并将网络吞吐量最大提高40%。     

面向6G物联网的分布式译码技术

随着5G商业化和标准化的逐步推进,对6G技术的研究也提上了日程。由于其在6G无线通信系统中的巨大应用前景,物联网(IoT)技术引起了人们广泛的兴趣。面向6G的物联网网络需要允许大量设备接入并支持海量数据传输,其鲁棒性和可扩展性至关重要。在物联网中,所述“事物”(用户)可以通过采用各种多功能无线传感器实时收集环境数据。通常来说,收集的数据将反馈到中央单元以进行进一步处理。但是这一机制依赖于中央单元的正常工作,鲁棒性较差。该文提出一种分布式译码算法,该算法通过让各用户之间互相协作,交换信息来实现在各个用户处完成译码。利用分布式译码算法,每个用户可以得到与中心化处理相似的译码性能,从而提高了网络的鲁棒性和可扩展性。同时,相比传统分布式译码算法,该算法不需要每个用户了解网络的拓扑结构,因此为面向6G的高动态物联网提供了技术支撑。     

Smart Edge Caching-Aided Partial Opportunistic Interference Alignment in HetNets

The development of the next-generation wireless networks are regarded as the essentials to embrace of Internet of Things (IoT) and edge computing in heterogeneous networks (HetNets). Due to the the spectrum scarcity problem and the large number of connectivity demand of IoT users, intelligent interference management for IoT is worthy of thorough investigation and should be well discussed with consideration on edge computing in heterogeneous networks (HetNets). Two crucial challenges in the context are: 1) placing edge cache based on dynamic request of IoT users, and 2) cache-enabled interference management with time-varying wireless channels. In this paper, we proposed smart edge caching-aided partial opportunistic interference alignment(POIA) with deep reinforcement learning for IoT downlink system in HetNets. Towards this end, the proposed scheme can update the base station (BS) cache dynamically, and then select the optimal cache-enabled POIA user group considering the time-varying user’s requests and time-varying wireless channels. To solve this problem efficiently, the reinforcement learning is exploited that can take advantage of a deep Q-learing to replace the system action. Extensive evaluations demonstrate that the proposed method is effectiveness according to sum rate and energy efficiency of IoT downlink transmission for HetNets.

     

无线EH认知物联网网络资源分配研究

由于5G技术的快速发展,基于能量采集的认知物联网(Internet of things,IOT)具有很大的应用前景.针对无线物联网网络中存在的"doubly-near-far"问题,考虑在认知物联网网络中将能量采集与信息接收站分开管理,提出了一个基于能量采集的异构认知物联网网络模型,实现用户能效的最大化.此外,该模型不...     

Efficient scalable video multicast based on network-coded communication

In order to increase the efficiency of mobile video transmission in a 5G network, this paper investigates a cooperative multicast of scalable video using network coding with adaptive modulation and coding over dedicated relay-based cellular networks. Different scalable video layers prefer different protection degrees, and user equipments (UEs) in different locations experience different packet loss rates in wireless networks. Guaranteeing that all UEs experience a certain level of video quality is one of the biggest challenges in scalable video multicast. Using the number of satisfied UEs as a metric, the proposed efficient scalable video multicast based on network-coded cooperation (SVM-NC) scheme, combined with adaptive modulation and coding, enhances the attainable system performance under strict time and bandwidth resource constraints for guaranteed smooth playback. Various simulations were performed for performance evaluation. The proposed scheme ensures that the expected percentage of satisfied UEs approximately achieves the maximum number of UEs in a multicast group by using network-coded cooperation over dedicated relay-based cellular networks. In addition, the peak signal-to-noise ratio metric is asymptotic to the maximum performance of high-resolution video quality offered by service providers.     

