协作系统中基于比例公平的资源分配方法

针对多用户协作中继系统中的资源分配问题,提出了一种在满足用户速率比例公平约束条件下的新算法。该算法先将由2个时隙组成的中继用户传输链路转换为一个等效信道链路,将涉及子载波分配、中继选择和功率分配的组合优化问题转化为分步的次优化问题。该算法在等功率分配情况下,根据各用户速率比例公平系数进行初步子载波数目分配;以瞬时信道增益最佳原则,进行剩余子载波数目分配及具体子载波分配,同时完成中继选择;在速率比例公平约束条件下推导出次优化功率分配的闭式表达式,从而完成各子载波上的功率分配。仿真结果表明,该算法在有效提高系统容量的同时,保证了各用户速率之间的比例公平性。     

基于M2M终端组的比例公平资源分配研究

基于M2M终端组的资源分配策略可以有效提高M2M通信中的资源利用率.本文研究了M2M通信系统中基于组的保证不同组间传输速率的比例公平资源分配问题,提出了一种次优的能够保证不同终端组间传输速率比例公平的资源分配算法,并通过仿真对算法的性能进行了验证,给出了速率最大化算法与终端组比例公平算法的性能比较.     

Resource allocation with proportional rate fairness in orthogonal frequency division multiple access relay networks

We address the problem of subchannel and transmission power allocation in orthogonal frequency division multiple access relay networks with an aim to maximize the sum rate and maintain proportional rate fairness among users. Because the formulated problem is a mixed‐integer nonlinear optimization problem with an extremely high computational complexity, we propose a low‐complexity suboptimal algorithm, which is a two‐step separated subchannel and power allocation algorithm. In the first step, subchannels are allocated to each user, whereas in the second step, the optimal power allocation is carried out on the basis of the given subchannel allocation and the nonlinear interval Gauss–Seidel method. Simulation results have demonstrated that the proposed algorithm can achieve a good trade‐off between the efficiency and the fairness compared with two other existing relevant algorithms. In particular, the proposed algorithm can always achieve 100% fairness under various conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

基于比例公平原则的多用户MIMO-OFDM系统资源分配

提出了一种基于比例公平原则提高MIMO-OFDM系统吞吐量的子载波和功率分配算法.它在总功率和误比特率的约束下,以获取最大系统吞吐量为目标,同时为兼顾用户间资源享用的公平性,根据用户速率成比例推导出了子载波分配限制准则.仿真结果表明,本算法不仅可满足不同用户的速率要求,而且平衡了容量最大化和用户间公平性的矛盾,同时计算...     

On the use of immune clonal optimization for joint subcarrier and power allocation in OFDMA with proportional fairness rate

Resource allocation in orthogonal frequency division multiple access is a constraint optimization problem. In this paper, we concentrate on maximizing both the sum capacity and proportional fairness rate among users. The optimization model of resource allocation is formulated and then an immune clonalbased algorithm is proposed for it. The resource allocation is solved by separating the subcarrier and power allocation in two steps. Suitable immune operators are designed, such as clonal, mutation, Baldwin learning, selection and so on. Experiments show that, compared with the previous methods, the proposed algorithm obtains higher sum capacity with comparable computational complexity, and keeps the proportional rate more fairly among users. Copyright © 2012 John Wiley & Sons, Ltd.     

面向云计算环境的动态公平性度量方法

针对云计算环境资源动态性特点,给出了一种资源分配算法公平性动态度量模型——DFE (dynamic fairness evaluation)。模型引入了公平、效率和时间参数,通过将资源分配结果进行量化处理,定量地描述不同分配算法的公平性。首先考虑了云环境下的2种典型动态因素：1）节点资源需求动态变化;2）虚拟节点动态变化,并分别对这2种场景建立子模型,通过这2种模型导出了公平性动态度量模型DFE。分析了2种子模型以及DFE,通过DFE对几种典型资源分配算法进行度量,验证了在资源需求以及虚拟节点动态变化的情况下,DFE能够有效度量分配算法公平性,为云计算平台资源分配算法的选择提供了重要的参考。     

