认知型飞蜂窝网络中的子信道分配与功率控制

为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。     

同频异构femtocell联合子信道和功率分配算法

摘要：针对macro-femto同频融合网络中基于资源分配的干扰抑制问题,提出一种联合子信道和功率分配算法来抑制同频干扰。该算法通过对MU进行功率控制并采用跨层切换消除同频跨层干扰,对FU进行联合信道和功率分配消除同频层内干扰;跨层切换问题是在每一层网络目标中断概率约束下通过优化网络吞吐量实现,而基于联合信道和功率分配的同频干扰抑制问题是在切换MU的目标数据速率和其他MU以及FU干扰门限约束下,通过优化FU的和速率实现。理论分析和仿真结果表明,该算法能够提高FU的和速率,增大femtocell的网络容量,并可增加femtocell的部署数目。     

多业务MIMO-OFDMA/SDMA系统跨层调度与动态资源分配

对多业务MIMO-OFDMA/SDMA 系统下行链路跨层调度与动态资源分配问题进行了研究.首先,在满足各种约束条件的前提下,以最大化系统吞吐量为目标建立了相应的优化模型;然后,提出了一种基于业务类型和子空间距离的用户分组算法,该算法采用聚类分析的方法在每个子载波上对配置有多根接收天线的用户进行分组,从而降低了调度时所需搜索的用户空间的维数;接着,基于所提出的用户分组算法并结合不同业务的优先级提出了一种新的跨层调度和资源分配算法,该算法充分利用跨层信息为每个子载波调度相应的用户组,并为调度到的用户分配相应的系统资源,从而通过最大化每个子载波的吞吐量近似实现了系统整体吞吐量的最大化.仿真结果表明,与现有的方案相比,所提算法更好地满足了不同业务用户的QoS要求,并获得了更好的吞吐量性能.     

LTE系统中下行频域资源分配算法的研究

在LTE系统中,下行频选分配依据子信道质量选取最好的信道来传输业务,提高系统吞吐量。本文从无线资源分配角度出发,针对现有频选算法的不足,提出一种改进型频选与非频选结合分配算法,实现频选资源选取的最优化,同时在资源分配时将频选分配和非频选分配算法进行合并处理,通过比较频选UE度量值和非频选UE度量值来决定当前资源块组(resource block group,RBG)的分配方式。通过系统级仿真可知,在提高资源分配合理性的同时,可以提高系统整体吞吐量。     

基于OFDMA/TDM系统的跨层资源分配算法

研究了OFDMA/TDM系统的资源分配问题,基于最差信道用户优先原则,提出了一种新的跨层资源分配算法CRRA(Cross-layer Radio Resource Allocation)及其简化算法S-CRRA(Simplified CRRA).该算法利用用户数据队列长度动态变化的特性和多用户分集策略以实现在满足用户服务质量(Quality of Service,QoS)的基础上最大化系统吞吐量,并且将频谱和功率分配分开进行以降低计算复杂度.仿真结果表明,CRRA算法和S-CRRA算法在系统吞吐量上基本一致,两者较已有的OFDMA/TDM系统资源分配算法能提高10%-24%的系统吞吐量.     

面向移动云计算接入网络的高能效无线资源管理

双层宏蜂窝/小蜂窝异构网络不但能解决室内用户的覆盖问题,还可以大幅度降低网络能量消耗。但是,网络中的跨层和层间干扰会降低网络性能,高能效的无线资源分配和优化方法无疑将成为解决此问题的有效途径。首先,给出了一个移动云计算管理框架。然后,针对无线单链路定义了空间传输效率,比较和分析了多种单链路效率度量的含义和数学性质,并针对基于LTE-A(long term evolution-advanced)的移动云计算接入网络,提出了一种高能效的无线资源管理算法。为了快速地达到最优解,设计了一个快速收敛的迭代算法。仿真分析说明此资源管理算法实现了移动云计算系统能量效率和吞吐量的高效折中。     

