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。     

MIMO-OFDM系统中基于效用函数的跨层资源分配算法

针对多业务MIMO-OFDM系统的下行链路提出了一种基于效用函数的跨层资源分配算法.建立了以效用函数最大化为目的的跨层优化目标,分别设计了语音、流媒体和"尽力而为"三种业务的边界效用函数.算法首先在所有用户中分配子载波,然后进行单用户和空间子信道的功率、比特分配,并对比特数目进行取整处理.仿真结果表明算法满足了多种业务的QoS要求,对时延敏感的业务能提供更小的时延,同时对"尽力而为"业务提供了更高的吞吐量.     

HSDPA系统中一种感知用户终端缓存状态的QoE保障调度算法

针对HSDPA系统中现有调度算法无法满足实时业务QoE的缺点,提出一种保障实时业务QoE的调度算法。该算法根据用户反馈的信道质量信息和在基站获取到的用户终端缓存状况信息。确定用户的优先级并据此调度优先级最高的用户,进而保证实时业务的吞吐量和QoE需求。仿真结果表明,与轮询调度算法、比例公平调度算法相比,提出的调度算法不仅能够保证实时业务的QoE需求,而且能满足非实时业务基本的吞吐量需求。     

基于区分业务的OFDM跨层动态资源分配算法

跨层设计是目前比较流行的、有效的无线系统设计方法.本文针对多业务(实时业务和非实时业务)正交频分复用(OFDM)系统,提出了一种跨层结构的动态资源分配算法.该算法不仅在物理层上考虑信道状态信息和功率限制条件,而且在MAC层上针对不同类型业务采取不同的调度策略:(1)对于高优先级的实时业务,采用最大化容量的OFDMA策略,在频域上最大限度地利用多用户分集提高频谱效率,在时域上通过时隙的分配来保证时延边界;(2)对于低优先级的非实时业务,在频域上采用基于比例公平的OFDMA策略,在时域上尽力而为地分配时隙.仿真结果表明,与传统的单层资源分配算法相比,所提算法能够在保证不同业务服务质量(QoS)的前提下,大幅度地提高系统性能.     

正交频分多址系统中一种面向多业务应用的自适应资源分配算法

针对正交频分多址(OFDMA)系统下行链路多业务自适应调度的问题,该文首先以最大化系统吞吐量为优化目标、每种业务的服务质量(QoS)保证为约束条件,建立了一种通用的多业务自适应资源分配模型。为解决此优化问题,提出了一种具体的自适应资源调度算法。该算法对实时业务按照用户选择最好的信道的原则分配尽可能少的资源以保证其QoS,对非实时业务把尽可能多的剩余资源按照信道选择最好的用户的原则进行分配,充分利用信道资源,提升系统容量。仿真结果表明,该算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面有一定的优越性。     

OFDMA中继网络变时域节能资源分配策略

现有正交频分多址接入(OFDMA)中继网络资源分配的研究均采用固定时域配置下的频域分配和功率分配,不能很好适应用户业务在时域上的变化.该文针对OFDMA中继网络提出一种可最优节能的资源分配策略和一种简化的节能资源分配策略,为资源分配问题建立一般化的模型,即动态分配时域资源、频域资源和功率资源,所建模型具有很强的灵活性和适应性,不仅适用于固定时域分配系统,也适用于非固定时域分配系统.此外针对非满负荷业务,在保证用户服务质量的情况下,以节能为目标对无线非协作中继网络的资源分配进行能效最大化建模,使用拉格朗日乘数法对模型求解.考虑到算法复杂度,应用指派问题中的匈牙利算法设计出一种简化的资源分配策略.理论和仿真结果表明,最优节能资源分配算法能够得到能效的最大化,而简化节能资源分配算法与最优节能资源分配算法在能效上的差距不足5%,但算法复杂度得到了显著降低.而且,动态分配时域资源比固定时域分配对用户分布不均或链路分布不均有更强的适应性.     