Leveraging AI-enabled 6G-driven IoT for sustainable smart cities

Many scholastic researches have begun around the globe about the competitive technological interventions like 5G communication networks and its challenges. The incipient technology of 6G networks has emerged to facilitate ultrareliable and low-latency applications for sustainable smart cities which are infeasible with the existing 4G/5G standards. Therefore, the advanced technologies like machine learning (ML), block chain, and Internet of Things (IoT) utilizing 6G network are leveraged to develop cost-efficient mechanisms to address the issues of excess communication overhead in the present state of the art. Initially, the authors discussed the key vision of 6G communication technologies, its core technologies (such as visible light communication [VLC] and THz), and the existing issues with the existing network generations (such as 5G and 4G). A detailed analysis of benefits, challenges, and applications of blockchain-enabled IoT devices with application verticals like Smart city, smart factory plus, automation, and XR that form the key highlights for 6G wireless communication network is also presented. In addition, the key applications and latest research of artificial intelligence (AI) in 6G are discussed facilitating the dynamic spectrum allocation mechanism and mobile edge computing. Lastly, an in-depth study of the existing open issues and challenges in green 6G communication network technology, as well as review of solutions and potential research recommendations are also presented.     

Optimized BS assignment and resource allocation in cooperative OFDM networks

Cooperative transmission (CT) and orthogonal frequency division multiple (OFDM) are promising technologies for extending coverage and increasing throughput in broadband wireless access (BWA) networks. Therefore, we propose a novel BWA network architecture, that can set up inter-cell collaboration using physical layer cooperative transmissions among distributed wired access networks with a powerful coordination capability at the central office. However, conventional base station (BS) assignment and resource allocation schemes cannot be used directly because a user can be serviced by more than one BS with cooperative transmission technology. This study proposes a novel framework of BS assignment and resource allocation in a cooperative OFDM network. We provide three approaches of resource allocation for minimizing bandwidth usage, minimizing transmission power consumption, and balancing resource costs respectively. An optimized resource allocation scheme can be implemented by flexibly choosing one of these approaches based on network load. The simulation results show the efficiency of the proposed mathematical formulations and linearization approach of our scheme. The performance benefit of CT technology on the bandwidth saving is demonstrated by comparing the new BS assignment and resource allocation scheme with conventional non-cooperative transmission.     

Multi-Stage Pricing Game for Collusion-Resistant Dynamic Spectrum Allocation

In order to fully utilize scarce spectrum resources, dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. The network users' behaviors and dynamics need to be taken into consideration for efficient and robust spectrum allocation. In this paper, we model the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. In order to combat user collusion, we propose a pricing-based collusion-resistant dynamic spectrum allocation approach to optimize overall spectrum efficiency, while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that the proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.     

VLC-WiFi异构网络QoS感知的跨层动态资源分配

VLC-WiFi异构网络已经成为广受欢迎的短距离无线通信方式之一。然而,有限的频谱资源导致VLC-WiFi异构网络容量难以满足井喷式增长的用户数据带宽需求。该文结合物理层的动态链路传输性能以及媒体访问控制层的队列缓冲延迟性能,定义链路传输性能和链路服务质量(QoS)感知等级评估公式,根据用户数据包QoS需求,设计QoS感知的跨层动态资源分配(QoS-CLDRA)方法,并引入非正交多址接入的用户匹配与功率分配策略,进一步提升系统的吞吐量。仿真结果表明:所提方法能够有效提升系统吞吐量和降低缓冲队列长度。     

基于双连接和回传带宽配置的系统吞吐量效用和最大化算法

针对双连接可行的异构无线网络中关于用户关联和回传带宽配置的联合优化问题,构建了一个新的网络吞吐量效用和最大化框架。将该联合优化问题建模为一个非凸的混合整数分式优化问题。为了便于求解,首先将原建模问题进行去分式化转换,然后针对转换后依旧非凸的混合整数非线性优化问题,将其分解为两个优化子问题分别求解。通过固定用户关联变量,得到了最优的回传带宽配置机制;通过固定回传带宽配置因子变量,提出一个有效的迭代算法求解双连接可行的用户关联子问题。相比固定的回传带宽配置机制,所提算法可以获得最优的回传单位带宽配置因子值,同时拥有最优的系统吞吐量和系统吞吐量效用和性能。     

