Quality of service analysis and resource allocation scheme for Long‐Term Evolution network

In this paper, we analyze the quality of service (QoS) framework supported by the Long‐Term Evolution standard and model the behavior of a finite‐state downlink wireless fading channel based on the configurations and system parameters provided by the 3GPP Long‐Term Evolution and provide experimental results. The model can be used to provide realistic physical layer input to evaluate the performance of algorithms at the upper layers. For example, the medium access control layer will use this data to test the performance of scheduling, admission control, power control, and so on. The QoS requirements at the physical layer, the data link layer, and the cross‐layer modeling are stated. Then, we present a QoS‐based call admission control algorithm that considers admission of calls for future start‐up as well as the immediate and hand‐off calls with a certain priority admission scheme. Analytical study based on two‐dimensional Markov chain is also provided. We then use a stochastic discrete event simulator to evaluate the performance of the call admission control algorithm. The results obtained for look‐ahead admission are compelling and indicate the usefulness of making advance resource reservations. Copyright © 2013 John Wiley & Sons, Ltd.     

基于柔性QoS的资源动态分配策略研究

本文在对QoS的柔性,描述和评价方法进行研究的基础上,针对频率资源有限的无线ATM网,提出了利用QoS的柔性在业务过程中对频率资源进行动态分配的方案和算法,并进行了实验仿真,结果表明利用QoS的柔性动态分配频率资源可以提高资源的利用率。     

Graph‐based resource allocation algorithms for multiuser downlink MIMO‐OFDMA networks

Multiuser multiple‐input multiple‐output orthogonal frequency division multiple access (MIMO‐OFDMA) is considered as the practical method to attain the capacity promised by multiple antennas in the downlink direction. However, the joint calculation of precoding/beamforming and resource allocation required by the optimal algorithms is computationally prohibitive. This paper proposes computationally efficient resource allocation algorithms that can be invoked after the precoding and beamforming operations. To support stringent and diverse quality of service requirements, previous works have shown that the resource allocation algorithm must be able to guarantee a specific data rate to each user. The constraint matrix defined by the resource allocation problem with these data rate constraints provides a special structure that lends to efficient solution of the problem. On the basis of the standard graph theory and the Lagrangian relaxation, we develop an optimal resource allocation algorithm that exploits this structure to reduce the required execution time. Moreover, a lower‐complexity suboptimal algorithm is introduced. Extensive simulations are conducted to evaluate the computational and system‐level performance. It is shown that the proposed resource allocation algorithms attain the optimal solution at a much lower computational overhead compared with general‐purpose optimization algorithms used by previous MIMO‐OFDMA resource allocation approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Opportunistic delay‐margin‐based resource allocation for next‐generation wireless networks

This paper studies and develops efficient traffic management techniques for downlink transmission at the base station (BS) of multi‐service IP‐based networks by combining quality‐of‐service (QoS) provision and opportunistic wireless resource allocation. A delay‐margin‐based scheduling (DMS) for downlink traffic flows based on the delays that each packet has experienced up to the BS is proposed. The instantaneous delay margin, represented by the difference between the required and instantaneous delays, quantifies how urgent the packet is, and thus it can determine the queuing priority that should be given to the packet. The proposed DMS is further integrated with the opportunistic scheduling (OPS) to develop various queueing architectures to increase the wireless channel bandwidth efficiency. Different proposed integration approaches are investigated and compared in terms of delay outage probability and wireless channel bandwidth efficiency by simulation. Copyright © 2010 John Wiley & Sons, Ltd.     

Performance analysis of a channel allocation scheme for multi‐service mobile cellular networks

This paper presents a new channel allocation scheme, namely the dynamic partition with pre‐emptive priority (DPPP) scheme, for multi‐service mobile cellular networks. The system is modelled by a two‐dimensional Markov process and analysed by the matrix‐analytic method. A pre‐emptive priority (PP) mechanism is employed to guarantee the quality of service (QoS) requirement of the real‐time (RT) traffic at the expense of some degradation of non‐real‐time (NRT) traffic, while the victim buffer compensates the degradation and has no negative impact on the RT traffic. The complete service differentiation between new calls and handoff calls from different traffic classes is achieved by using the dynamic partition (DP) concept with the help of related design parameters. The performance analysis and numerical results show that the DPPP scheme, compared with the existing schemes, is effective and practical in multi‐service environments. Copyright © 2006 John Wiley & Sons, Ltd.     

An uplink resource allocation scheme for OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, the uplink radio resource allocation is investigated for OFDMA‐based cognitive radio networks. In consideration of the characteristics of cognitive radio and OFDMA, an improved water‐filling power allocation scheme is proposed under the interference temperature constraints for optimal performance. Based on the improved water‐filling power allocation, a simple subcarrier allocation algorithm for uplink is proposed. The subcarrier allocation rules are obtained by theoretical deduction. In the uplink subcarrier allocation algorithm, the subcarriers are allocated to the users with the best channel quality initially and then adjusted to improve the system performance. A cursory water‐filling level estimation method is used to decrease the complexity of the algorithm. Asymptotic performance analysis gives a lower bound of the stability of the water‐filling level estimation. The complexity and performance of the proposed radio resource allocation scheme are investigated by theoretical analysis and numerical results. Copyright © 2008 John Wiley & Sons, Ltd.     