多用户MIMO-OFDMA系统混合业务的跨层分组调度算法

该文提出了一种针对多输入多输出-正交频分多址系统混合业务的跨层分组调度算法。该算法基于物理层的信道状况和媒体接入控制子层用户的排队时延,分别为实时业务用户和非实时业务用户的排队时延构建相应的效用函数,以保障不同业务的服务需求。仿真结果表明:该算法不但能保证实时业务的时延需要,而且能够获得很好的吞吐量,并满足公平性要求。     

下行多业务OFDMA系统中基于有效容量的资源分配算法研究

该文对多业务OFDMA系统的下行链路资源分配进行了研究,侧重考虑了实时业务用户的QoS要求,建立2维马尔可夫无线信道模型,采用自适应调制技术、有效容量理论以及有效带宽理论,为实时用户分配资源;并实现了非实时业务用户、尽力而为业务用户的资源分配。仿真结果表明,所提算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面都有一定的优越性。     

云雾混合网络下基于多智能体架构的资源分配及卸载决策研究

针对D2D辅助的云雾混合架构下资源分配及任务卸载决策优化问题,该文提出一种基于多智能体架构深度强化学习的资源分配及卸载决策算法.首先,该算法考虑激励约束、能量约束以及网络资源约束,联合优化无线资源分配、计算资源分配以及卸载决策,建立了最大化系统总用户体验质量(QoE)的随机优化模型,并进一步将其转化为MDP问题.其次,该算法将原MDP问题进行因式分解,并建立马尔可夫博弈模型.然后,基于行动者-评判家(AC)算法提出一种集中式训练、分布式执行机制.在集中式训练过程中,多智能体通过协作获取全局信息,实现资源分配及任务卸载决策策略优化,在训练过程结束后,各智能体独立地根据当前系统状态及策略进行资源分配及任务卸载.最后,仿真结果表明,该算法可以有效提升用户QoE,并降低了时延及能耗.     

多波束赋形在非正交多址接入技术中的应用研究

为解决非正交多址接入(NOMA)技术在毫米波Massive MIMO系统中用户的分组受限于基站波束宽度的问题,提出了一种能够产生指向多个方向的波束的波束赋形方案.基于该多波束波束赋形方案,建立了多小区多用户场景下的用户资源分配的数学模型.为降低计算的复杂性,采用两阶段的资源分配算法.在第一阶段中,在给定的功率分配条件下将模型转化为联盟博弈中联盟的生成问题,并提出一种通过迭代确定用户分组和天线单元分配的算法;在第二阶段中,通过将非凸的数学优化问题转化为DC规划问题,提出用户功率分配的算法.仿真结果表明,本文所提多波束波束赋形方案能够有效产生指向多个方向的波束,且所提资源分配算法能够有效提高系统的性能.     

Wireless Packet Scheduling Algorithm for OFDMA System Based on Time‐Utility and Channel State

In this paper, we propose an urgency‐ and efficiencybased wireless packet scheduling (UEPS) algorithm that is able to schedule real‐time (RT) and non‐real‐time (NRT) traffics at the same time while supporting multiple users simultaneously at any given scheduling time instant. The UEPS algorithm is designed to support wireless downlink packet scheduling in an orthogonal frequency division multiple access (OFDMA) system, which is a strong candidate as a wireless access method for the next generation of wireless communications. The UEPS algorithm uses the time‐utility function as a scheduling urgency factor and the relative status of the current channel to the average channel status as an efficiency indicator of radio resource usage. The design goal of the UEPS algorithm is to maximize throughput of NRT traffics while satisfying quality‐of‐service (QoS) requirements of RT traffics. The simulation study shows that the UEPS algorithm is able to give better throughput performance than existing wireless packet scheduling algorithms such as proportional fair (PF) and modifiedlargest weighted delay first (M‐LWDF), while satisfying the QoS requirements of RT traffics such as average delay and packet loss rate under various traffic loads.     

Optimal resource allocation in multiservice CDMA networks

This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA/time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks.     

