基于干扰消减的认知无线电频谱分配算法

在认知无线电网络的频谱分配过程基础上,提出了一种基于干扰消减的频谱分配算法.该算法通过将可用频谱分配给能够同时无干扰地接入同一频谱的所有认知用户来提高授权频谱的使用率.同时,该算法参考各个认知用户在初始阶段的可用频谱数量来为未分配到频谱资源的认知用户进行频谱分配,对频谱分配过程的公平性进行了优化.仿真结果表明,该算法能够在认知用户数量较多、可用频谱紧张的情况下获得较高的吞吐量.     

宽带多小区蜂窝网络中频谱功率分割机制

该文考虑小区间业务均匀分布,提出了频谱功率分割(Frequency Power Partition,FPP)机制:小区间频率复用因子为1,2/3的频谱为低功率频谱,剩余频谱为高功率频谱,且相邻小区的高功率频谱相互正交。结合FPP特点,从吞吐量和公平性角度出发,分别提出了基于影响度的频谱分配(Influence-based Frequency Allocation,IFA)算法和基于收益与影响度的频谱分配(Profitability-and-Influence based Frequency Allocation,PIFA)算法。最后考虑到小区内用户和业务分布的不均匀性,设计了一种简单的功率控制机制。仿真和分析结果表明与软频率复用(SFR)相比,FPP＋IFA和FPP＋PIFA分别使系统吞吐量和公平性得到较大改善,且功率控制机制进一步提高了用户和业务分布不均匀时的系统吞吐量。     

OFDM系统Femtocell网络下行联合资源分配

为进一步提高家庭基站(Femtocell)网络中频谱利用率并优化功率分配,在基于正交频分复用技术(OFDM)系统网络中,提出一种子载波联合优化的多用户资源分配算法,即以最大化频谱利用率作为目标函数,加入基站选择因子对家庭基站进行待机模式选择优化,再对用户的子载波资源进行公平分配,最后利用线性封顶注水算法对小区基站用户功率进行优化分配。仿真结果表明,多用户资源分配算法不仅使频谱和功率利用率都得到显著增长,而且提高了系统吞吐量和用户公平性。该家庭基站资源寻优模型有效地改善了频谱紧缺和功率浪费现状,降低了家庭基站之间的干扰。      

一种基于流量需求的动态频谱分配算法

感知无线电是一个解决当前频谱资源紧缺情况的有效手段,其中动态频谱分配技术是一个非常重要的环节.文章首先建立了基于冲突图的需求分配模型,基于此模型提出了一种基于用户需求的动态频谱分配算法,在传统标签机制基础上增加了对感知用户随时间改变的频谱需求的支持.试验结果表明,当每个感知用户对频谱的需求随着时间的变化而变化并且为有限值的情况下,该算法能保证较好的公平性和提供较高的分配效率.     

认知无线电频谱分配新算法研究

构造了一个基于合作博奕的非对称纳什协商效能函数,并通过2个认知用户间协商子载波的使用,实现了基于感知贡献加权的比例公平性频谱分配的新算法。仿真结果表明提出的方案不仅实现了频谱资源的公平有效分配,而且有利于频谱感知的最大化。     

WRAN系统的频谱分配算法

IEEE802.22工作组的工作范围是对工作在54～862MHz的VHF/UHFTV频带内的固定点对多点无线区域网（WRAN）制定基于认知无线电的空中接口。频谱资源分配是WRAN中的关键技术,目前对认知无线电的频谱分配算法的研究多集中在比较广义的范围,对WRAN等具体系统的频谱分配研究较少。根据WRAN的特点和OFDM的传输特性,提出一种OFDM多用户资源分配算法：多载波比例公平算法（MPF）和最大化吞吐量算法（KH）的组合算法（KH＆MPF）,该算法将最大化吞吐量算法和多载波比例公平算法进行优势互补,得到公平性和吞吐量都次优的结果,解决用户之间的公平性问题,考虑用户的Qos要求。最后对该算法进行仿真。     

基于服务公平性感知的弹性光网络动态频谱分配算法

针对弹性光网络中的业务服务公平性问题,从不同粒度、不同跳数业务之间的服务公平性两方面,分别提出了相应的公平性感知动态频谱分配算法.通过引入新的效用函数,使得进行频谱分配时不仅考虑不同粒度、不同跳数业务间的服务公平性,而且还兼顾网络整体的频谱资源利用率,从而大大缓解了网络整体阻塞性能损伤.仿真结果表明,在动态网络环境下,针对不同粒度、不同跳数的业务的公平性问题所提出的方案可以极大地提高弹性光网络中业务之间的服务公平性,并且没有明显的阻塞性能恶化.     