无线多跳网络下基于过时信道状态信息的跨层资源分配

对于无线多跳网络跨层资源分配算法的研究大多是建立在假定每个节点能获得网络中其他节点的完美的信道状态信息(CSI)的基础上。但是由于信道的时变特性和CSI的反馈延时,在动态变化较快的无线网络中,节点所获得的CSI很可能是过时或者部分过时的。基于这个前提,该文首次在动态无线多跳网络跨层资源优化分配算法中考虑了CSI这种变化的影响,并提出了一种相应的分布式联合拥塞控制和功率分配算法。仿真结果证明该算法能够极大地提高网络效用和能量效用。     

基于粒子群算法的下行CR-NOMA网络资源分配

将非正交多址接入(Non-orthogonal Multiple Access,NOMA)技术应用于认知无线电(Cognitive Radio,CR)次网络,使次用户的信号在功率域叠加,可以进一步提高次网络的吞吐量。为此,将粒子群算法(Particle Swarm Optimization,PSO)应用于底层模式的CR-NOMA网络进行资源分配,并分为子信道分配和功率分配两个步骤。在子信道分配中,使用结合遗传算法思想的粒子群算法提高算法的全局搜索能力。在此基础上,使用基于罚函数的粒子群算法对子信道功率和信道内用户功率进行分配。仿真结果表明,提出的基于粒子群算法的CR-NOMA网络资源分配相比以往算法能获得更高的次网络吞吐量。     

基于MAC层优先级调度的宽带电力线跨层资源分配

传统的资源分配算法采用分层系统,且不适用于宽带电力线通信系统中的不良信道环境。文中引入跨层思想提高资源利用率,保证服务质量(QoS),提出了一种基于MAC层QoS优先级调度功能的宽带电力线跨层资源分配方案。该算法考虑了实时用户对延迟的要求和非实时用户对队列长度的要求,并提出用户优先级函数。根据其优先级函数计算每个用户的数据包数量,生成基于效用函数的调度序列。在物理层中,根据调度的数据包,该算法分配物理资源用于分组。仿真结果表明,该算法在提高用户QoS的同时兼顾了系统的性能和吞吐量。     

基于补偿式CSI的分布式跨层联合资源分配算法

为消除过时信道状态信息(CSI)对分布式无线多跳网络环境下跨层资源分配效率的影响,提高跨层联合资源分配的准确性,基于信道相关性提出了一种补偿式跨层联合资源分配算法。利用瞬时和过时信道状态信息之间的条件概率密度函数,基于瑞利衰落信道模型求得信噪比(SINR) 模型下条件容量的闭式解。为补偿部分网络性能的损失,提出了一种考虑过时信道状态信息的联合拥塞控制、信道分配和功率控制的算法,在此过程中网络被建模成一个NUM 问题,可变的链路数据率和功率等资源限制作为约束条件。运用拉格朗日对偶分解技术,NUM问题被分布式求解。实验对比分析表明：在确保较低复杂度的前提下,该算法有效改善了分布式多跳网络资源分配的合理性,使其网络总体效用得到提升,降低了能耗。     

Cross-layer resource allocation for QoS guarantee with finite queue constraint in multirate OFDMA wireless networks

Efficient radio resource allocation is essential to provide quality of service （QoS） for wireless networks. In this article, a cross-layer resource allocation scheme is presented with the objective of maximizing system throughput, while providing guaranteed QoS for users. With the assumption of a finite queue for arrival packets, the proposed scheme dynamically a/locates radio resources based on user＇s channel characteristic and QoS metrics derived from a queuing model, which considers a packet arrival process modeled by discrete Markov modulated Poisson process （dMMPP）, and a multirate transmission scheme achieved through adaptive modulation. The cross-layer resource allocation scheme operates over two steps. Specifically, the amount of bandwidth allocated to each user is first derived from a queuing analytical model, and then the algorithm finds the best subcarrier assignment for users. Simulation results show that the proposed scheme maximizes the system throughput while guaranteeing QoS for users.     

