OFDMA协同通信系统资源分配算法

提出了一种OFDMA协同蜂窝网中满足用户QoS需求且兼顾用户公平性的子载波和功率联合分配算法。针对已有算法仅考虑平均功率下的子载波分配、中继节点存在未用功率的情况,研究了子载波分配完毕后中继节点剩余功率最优分配问题。给出了一种基于二分法的功率注水分配方案。仿真结果表明,所提出的子载波和功率联合分配算法能够在满足用户QoS需求及公平性的同时,进一步提高网络吞吐量。     

OFDMA 协同网络中基于QoS 保证的资源分配算法

针对正交频分多址(OFDMA)协作通信系统,为了解决数据传输速率最大化并提供尽力而为业务与实时业务的服务质量(QoS)保证问题,提出新型资源分配算法.通过以总功率受限为约束条件,定义基于数据速率、时延和丢包率的效用函数,并以在协作传输中以最大化效用函数为目标进行中继选择和子载波分配.通过中继和用户上的子载波和功率分配方案的设计,从而最大化网络数据传输速率并最小化时延与丢包率,为多种业务提供服务质量保证.采用最优化理论与方法求解效用函数,得到了资源分配结果.仿真结果验证了算法收敛,并给出功率分配结果,以及网络吞吐量和时延性能指标情况,验证了算法的有效性.     

OFDMA系统中基于多业务QoS保证的机会调度算法

针对正交频分多址接入（OFDMA）系统中多业务资源调度问题,提出了一种基于服务质量（QoS）的最小性能保证的资源机会调度算法。以系统总吞吐量优化为目标,根据业务的QoS参量设计子载波调度参数,并利用图论中最大加权双向匹配问题的求解算法,在各业务间公平分配子载波资源,保证了各业务的QoS要求。仿真结果表明,所提算法在保证各业务的最低速率要求的前提下有效地提高了系统总吞吐量性能。     

中继OFDMA系统容量公平资源分配算法研究

针对OFMDA解码-转发中继系统的资源分配问题,提出了一种以系统总功率和用户间的数据速率比例公平为约束条件,以最大化系统总速率为目标的资源分配算法。该资源分配问题为非线性最优化问题,联合求解所有变量复杂度很高,通过次优化的方法降低计算复杂度。算法包括：子载波分配和功率分配。子载波分配是以功率平均分配为前提,对基站-中继站和中继站-用户链路的子载波按照信道条件进行配对,并根据比例公平约束将配对的子载波分配给相应的用户。功率分配是对每个用户利用Lagrange方法调整每个子载波的功率,进一步提高系统的数据速率。算法仿真分析表明,该算法既能同时满足多用户不同数据速率的要求,又能提高系统的数据速率。     

基于子载波选择配对及功率优化分配的多跳中继系统研究

为了提升OFDM协作通信系统的网络覆盖率及网络容量,提出了一种基于子载波选择配对及功率优化分配的多跳中继OFDM系统优化算法。首先,通过在OFDM的系统模型上进行中继配对和非中继配对的性能分析,将子载波选择配对转换为一个整数规划问题,并采用基于匈牙利算法的规划方法进行配对矩阵的计算。接着,根据OFDM系统的功率分配问题,通过KKT条件对中继功率及电源功率进行优化,从而实现中继系统的功率优化分配 。最终的仿真结果表明,与统计质量QoS保证的资源分配方案以及OFDM中继系统异构服务的资源分配算法相比,所提出的方法在提高网络覆盖率和容量上均表现出更好的效果。     

改进的OFDM双向中继功率分配策略

针对放大转发(AF)模式下正交频分复用(OFDM)双向中继网络如何提高系统总容量的问题,提出了一种低复杂度的以系统总速率最大化为目标的最优功率分配策略。该策略先建立用户与中继节点间的最优功率分配比例关系,将三层功率最优化问题简化为一层最优化问题,实现了将节点上的功率优化分配问题转化成一种易于处理的形式,以较小的复杂度获得了各节点上分配的功率占所在子载波对上分配的功率的比重;然后利用原对偶内点法求解各子载波间的功率分配问题;最终,求得各节点最优的功率分配。仿真实验表明,所提算法能显著提升系统总速率,且其性能随子载波数的增多而提升。     