认知无线网络中兼顾效用与公平的联合带宽和功率分配算法

对不同类型的业务采用了统一的效用函数形式,并在此基础上构造了基于网络效用最大化模型的优化问题。采用拉格朗日对偶方法对问题进行了求解,提出了一种分布式的联合带宽和功率分配算法。仿真结果表明,本算法能够有效地为不同类型认知用户分配合理的带宽和功率资源,在最大化所有认知用户总效用的同时保证用户之间的效用公平性。     

基于公平度门限的多用户OFDM系统自适应资源分配算法

在传统的子载波分配过程中,具有优先权的用户将优先选择最好的载波,这将导致载波利用效率下降.许多改进算法通过牺牲一定的公平性来提升容量并降低复杂度,但是这可能会使用户间无法达到所要求的公平性.针对这些问题,提出了一种基于公平度门限的载波和功率自适应分配算法.在载波分配过程中,通过公平度门限来决定载波分配优先级,从而实现容量和公平度的粗略折中.载波分配后利用粒子群(PSO)算法进行功率分配来达到所要求的公平度门限.实验结果表明,该算法在满足所要求公平度门限的同时提升了系统容量.     

效用max—min公平准则及其在ABR业务中的应用

本文提出一种新的基于效用函数的max-min(UMM）公平准则,它实现的是用户效用之间的公平分配。在ABR业务下,本文提出UMM公平性的另外两个等价定义,考察了用户的最小需求和最大需求。为了求解UMM公平分配,文中给出集中式的UMM公平分配算法及其数学证明。文章从保证分配效率的角度出发赋予峰值信元位率PCR以新的含义。UMM公平性不仅是对以往ABR业务中max-min公平性的概括,还具有很好的推广前景,特别适用于多应用类型的网络资源分配。     

无线网络中兼顾业务类型及公平性的无线资源共享问题研究

基于图染色理论提出了2种无线网络中的无线资源共享算法C_TDRS和S_TDGRS.这2种算法分别从子信道和业务流角度考虑,以尽力满足业务需求为目标,兼顾了业务类型和资源共享的公平性.仿真结果表明,2种算法的共享结果在系统吞吐率和比例公平方面比现有算法更接近最优值,并且S_TDGRS算法对2个指标有很好的折衷.     

Efficient allocation of LTE downlink spectral resource to improve fairness and throughput

For the current generation of cellular communication systems, long‐term evolution (LTE) has been the major protocol to support high‐speed data transmission. It is critical to allocate downlink spectral resource in LTE, namely, resource blocks (RBs), but the issue is not well addressed in the standard. Therefore, the paper develops an efficient RB allocation algorithm with 4 mechanisms to improve both fairness and throughput in LTE. For fairness concern, our RB allocation algorithm uses a resource‐reservation mechanism to prevent cell‐edge user equipments from starvation, and a credit‐driven mechanism to keep track of the amount of resource given to each user equipment. For throughput concern, it adopts both weight‐assignment and RB‐matching mechanisms to allocate each RB to a packet according to its flow type and length. Through simulations, we demonstrate that the proposed RB allocation algorithm can significantly increase both throughput and fairness while reducing packet dropping and delays of real‐time flows, as compared with previous methods.     

Resource allocation for multiuser cognitive OFDM networks with proportional rate constraints

In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.     

速率比例公平下多用户OFDM系统的自适应资源分配

在多用户正交频分复用(MU-OFDM)系统中,考虑各个用户之间具有比例数据传输速率限制条件下的一种公平的自适应资源分配方案的最优算法计算量巨大,为此,提出了一种将子信道分配和功率分配相分离的次优算法.首先,在假设相同功率分配的情况下进行子信道的分配,然后在保持一定比例公平条件下使总容量最大时进行最优功率分配.对该算法的仿真表明,在用户数为2、子信道数为10的系统中,所提算法的容量性能接近最优算法,而计算量由指数增长变为线性增长.所提资源分配算法的总容量比以前的算法在用户间的分配更公平也更灵活.     