Bandwidth allocation in wireless ad hoc networks: Challenges and prospects

Ensuring each user experiences a satisfactory quality of service is an important challenge for network designers, especially in wireless networks, where resources are relatively scarce and interference is relatively high. Accordingly, there has been recent interest in bandwidth allocation in wireless ad hoc networks, the focus of this article. After highlighting the main challenges, we survey recently proposed solutions, which address the problem at the network or MAC layer, individually or jointly. We also classify these solutions according to some major design criteria, and suggest the directions of future work on bandwidth allocation.     

Spectrum allocation for wireless backhaul in heterogeneous ultra-dense networks

Wireless ultra-dense network (UDN) is one of the important technologies to solve the burst of throughput demand in the forthcoming fifth generation (5G) cellular networks. Reusing spectrum resource for the backhaul of small base stations (SBSs) is a hotspot research because of lower cost and rapid implementation with macro base stations (MBSs) in recent years. In heterogeneous UDN, the problem of spectrum allocation for wireless backhaul is investigated. In particular, two different spectrum resource reusing strategies for wireless backhaul are proposed in heterogeneous UDN with the limited bandwidth condition. Using a stochastic geometry-based heterogeneous UDN model, the success probabilities that mobile users communicate with SBSs or MBSs are derived under two different spectrum resource reusing strategies. In addition, the network throughput’s analytical expressions and the optimal ratio of spectrum allocation are derived. Numeral results are provided to evaluate the performance of the proposed strategies at throughput. Thus, the effectiveness of the strategy that mobile users can only communicate with SBSs is validated.     

Addressing the interdependence in providing fair and efficient bandwidth distribution in hybrid optical‐wireless networks

The convergence of optical and wireless technologies may offer a compelling network access infrastructure because these technologies combine major benefits such as large coverage in the wireless part and huge bandwidth in the optical part of the converged access network. The convergence of the passive optical networks with 4G wireless standards, such as the Worldwide Interoperability for Microwave Access and the Long Term Evolution, constitutes a quite attractive solution to meet the challenges of the modern bandwidth‐hungry access networks. One of the most important objective a modern access network has to address is the adequate bandwidth distribution to the final users. In addition, several other aims are emerged towards this goal, such as fairness and quality of service provisioning. The adversity of designing an efficient bandwidth distribution scheme for hybrid optical‐wireless access networks lies in the interdependence of both domains: the bandwidth distribution in the wireless domain depends on the optical transmission grant opportunities, while the bandwidth coordinator in the optical part has to be aware of the mobile user heterogeneity in the wireless domain. Moreover, the bandwidth decision‐making module in both networks has to be aware of providing a fair allocation independently of the number of mobile users or the traffic requests in the network. In this work, we endeavor to address the aforementioned challenges. A novel, fair, and efficient bandwidth distribution scheme is proposed for hybrid optical‐wireless access networks. By using weighted fairness provisioning techniques, the proposed scheme intends to alleviate the interdependence of the two domains, offering a fair and efficient bandwidth distribution to the mobile users. The weights are properly defined, by utilizing suitable optimization techniques such as the Lagrange multiplies, so as to incorporate the underlying features of each traffic requests, such as the population density and the propagation delay. Extensive simulation results indicate the capability of the proposed scheme, compared with other competitive allocation schemes, in provisioning a more efficient and fair bandwidth distribution in terms of latency, throughput, and packet drop ratio. Copyright © 2015 John Wiley & Sons, Ltd.     