Cross-layer resource allocation over wireless relay networks for quality of service provisioning

The authors propose a physical-datalink cross-layer resource allocation scheme over wireless relay networks for quality-of-service (QoS) guarantees. By integrating information theory with the concept of effective capacity, the proposed scheme aims at maximizing the relay network throughput subject to a given delay QoS constraint. This delay constraint is characterized by the so-called QoS exponent thetas, which is the only requested information exchanged between the physical layer and the datalink layer in our cross-layer design based scheme. Over both amplify-and-forwards (AF) and decode-and-forward (DF) relay networks; the authors develop the associated dynamic resource allocation algorithms for wireless multimedia communications. Over DF relay network, the authors also study a fixed power allocation scheme to provide QoS guarantees. The simulations and numerical results verify that our proposed cross-layer resource allocation can efficiently support diverse QoS requirements over wireless relay networks. Both AF and DF relays show significant superiorities over direct transmissions when the delay QoS constraints are stringent. On the other hand, the results demonstrate the importance of deploying the dynamic resource allocation for stringent delay QoS guarantees.     

Cross-Layer Multi-Packet Reception Based Medium Access Control and Resource Allocation for Space-Time Coded MIMO/OFDM

In this paper, a cross-layer design framework for multi-input multi-output (MIMO)/orthogonal frequency division multiplexing (OFDM) based wireless local area networks (WLANs) is proposed. In contrast to conventional systems where the medium access control (MAC) and physical (PHY) layers are separately optimized, our proposed methodology jointly designs a multi-packet reception (MPR) based protocol with adaptive resource allocation. Specifically, a realistic collision model is employed by taking into consideration the PHY layer parameters such as channel information, space-time coded beamforming and multiuser detection, as well as sub-carrier, bit, and power allocation. The allocation problem is formulated, so as to maximize the system throughput, subject to the constraints from both the MAC and PHY layers. These constraints depend on the results of access contention, data packets? length, users? spatial correlation and the quality of channel feedback information. An iterative algorithm is then provided to obtain the optimal solution. Simulation results will show that our proposed approach achieves significant improvement in system performance such as average throughput and packet delay, compared with conventional schemes where cross-layer design and optimization is not used.     

Quality-driven cross-layer optimized video delivery over LTE

3GPP Long Term Evolution is one of the major steps in mobile communication to enhance the user experience for next-generation mobile broadband networks. In LTE, orthogonal frequency- division multiple access is adopted in the downlink of its E-UTRA air interface. Although cross-layer techniques have been widely adopted in literature for dynamic resource allocation to maximize data rate in OFDMA wireless networks, application-oriented quality of service for video delivery, such as delay constraint and video distortion, have been largely ignored. However, for wireless video delivery in LTE, especially delay-bounded real-time video streaming, higher data rate could lead to higher packet loss rate, thus degrading the user-perceived video quality. In this article we present a new QoS-aware LTE OFDMA scheduling algorithm for wireless real-time video delivery over the downlink of LTE cellular networks to achieve the best user-perceived video quality under the given application delay constraint. In the proposed approach, system throughput, application QoS constraints, and scheduling fairness are jointly integrated into a cross-layer design framework to dynamically perform radio resource allocation for multiple users, and to effectively choose the optimal system parameters such as modulation and coding scheme and video encoding parameters to adapt to the varying channel quality of each resource block. Experimental results have shown significant performance enhancement of the proposed system.     