一种基于非对称纳什协商的认知无线电频谱共享新算法

该文研究基于MIMO-OFDMA的认知无线电系统频谱共享的新机制。首先构造了一个基于非对称纳什协商方案的效能函数,其次通过多用户最优匹配及两两协商新算法并证明其收敛性,最终实现了基于感知贡献加权的比例公平性频谱共享。仿真结果表明提出的方案不仅实现了频谱资源的公平有效分配,而且有利于最大化频谱感知的结果。     

基于图论模型的改进型频谱分配算法

认知无线电技术能够感知周围无线电环境并择机使用频谱空洞。文章通过对现有的频谱分配算法研究分析,提出了基于图论着色模型的改进型频谱分配算法。该算法建立在授权用户状态动态变化的基础上,利用频谱下一时刻空闲概率降低授权用户的活动性对频谱分配的影响。仿真结果表明该算法有效提高了频谱概率上的效益并且保证了系统公平性。     

认知无线网络中基于用户需求和频谱聚合的动态频谱分配

认知无线电技术可以感知周围无线环境择机利用频谱空洞,从而达到提高频谱效率的目的.在认知无线电网络中,现有的频谱分配算法大部分是基于连续频谱分配并且没有考虑用户的需求.但是连续频谱分配会生成许多小于用户需求的频谱片段,这些频谱片段不能被充分利用,从而造成频谱浪费.本文基于图论提出了一种联合考虑用户需求和非连续频谱聚合的频谱分配算法.在该算法中,非连续的频谱片段被聚合以尽可能多地满足用户总需求,充分利用了小的频谱片段,避免了频谱浪费,从而提高频谱效率.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

无线供电混合多址接入网络的资源分配

无线供电技术是延长无线网络节点寿命的有效方案。该文研究一个由基站和多个分簇用户组成的无线供电混合多址接入系统。系统的传输分为两个阶段。在第1阶段,基站向用户广播能量;在第2阶段,用户向基站传输信息。用户簇和用户簇之间采用时分多址接入,分时传输;同一簇内多个用户采用非正交多址接入,同时传输。该文研究联合优化系统的各阶段的传输时间、基站的发射功率、用户的发射功率等资源,分别以优化网络频谱效率和用户簇之间的公平性为目的,提出最大化网络吞吐量和最大化用户簇的最小吞吐量的联合资源分配算法。研究结果表明所提的两种算法分别能有效提高系统的频谱效率和保证用户簇之间的公平性。     

认知无线电系统中基于多标拍卖的信道分配机制

为在认知无线电系统中实现对频谱的有效管理,文中提出了一种基于多标拍卖的信道分配机制,并给出了三种分配规则:吞吐量最大规则、效用公平规则以及时间公平规则.最后通过仿真验证了三种分配规则下的系统性能,仿真结果说明,进行信道分配时利用吞吐量最大规则能使系统吞吐量达到最大,采用效用公平规则能达到最佳效用公平性.使用时间公平规则可保证用户在为传输文件而竞争频谱资源过程中的时间公平,且文件的平均传输时间最少、时延最小.     

Fairness based resource allocation for uplink OFDMA systems

This article investigates two fairness criteria with regard to adaptive resource allocation for uplink orthogonal frequency division multiple access （OFDMA） systems. Nash bargaining solution （NBS） fairness and proportional fairness （PF） are two suitable candidates for fairness consideration, and both can provide attractive trade-offs between total throughput and each user＇s capacity. Utilizing Karush-Kuhn- Tucker （KKT） condition and iterative method, two effective algorithms are designed, to achieve NBS fairness and proportional fairness, respectively. Simulation results show that the proposed resource allocation algorithms achieve good tradeoff between the overall rate and fairness, with little performance loss from the total capacity.     