HSDN‐GRA: A hybrid software‐defined networking‐based geographic routing protocol with multi‐agent approach

We propose in this paper a Hybrid Software‐Defined Networking‐based Geographical Routing Protocol (HSDN‐GRA) with a clustering approach. It takes into account three different criteria to select the best relay to send data: (1) the contact duration between vehicles, (2) the available load of each vehicle, (3) and the log of encountered communication errors embedded in each cluster head. The multi‐criteria strategy allows the selection of the most reliable vehicles by avoiding communication problems and ensuring connection availability. Once the hybrid control plane has found out the next eligible neighbor, the data plane will be in charge of dividing and sending data. To validate our approach, HSDN‐GRA has been modeled and implemented in JADE, a multi‐agent platform, to be compared to other multi‐agent based protocols. Simulation results show that HSDN‐GRA achieves good performance with respect to the average routing overhead, the packet drop rate, and the throughput.     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

面向大规模物联网的无人机通信感知一体化能效优化算法

针对大规模物联网场景下无人机通信感知一体化系统存在的重复感知和能量受限等问题,提出了一种基于聚类算法的能效优化方案。该方案在满足无人机的移动性和感知能力约束下,通过联合设计无人机的三维轨迹和发射功率来最大化系统能效。由于该问题是非凸的,首先将其解耦为两个子问题,然后利用模拟退火算法和标准凸优化技术来求解无人机的悬停位置和飞行速度以获取最优轨迹,最后根据最优轨迹推导发射功率的闭合表达式,求得每个悬停位置的最优发射功率。与传统的二维和三维方案相比,所提基于聚类的能效优化方案在收敛速度提高4倍的基础上能提升20%~30%系统能效。     

A multi‐cell adaptive resource allocation scheme based on potential game for ICIC in LTE‐A

Intercell interference coordination in Third Generation Partnership Project long‐term evolution‐advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long‐term evolution‐advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell‐edge throughputs. Copyright © 2013 John Wiley & Sons, Ltd.     

Hopfield neural‐network‐based dynamic resource allocation scheme for non‐real‐time traffic in wireless networks

Dynamic resource allocation (DRA) plays a fundamental role in current and future wireless networks, including 3G systems. In this paper, a scheduling DRA scheme for non‐real‐time (NRT) packet services in wireless system is proposed based on the use of Hopfield neural networks (HNN). The scheme exploits the fast response time of HNN for solving NP optimization problems and has been particularized for the downlink transmission in a UMTS system, although it could be easily extended to any other radio access technology. The new DRA scheme follows a delay‐centric approach, since it maximizes the overall system resource utilization while minimizing the packet delay. Simulation results confirm that the proposed HNN‐based DRA scheme is effective in supporting different types of NRT services, while achieving efficient utilization of radio resources. Copyright © 2008 John Wiley & Sons, Ltd.     

A fast‐convergent fairness scheme for resource allocation in RPR networks

In this paper, we propose a fast‐convergent fairness scheme in IEEE 802.17 resilient packet ring (RPR) networks. In the proposed scheme, each station could rapidly approach fair rate by estimating the number of unbounded flows at each link. In addition, the fast‐convergent scheme could prevent rate oscillations in the RPR aggressive mode scheme under unbalanced traffic. The estimation mechanism is simple and scalable since it is stateless without per‐flow management. Through analytical and simulation evaluations our scheme was found to be stable and speedy when compared with 802.17 RPR fairness scheme or the proposed distributed virtual‐time scheduling in rings scheme. Our scheme could allocate bandwidth fairly and smoothly among flows and achieve high utilization at the same time in the RPR network. Copyright © 2008 John Wiley & Sons, Ltd.     

Maximization of user satisfaction in OFDMA systems using utility‐based resource allocation

In order to keep and/or expand its share of the wireless communication market and decrease churn, it is important for network operators to keep their users (clients) satisfied. The problem to be solved is how to increase the number of satisfied non‐real time (NRT) and real time (RT) users in the downlink of the radio access network of an orthogonal frequency division multiple access system. In this context, the present work proposes a method to solve the referred problem using a unified radio resource allocation (RRA) framework based on utility theory. This unified RRA framework is particularized into two RRA policies that use sigmoidal utility functions based on throughput or delay and are suitable for NRT and RT services, respectively. It is demonstrated by means of system‐level simulations that a step‐shaped sigmoidal utility function combined with a channel‐aware opportunistic scheduling criterion is effective toward the objective of user satisfaction maximization. Copyright © 2014 John Wiley & Sons, Ltd.     