Resource scheduling in downlink LTE-advanced system with carrier aggregation

In this paper,we focus on the resource scheduling in the downlink of long term evolution advanced (LTE-A) assuming equal power allocation among subcarriers.Considering the backward compatibility,the LT...     

RPR环网中的一种带宽公平分配算法

首先讨论了RPR网络中的公平性原则,然后结合该原则引入了一种适合于RPR网络的公平分配方案,基于该方案提出了一种能满足RPR环网性能要求的公平分配算法。该算法通过采用控制的方法为共享某链路的各数据流合理地分配带宽资源,从而达到:(1)各流的速率达到稳定;(2)链路缓存的占有量稳定到一个目标值;(3)链路带宽得到充分利用且实现公平分配。同时该算法能顺次协同地处理完网络中的各个链路,从而能够实现整个RPR环网的公平性与高的链路带宽利用率,达到RPR协议所要求的目标。给出了该算法的代码描述并对其作出稳定性分析,然后通过仿真对其性能进行了验证。     

RPR网络中公平性算法的研究

主要讨论弹性分组环网中的公平性算法,对现有的公平性算法进行了分类和比较研究,分析了其性能指标和技术特点,最后结合相关的研究工作讨论了未来的发展趋势.     

OFDMA系统跨层资源分配算法

OFDM具有高频谱利用率和抗多径衰落的优点,已被公认为第三代移动通信系统长期演进标准以及第四代移动通信系统的核心技术。OFDMA是基于OFDM的一种多用户接入技术,在OFDMA系统中,各用户在不同的子载波上同时传输数据。主要研究了OFDMA系统中的跨层资源分配算法。详细分析了保证速率比例公平的非实时业务跨层资源分配算法,仿真结果说明该算法能够较好地保证用户之间的公平性,并能够获得较大的系统吞吐量和较小的业务延时。     

基于公平性的多用户OFDM系统自适应功率分配松弛算法

提出了两种多用户OFDM系统下行链路的自适应功率分配算法.通过进一步放松不同用户之间数据速率比例性要求,提出的新算法提高了功率使用效率.实验仿真表明:在降低计算复杂度的同时,大大提高了系统容量,并且也近似满足了不同用户之间数据速率比例性要求.     

A distributed pricing algorithm for achieving network‐wide proportional fairness

Proportional fairness (PF) scheduling achieves a balanced tradeoff between throughput and fairness and has attracted great attention recently. However, most previous work on PF only considers the single cell scenario. This paper focuses on the problem of achieving network‐wide PF in a generalized multiple base station multiple user network. The problem is formulated as a maximization model and solved using the dual method. By decomposing the dual objective function, we get a distributed pricing based algorithm. Optimality of this algorithm is presented. Although the algorithm is derived using fixed link rate assumption, it can still apply in the presence of time‐varying rates. The proposed algorithm is suitable for distributed systems in the sense that it does not need any inter base station communication at all. Simulations illustrate that the proposed distributed network‐wide PF scheduling algorithm achieves almost the same performance as the centralized one. Compared with traditional local PF (LPF) scheduling, the network‐wide PF scheduling achieves higher throughput, lower throughput oscillation, and greater fairness. Copyright © 2010 John Wiley & Sons, Ltd.     

Fairness based resource allocation for multiuser MISO-OFDMA systems with beamforming

Resource allocation problem in multiuser multiple input single output-orthogonal frequency division multiple access (MISO-OFDMA) systems with downlink beamforming for frequency selective fading channels is studied. The article aims at maximizing system throughput with the constraints of total power and bit error rate (BER) while supporting fairness among users. The downlink proportional fairness (PF) scheduling problem is reformulated as a maximization of the sum of logarithmic user data rate. From necessary conditions on optimality obtained analytically by Karush-Kuhn-Tucker (KKT) condition, an efficient user selection and resource allocation algorithm is proposed. The computer simulations reveal that the proposed algorithm achieves tradeoff between system throughput and fairness among users.