一种改进的多用户OFDM系统跨层分配优化算法

提出了一种多用户正交频分复用系统的跨层资源分配模型,结合了物理层中信道状态和媒体接入控制层中用户的队列信息,能更好地满足用户的服务质量要求。改进的混合优化算法结合了遗传算法与禁忌搜索算法的优点,并且对遗传算法的交叉因子进行改进,提高了全局搜索能力,能够更好地收敛于全局最优值,这样能更好地解决跨层资源分配问题。仿真结果表明,在此模型下利用改进的混合算法能有效地提高系统吞吐量,减小用户的平均时延,提高服务质量。     

GEO卫星LTE跨层资源调度算法

地球同步轨道(GEO)卫星通信系统具有通信时延长的特点,适用于GEO卫星长期演进(LTE)通信的资源调度算法非常重要。为提升星上资源分配的高效性,基于可变最大加权时延优先(M-LWDF)算法,提出了一种综合考虑媒体接入控制(MAC)层参数和应用层参数的跨层调度算法。该算法在MAC层从数学角度推导,提出权重更大的时延判决因子及在应用层根据业务优先级不同引入Q因子。仿真结果表明,与M-LWDF算法相比,不同业务情况下,跨层资源调度算法减小了通信时延,提高了系统吞吐量,但公平性能略有下降并增加了复杂度。     

Enhanced performance based on cross-layer design from physical to transport layers for multihop wireless networks

This paper puts forward a novel cognitive cross-layer design algorithms for multihop wireless networks optimization across physical,mediam access control(MAC),network and transport layers.As is well known,the conventional layered-protocol architecture can not provide optimal performance for wireless networks,and cross-layer design is becoming increasingly important for improving the performance of wireless networks.In this study,we formulate a specific network utility maximization(NUM)problem that we believe is appropriate for multihop wireless networks.By using the dual algorithm,the NUM problem has been optimal decomposed and solved with a novel distributed cross-layer design algorithm from physical to transport layers.Our solution enjoys the benefits of cross-layer optimization while maintaining the simplicity and modularity of the traditional layered architecture.The proposed cross-layer design can guarantee the end-to-end goals of data flows while fully utilizing network resources.Computer simulations have evaluated an enhanced performance of the proposed algorithm at both average source rate and network throughput.Meanwhile,the proposed algorithm has low implementation complexity for practical reality.     

Noncooperative power-control game and throughput game over wireless networks

Resource allocation is an important means to increase system performance in wireless networks. In this letter, a game-theory approach for distributed resource allocation is proposed. Observing the bilinear matrix inequality nature of resource allocation, we construct two interrelated games: a power-control game at the user level, and a throughput game at the system level, respectively, to avoid local optima. An optimal complex centralized algorithm is developed as a performance bound. The simulations show that the proposed games have near-optimal system performance.     

Queue-Aware Resource Allocation for Multi-cell OFDMA Systems with QoS Provisioning

This paper proposes a queue-aware resource allocation algorithm which provides quality of service (QoS) guarantees. The proposed solution adopts a cross-layer design approach since it is aware of both users’ queue buffer states (data link layer) and channel quality state (physical layer). Main advantages of the proposed resource allocation algorithm are: the low computational complexity and its capacity of maintaining lower QoS violation probability than other multi-cellular schemes. The proposed solution can also result in enhanced cell-edge data rate and improved fairness performance. User minimum data rate and target bit error rate as considered as QoS parameters. Validation of the proposed algorithm is achieved through various simulation scenarios wherein QoS violation probability, system fairness, user average data rate and cell-edge throughput are investigated. Numerical results and complexity analysis demonstrate the efficiency and the feasibility of the proposed QoS-oriented approach.     

中继增强的无线蜂窝多小区系统的联合调度与功率控制算法

针对采用全局频率复用的中继增强的无线蜂窝多小区系统,该文考虑多种通信模式并存的混合场景,提出了一种干扰感知的联合资源分配策略。以最大化系统总吞吐量为目标,同时考虑小区间干扰对中继节点与移动站点的影响,以及基站与中继节点各自的发射功率约束。为了降低计算复杂度,针对用户与中继节点配对问题提出了一种基于小区间干扰的调度算法;针对功率控制问题分别提出了一种基于符号规划的最优功率分配算法和一种次优的最小能耗功率分配算法。仿真结果表明,该文所提算法逼近最优资源分配,在系统吞吐量与能量效率等性能方面具有显著优势。