A utility-based capacity optimization framework for achieving cooperative diversity in the hierarchical converged heterogeneous wireless networks

A hierarchical convergence mechanism for the heterogeneous wireless communication system via the heterogeneous cooperative relay node is presented in this paper, in which the techniques of cooperative communication and wireless relay are utilized to improve performances of the individual user and the overall converged networks. In order to evaluate the benefits of the proposal, a utility-based capacity optimization framework for achieving the heterogeneous cooperative diversity gain is proposed. The heterogeneous cooperative capacity, relay selection and power allocation theoretical models are derived individually. The joint optimization model for relay selection and power allocation is presented as well. Owing to the computation complexity, the sub-optimal cooperative relay selection algorithm, the sub-optimal power allocation algorithm and the sub-optimal joint algorithm are determined to approach the maximum overall networks' spectrum efficiency. These proposed algorithms are designed in conformance to guarantee the equivalent transmission rates of the different wireless access networks. The simulation results demonstrate that the utility-based capacity model is available for the heterogeneous cooperative wireless communication system, and the proposed algorithms can improve performances by achieving the cooperative gain and taking full advantage of the cross-layer design. Copyright © 2008 John Wiley & Sons, Ltd.     

Class-based quality of service over air interfaces in 4G mobilenetworks

We present a framework for quality of service provisioning over the air interfaces in future wireless networks, including 3G enhancement and 4G mobile networks. The framework is based on the paradigm of service classes, wherein each class can exhibit a characteristic behavior in terms of resource allocation over the air interface. Using this QoS framework, future wireless network operators can define their own sets of service classes, choose the preferred way of implementing the QoS behavior of these classes, and offer class-based pricing schemes. The user application can choose the service class that best suits its expectations in terms of QoS and cost of access. A class-based bandwidth scheduling scheme is described as a mechanism to implement this QoS framework over CDMA air interfaces. This scheme incorporates the paradigm of service classes, in conjunction with fair resource allocation and air interface congestion resilience, while allocating air interface bandwidth to mobile users     

Energy‐efficient device‐to‐device communication using adaptive resource‐block allocation

Device‐to‐device (D2D) communication in the fifth‐generation (5G) wireless communication networks (WCNs) reuses the cellular spectrum to communicate over the direct links and offers significant performance benefits. Since the scarce radio spectrum is the most precious resource for the mobile‐network operators (MNOs), optimizing the resource allocation in WCNs is a major challenge. This paper proposes an adaptive resource‐block (RB) allocation scheme for adequate RB availability to every D2D pair in a trisectored cell of the 5G WCN. The hidden Markov model (HMM) is used to allocate RBs adaptively, promoting high resource efficiency. The stringent quality‐of‐service (QoS) and quality‐of‐experience (QoE) requirements of the evolutionary 5G WCNs must not surpass the transmission power levels. This is also addressed while using HMM for RB allocation. Thus, an energy‐efficient RB allocation is performed, with higher access rate and mean opinion score (MOS). Cell sectoring effectively manages the interference in the 5G networks amid ultrauser density. The potency of the proposed adaptive scheme has been verified through simulations. The proposed scheme is an essential approach to green communication in 5G WCNs.     

Sensing Confidence Level-Based Joint Spectrum and Power Allocation in Cognitive Radio Networks

Cognitive radio (CR) has been extensively investigated in the past decade to tackle the contradiction between wireless spectrum shortage and underutilization. In this paper, we present a unified analytical framework to design PHY-layer spectrum sensing and MAC-layer resource scheduling jointly for CR networks. A key parameter, named sensing confidence level (SCL), is introduced to characterize the presence of imperfect sensing, and bridge the designs between kinds of spectrum sensing schemes and resource allocation algorithms. The SCL-based joint design of spectrum and power allocation is formulated as a mixed integer non-linear optimization problem and Lagrange duality theory is introduced to make the problem tractable. The proposed joint design framework in this paper provides a baseline for comparing different spectrum sensing schemes plus bandwidth and power allocation algorithms. Numerical results demonstrate the effectiveness of the proposed framework.