Proportional fair scheduling with superposition coding in a cellular cooperative relay system

Many works have tackled on the problem of throughput and fairness optimization in cellular cooperative relaying systems. Considering firstly a two-user relay broadcast channel, we design a scheme based on superposition coding (SC) which maximizes the achievable sum-rate under a proportional fairness constraint. Unlike most relaying schemes where users are allocated orthogonally, our scheme serves the two users simultaneously on the same time-frequency resource unit by superposing their messages into three SC layers. The optimal power allocation parameters of each SC layer are derived by analysis. Next, we consider the general multi-user case in a cellular relay system, for which we design resource allocation algorithms based on proportional fair scheduling exploiting the proposed SC-based scheme. Numerical results show that the proposed algorithms allowing simultaneous user allocation outperform conventional schedulers based on orthogonal user allocation, both in terms of throughput and proportional fairness. These results indicate promising new directions for the design of future radio resource allocation and scheduling algorithms.     

基于MADDPG的无人机辅助通信功率分配算法

针对多无人机(unmanned aerial vehicle, UAV)作为空中基站辅助通信的吞吐量和公平性问题,提出了一种基于多智能体深度确定性策略梯度算法(multi-agent deep deterministic policy gradient algorithms, MADDPG)的功率分配算法,该算法通过联合优化UAV基站的功率分配和用户接入以提高系统吞吐量和公平性。本文首先构建了UAV基站为地面建立通信服务的三维场景,然后通过联合功率、用户关联和UAV位置约束,构建了吞吐量和公平性最大化的问题模型。考虑到该问题的复杂性,本文将所构建的优化问题建模为马尔科夫决策过程(Markov decision process, MDP),通过引入深度确定性策略梯度算法(deep deterministic policy gradient algorithm, DDPG)解决该问题。仿真结果表明,本文提出的基于MADDPG的UAV基站功率分配算法与其他算法相比,可以有效地提升系统的吞吐量和用户的公平性,提高通信的服务质量。     

Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks

Both spectrum sensing and power allocation have crucial effects on the performance of wireless cognitive ad hoc networks. In order to obtain the optimal available subcarrier sets and transmission powers, we propose in this paper a distributed resource allocation framework for cognitive ad hoc networks using the orthogonal frequency division multiple access (OFDMA) modulation. This framework integrates together the constraints of quality of service (QoS), maximum powers, and minimum rates. The fairness of resource allocation is guaranteed by introducing into the link capacity expression the probability that a subcarrier is occupied. An incremental subgradient approach is applied to solve the optimization problems that maximize the weighted sum capacities of all links without or with fairness constraints. Distributed subcarrier selection and power allocation algorithms are presented explicitly. Simulations confirm that the approach converges to the optimal solution faster than the ordinary subgradient method and demonstrate the effects of the key parameters on the system performance. It has been observed that the algorithms proposed in our paper outperform the existing ones in terms of the throughput and number of secondary links admitted and the fairness of resource allocation.     

Joint overlay and underlay resource allocation with weighted fairness in OFDM‐based cognitive radio systems

In this paper, the problem of hybrid overlay and underlay spectrum access is investigated for OFDM‐based cognitive radio (CR) systems. Both the metrics for system (e.g. capacity) and users (e.g. fairness) are integrated into the unified framework of weighted‐capacity maximization with the interference constraint in CR systems. For easing the procedure of resource allocation, two criteria, respectively, for subcarrier assignment and power allocation are theoretically derived based on the Karush–Kuhn–Tucker conditions. Under the guidance of the two criteria, max‐capacity subcarrier assignment and optimal power allocation are proposed to flexibly distribute spectrum resources to secondary users. In order to reduce the computational complexity further, a suboptimal power allocation algorithm, referred to as cap‐limited waterfilling, is also presented by decomposing the interference constraint. Simulation results show that the capacity and fairness performance of the proposed algorithms is considerably better than the conventional ones in references. The proposed suboptimal algorithm with substantially lower complexity approaches to optimal power allocation in the vicinity of only 1% performance gap. Meanwhile, joint access model is greatly beneficial to spectrum efficiency enhancement in CR systems. Copyright © 2014 John Wiley & Sons, Ltd.