基于拍卖理论的中继协作网络功率分配研究

针对放大转发无线协作中继网络,文中提出了一种改进的基于拍卖理论的分布式功率分配算法。该算法中用户以最大化自身的效用为目标,通过向中继节点发送投标量的方式购买中继功率,中继节点根据价格更新策略指定合理的中继价格,并根据用户的投标量进行功率分配。改进算法重新定义了用户节点的效用函数,降低了算法的复杂度。文中分析了单中继无线协作网络中继功率的分配过程以及用户的最佳投标量。仿真结果表明,该改进算法收敛速度快,中继节点覆盖范围大,有效提高了网络的传输速率。     

无线协作网络中的能量有效性中继选择算法

研究了无线协作网络中的中继选择问题,允许中继具有缓存数据的能力,提出了一种带有buffer的能量有效性中继选择算法,以延长网络生命周期并提高系统吞吐量。该算法综合考虑链路信息,中继的队列状态以及节点的剩余能量信息,通过加权效用公式选择最优接收数据中继与最优发送数据中继。考虑源节点与中继节点间的功率分配,以降低因源节点到中继节点以及中继节点到目的节点间的信道速率不一致所引起的系统丢包率。仿真实验结果表明,该算法有效地延长了网络的生命周期,随着中继个数的增加网络吞吐量有明显的提高,考虑功率分配后,有效降低了系统丢包率。     

AF型中继辅助OFDM系统中的功率优化

讨论了AF型中继辅助OFDM通信系统中的功率优化方案,并针对最优的功率优化方案很难得到闭合解的问题,提出了一种迭代的功率优化算法。这种迭代算法将AF型中继辅助OFDM通信系统中,单个子载波上源节点与中继节点间的功率分配问题以及各个子载波之间的功率优化问题分开,首先计算给定某个子载波上发送总功率下源节点与中继节点间的功率分配,然后在此基础上进一步优化子载波间的功率分配,并迭代逼近最优解。实验证明,在给定传输总功率的情况下,与传统的等功率分配相比这种迭代的优化方案可以获得较高的系统性能优势。     

协同OFDM系统联合中继选择、子载波配对和功率分配算法

研究了协同OFDM系统中的资源分配问题,提出了一种联合中继选择、子载波配对和功率分配的算法.首先在假定等功率分配的情况下,对中继节点进行选择并对子载波进行配对,然后在此基础上对选定的子载波对进行功率分配.分析结果显示所提算法是一种计算复杂度比较低,且系统容量接近最优容量的算法.     

QoS-aware distributed spectrum sharing for heterogeneous wireless cognitive networks

Ubiquitous wireless networking calls for efficient dynamic spectrum allocation (DSA) among heterogeneous users with diverse transmission types and bandwidth demands. To meet user-specific quality-of-service (QoS) requirements, the power and spectrum allocated to each user should lie inside a bounded region in order to be meaningful for the intended application. Most existing DSA methods aim at enhancing the total system utility. As such, spectrum wastage may arise when the system-wise optimal allocation falls outside individual users’ desired regions for QoS provisioning. The goal of this paper is to develop QoS-aware distributed DSA schemes using game-theoretic approach. We derive DSA solutions that respect QoS and avoid naively boosting or sacrificing some users’ utilities to maximize the network spectrum utilization. Specifically, we propose two game-based DSA algorithms: one resorts to proper scaling of the transmission power according to each user’s useful utility range, and the other embeds the QoS factor into the utility function used during gaming. To evaluate DSA schemes from a practical QoS perspective, we introduce two new metrics, namely “system useful utility” and “fraction of QoS-satisfied users”. Simulations confirm that the proposed DSA techniques outperform existing QoS-blind game models in terms of the spectrum sharing efficiency in heterogeneous networks. Convergence analysis of the proposed QoS-aware DSA algorithms is also provided.     

电力线通信系统中跨层的用户调度和资源分配

针对多用户多业务基于正交频分多址的电力线通信系统,提出一种在数据链路控制层进行用户调度和在物理层进行资源分配的多层多目标最优的跨层资源分配算法,其用户调度根据所有用户的服务质量(QoS)满意程度、QoS要求、业务包模型、信道状态信息和队列状态信息,从所有用户中选出要服务的用户和确定这些用户的最优跨层参数;其资源分配则根据所有调度用户的QoS要求、最优跨层参数和信道状态信息,先把功率按地窖注水原理分给每个子载波,再把每个子载波最优地分给调度用户并采用逐比特加载查表算法调整其上分配的功率和比特。最后在典型的电力线信道环境下对算法进行仿真,结果表明新算法在系统资源大范围变化时也能保障用户的服务质量,同时有效地提高系统资源的利用。     

A new approach to dynamic bandwidth allocation in Quality of Service networks: Performance and bounds