A self‐organized resource allocation scheme for heterogeneous macro‐femto networks

This paper investigates the radio resource management (RRM) issues in a heterogeneous macro‐femto network. The objective of femto deployment is to improve coverage, capacity, and experienced quality of service of indoor users. The location and density of user‐deployed femtos is not known a‐priori. This makes interference management crucial. In particular, with co‐channel allocation (to improve resource utilization efficiency), RRM becomes involved because of both cross‐layer and co‐layer interference. In this paper, we review the resource allocation strategies available in the literature for heterogeneous macro‐femto network. Then, we propose a self‐organized resource allocation (SO‐RA) scheme for an orthogonal frequency division multiple access based macro‐femto network to mitigate co‐layer interference in the downlink transmission. We compare its performance with the existing schemes like Reuse‐1, adaptive frequency reuse (AFR), and AFR with power control (one of our proposed modification to AFR approach) in terms of 10 percentile user throughput and fairness to femto users. The performance of AFR with power control scheme matches closely with Reuse‐1, while the SO‐RA scheme achieves improved throughput and fairness performance. SO‐RA scheme ensures minimum throughput guarantee to all femto users and exhibits better performance than the existing state‐of‐the‐art resource allocation schemes.Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal resource allocation for two-stage connectionless access with collision detection

Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.     

Random forest classifier‐based safe and reliable routing for opportunistic IoT networks

Designing a safe and reliable way for communicating the messages among the devices and humans forming the Opportunistic Internet of Things network (OppIoT) has been a challenge since the broadcast mode of message sharing is used. To contribute toward addressing such challenge, this paper proposes a Random Forest Classifier (RFC)‐based safe and reliable routing protocol for OppIoT (called RFCSec) which ensures space efficiency, hash‐based message integrity, and high packet delivery, simultaneously protecting the network against safety threats viz. packet collusion, hypernova, supernova, and wormhole attacks. The proposed RFCSec scheme is composed of two phases. In the first one, the RFC is trained on real data trace, and based on the output of this training, the second phase consists in classifying the encountered nodes of a given node as belonging to one of the output classes of nodes based on their past behavior in the network. This helps in proactively isolating the malicious nodes from participating in the routing process and encourages the participation of the ones with good message forwarding behavior, low packet dropping rate, high buffer availability, and a higher probability of delivering the messages in the past. Simulation results using the ONE simulator show that the proposed RFCSec secure routing scheme is superior to the MLProph, RLProph, and CAML routing protocols, chosen as benchmarks, in terms of legitimate packet delivery, probability of message delivery, count of dropped messages, and latency in packet delivery. The out‐of‐bag error obtained is also minimal     

大规模MIMO OFDMA下行系统能效资源分配算法

针对大规模多输入多输出（MIMO）正交频分多址(OFDMA)下行移动通信系统,提出了一种基于能效最优的资源分配算法。所提算法在采用迫零(ZF)预编码的情况下,以最大化系统能效的下界为准则,同时考虑每个用户的最低速率要求,通过调整带宽分配、功率分配和基站天线数分配来优化能效函数。首先根据优化条件提出了一种迭代算法确定每个用户的带宽分配,然后利用分数规划的性质并采用凸优化方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法在较少迭代次数的同时能够取得较好的系统能效性能和吞吐量性能。     

基于扩展传染病模型和马尔可夫链的物联网可用度评估方法

为反映恶意程序传播环境下物联网可用的状态,基于扩展的SEIRD传染病模型和马尔可夫链提出一种物联网可用度评估方法。根据物联网节点的实际状态,扩展经典传染病模型SIR建立SEIRD物联网节点状态转换模型。由物联网节点各个状态之间的动态变化过程,构建物联网节点处于5种状态的概率动力学方程,得到反映各状态转换的马尔可夫矩阵,进一步得到物联网节点的可用度计算方法。以典型的星形和簇形物联网拓扑结构为例,给出整个物联网可用度的评估方法。通过实验,为管理员如何合理部署正常工作节点数、路由数提供建议。研究成果对提高物联网可用度、促进物联网成功应用具有理论指导意义。     

Performance evaluation of priority based adaptive multiguard channel call admission control for multiclass services in mobile networks

The CAC (call admission control), which can guarantee call services to meet their QoS (Quality of Service) requirements, plays a significant role in providing QoS in wireless mobile networks. In this paper, an adaptive multiguard channel scheme‐based CAC strategy is proposed to prioritize traffic types and handoff calls. The major aim of the study is to develop the analytical model of the priority traffic and handoff calls based adaptive multiguard channel scheme and examining the performance through setting the value of the adaptive ratio parameters. Our proposed scheme tries to mediate the advantages and drawbacks of the static and dynamic CAC schemes. The proposed scheme is quite different from previous studies because multithreshold values have been considered for multiclass traffic by adaption parameters, and a closed form analytical model is developed The numerical results show that this scheme can be used to keep the targeted QoS requirement by suitably setting the adaptive ratio parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

面向智能物联网的多媒体通信关键技术研究与应用

随着5G大规模商用和人工智能技术的日趋成熟,基础通信服务开启新一轮革新.以固话和手机为代表的传统通信正逐步向场景化智能通信演进,基础通信连接也正在从70亿人和人的连接,向200亿人与人/物的实时音视频连接迈进,呈现超清体验、交互智能、终端多态、服务泛在的发展趋势.本文提出面向智能物联网的多媒体通信系统架构以及关键技术研...