Traffic Aided Uplink Opportunistic Scheduling with QoS Support in Multiservice CDMA Networks

In this letter, we address the problem of resource allocation with efficiency and quality of service (QoS) support in uplink for a wireless CDMA network supporting real‐time (RT) and non‐realtime (NRT) communication services. For RT and NRT users, there are different QoS requirements. We introduce and describe a new scheme, namely, traffic aided uplink opportunistic scheduling (TAUOS). While guaranteeing the different QoS requirements, TAUOS exploits the channel condition to improve system throughput. In TAUOS, the cross‐layer information, file size information, is used to improve fairness for NRT users. Extensive simulation results show that our scheme can achieve high system throughput in uplink wireless CDMA systems, while guaranteeing QoS requirements.     

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 low-complexity beamforming-based scheduling to downlink OFDMA/SDMA systems with multimedia traffic

In this paper, we propose a low-complexity beamforming-based scheduling scheme utilizing a semi-orthogonal user selection (SUS) algorithm in downlink orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) systems to support multimedia traffic. One of the challenges in the multi-dimensional (space, time, and frequency) radio resource allocation problem for OFDMA/SDMA systems is its high complexity, especially to simultaneously satisfy the quality of services (QoS) requirements for various traffic classes. In the literature, the SUS algorithm is usually applied to the single-class traffic environment, but extending the SUS algorithm to the multimedia environment is not straightforward because of the need to prioritize the real-time (RT) users and the non-real-time (NRT) users. To solve this problem, we propose the concept of urgency value to guarantee the fairness of the NRT as well as the best effort (BE) users while satisfying the delay requirement for the RT users. Simulation results show that, when traffic load is greater than 0.5, the proposed scheduling algorithm can improve the fairness performance by more than 100% over the most recently proposed algorithms.     

Resource Allocation in OFDMA Wireless Communications Systems Supporting Multimedia Services

We design a resource allocation algorithm for downlink of orthogonal frequency division multiple access (OFDMA) systems supporting real-time (RT) and best-effort (BE) services simultaneously over a time-varying wireless channel. The proposed algorithm aims at maximizing system throughput while satisfying quality of service (QoS) requirements of the RT and BE services. We take two kinds of QoS requirements into account. One is the required average transmission rate for both RT and BE services. The other is the tolerable average absolute deviation of transmission rate (AADTR) just for the RT services, which is used to control the fluctuation in transmission rates and to limit the RT packet delay to a moderate level. We formulate the optimization problem representing the resource allocation under consideration and solve it by using the dual optimization technique and the projection stochastic subgradient method. Simulation results show that the proposed algorithm well meets the QoS requirements with the high throughput and outperforms the modified largest weighted delay first (M-LWDF) algorithm that supports similar QoS requirements.     

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.     

基于资源因子的电力线通信系统自适应资源分配

本文分析了电力线通信系统在每时隙内的最大总功率、各实时用户固定比特和非实时用户最小比特、各子载波允许最大功率和特定比特数的约束下,多用户多业务在多子载波上的自适应资源分配的多层多目标最优模型,并提出一种基于资源因子和用户优先级的功率和速率自适应相结合的资源分配算法。在典型电力线信道环境下其仿真结果表明,本文算法的性能忧于已有的多用户资源分配算法且能满足多用户多业务电力线通信资源分配的多目标要求。     

Caching resource management of mobile edge network based on Stackelberg game

Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobile edge caching technology from the perspectie of caching resource management by examining a network composed of one operator, multiple users and Content Providers (CPs). The caching resource management model is constructed on the premise of fully considering the QoE of users and the servicing capability of the Base Station (BS). In order to create the best caching resource allocation scheme, the original problem is transformed into a multi-leader multi-follower Stackelberg game model through the analysis of the system model. The strategy combinations and the utility functions of players are analyzed. The existence and uniqueness of the Nash Equilibrium (NE) solution are also analyzed and proved. The optimal strategy combinations and the best responses are deduced in detail. Simulation results and analysis show that the proposed model and algorithm can achieve the optimal allocation of caching resource and improve the QoE of users.