Efficient dynamic resource provisioning algorithms are necessary to the development and automation of Quality of Service (QoS) networks. The main goal of these algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources.In this paper we introduce a new service model that provides per-flow bandwidth guarantees, where users subscribe for a guaranteed rate; moreover, the network periodically individuates unused bandwidth and proposes short-term contracts where extra-bandwidth is allocated and guaranteed exclusively to users who can exploit it to transmit at a rate higher than their subscribed rate.To implement this service model we propose a dynamic provisioning architecture for intra-domain Quality of Service networks. We develop a set of dynamic on-line bandwidth allocation algorithms that take explicitly into account traffic statistics and users’ utility functions to increase users’ benefit and network revenue.Further, we propose a mathematical formulation of the extra-bandwidth allocation problem that maximizes network revenue. The solution of this model allows to obtain an upper bound on the performance achievable by any on-line bandwidth allocation algorithm.We demonstrate through simulation in realistic network scenarios that the proposed dynamic allocation algorithms are superior to static provisioning in providing resource allocation both in terms of total accepted load and network revenue, and they approach, in several network scenarios, the ideal performance provided by the mathematical model.     

Game Theoretic subcarrier and power allocation for wireless OFDMA networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.     

认知无线电中能效优化的子载波匹配策略

针对协作认知无线电系统中的能量效率问题,提出一种以最大化能量效率为目标的资源联合分配算法。在满足服务质量要求和功率约束的情况下,首先通过一种能量效率优先的启发式方案对子载波进行匹配,再引入基于拉格朗日对偶算法对其中的功率分配问题进行非线性优化,从而最大限度地提高整个系统的能量效率。仿真实验结果表明,所提算法的能量效率得到显著提升,验证了所提方案的有效性。     

协作式云资源博弈分配

针对用户对云资源的异构性需求和竞争问题,提出了一种协作式资源分配博弈策略。建立了资源分配的协作式博弈模型,定义了协作博弈的用户效用函数和评估函数,证明了在该效用函数下协作博弈存在唯一Nash均衡,并讨论了用户组建联盟对协作特征函数和整体效用的影响。实验结果表明,在该协作博弈策略下,个体用户通过组建联盟集体出价的方式,能够为联盟用户带来更大效用,以收敛方式实现Pareto改进。     

QoS-Aware Tethering in a Heterogeneous Wireless Network using LTE and TV White Spaces

Wireless networks have resource limitations; in a dense area, cellular spectrum resources are insufficient and affect the system performance. A Long Term Evolution (LTE) network aims to serve heterogeneous users with different QoS requirements. Traditional approaches need new infrastructure and degrade performance of delay sensitive applications, which may result in users with minimum rate requirements being in high blocking probability. To utilize wireless resources efficiently, users want to access the same medium to connect with the same multicast group and be overhauled at the same time. In this paper, a new technique is proposed for operator-controlled called the QoS-Aware Tethering in a Heterogeneous Wireless Network using LTE and TV White Spaces (QTHN) to improve QoS for Constant Bit Rate (CBR) and Best Effort (BE) users. The proposed QTHN converts the whole dense wireless network into hexagonal clusters via two layer network communication. In a cluster, one node is selected as a cluster head and all other nodes act as slaves. Within a cluster, a cluster head acts as an access point known as a Hotspot (H), which is further connected to the Base-station (BS). The proposed QTHN aims to improve QoS within heterogeneous wireless network using LTE and unused White Spaces in a wireless dense area. Simulation results show that the proposed QTHN reduced the numbers of blocked users and improved network utility.     

Resource allocation algorithm with limited feedback for multicast single frequency networks

The single frequency network (SFN) can provide a multimedia broadcast multicast service over a large coverage area. However, the application of SFN is still restricted by a large amount of feedback. Therefore, we propose a multicast resource allocation scheme based on limited feedback to maximize the total rate while guaranteeing the quality of service (QoS) requirement of real-time services. In this scheme, we design a user feedback control algorithm to effectively reduce feedback load. The algorithm determines to which base stations the users should report channel state information. We then formulate a joint subcarrier and power allocation issue and find that it has high complexity. Hence, we first distribute subcarriers under the assumption of equal power and develop a proportional allocation strategy to achieve a tradeoff between fairness and QoS. Next, an iterative water-filling power allocation is proposed to fully utilize the limited power. To further decrease complexity, a power iterative scheme is introduced. Simulation results show that the proposed scheme significantly improves system performance while reducing 68% of the feedback overhead. In addition, the power iterative strategy is suitable in practice due to low complexity.