LTE-A多小区中继网络两跳速率匹配资源分配算法

针对中继网络的两跳特性,提出一种多小区中继网络两跳速率匹配资源分配算法。首先,在第一个子时隙内各小区独立地为小区中所有用户分配子载波,并根据子载波分配结果,建立基于非合作博弈的功率分配模型;然后,由第一跳资源分配结果对第二跳速率匹配,自适应地为中继分配资源以满足边缘用户的速率需求。仿真结果表明,该算法在满足边缘用户速率需求的前提下,进一步提高了中心用户的吞吐量,同时降低了系统的发射功率,从而提升了系统性能。     

基于非合作博弈的OFDMA无线多跳中继网络上行链路资源分配算法

研究了基于OFDMA多址技术的无线多跳中继网络上行链路资源分配问题。首先,在最大发射功率等约束条件下,建立了多小区OFDMA无线多跳中继网络上行链路的资源分配优化模型。将非合作博弈论和定价机制引入后,该优化问题可转化为在每个子信道上独立地进行功率分配。基于非合作博弈的功率分配模型中的纳什均衡点的存在性和唯一性得到了证明,并给出了具体的分布式求解算法。仿真结果表明,所提算法能在大幅减少系统总发射功率的情况下,有效地提升系统吞吐量,达到较高的能效比。     

一种基于多小区OFDMA系统用户公平性约束的分布式资源分配算法

针对多小区OFDMA系统下行链路,研究了用户公平性约束下的资源分配问题,提出了一种多基站协作的迭代优化的分布式资源分配算法。每个小区根据干扰状况及用户公平性,迭代地进行子载波和功率的资源优化;而每次迭代中,根据用户公平性准则分配子载波,并将非凸的小区功率优化问题转化为其下界的凸问题,通过一个分布式算法来求解。通过仿真验证了算法的有效性;仿真结果表明,与传统网络的固定功率分配的情形相比,所提算法保证了用户之间的公平性并显著提高了系统吞吐量。     

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。     

基于博弈论的OFDMA系统多小区功率协调分配算法

提出了一种用于正交频分多址(OFDMA)通信系统下行链路的多小区功率协调分配算法,协调相邻小区在同频子信道上的发送功率,抑制小区间干扰,提高信道容量.将博弈论引入到多小区功率分配中,给出基于定价的多小区非合作功率分配博弈模型,并分析了该博弈的纳什均衡解的存在性和惟一性,给出了该模型的分布式求解算法.通过仿真分别给出了单小区场景与多小区场景下算法性能,讨论了定价因子对系统性能的影响.仿真结果表明,提出的多小区功率协调分配算法可以充分利用无线资源,提高系统吞吐量,降低平均发送功率.     

优化公平性的多用户OFDM系统下行链路资源分配算法

研究了优化公平性的多用户OFDM系统下行链路的资源分配算法,根据系统各用户的业务需求,在保证用户所得数据速率满足一定比例以及系统总功率限制的前提下,提高系统总数据速率。首先,根据公平性原则进行用户的子载波分配,子载波功率分配使用注水算法;子载波分配完成后,利用贪婪功率分配算法,以最大化用户数据速率和提高功率利用率为目标,对各用户内部子载波功率和比特数进行再分配。仿真结果表明,相比参考文献[10]的算法,该算法在提高系统总速率的同时,更好地保证了用户数据速率的公平性;相比参考文献[12]的算法,该算法虽然牺牲了一定的系统总速率,但能提供更高的用户数据速率公平性。     

一种提高小区边缘用户性能的多用户子载波功率分配策略

在OFDMA系统中,小区边缘用户由于受到来自相邻小区的同频干扰,通信质量严重下降.有效地抑制小区间干扰,极大地提升无线网络性能尤其是小区边缘用户性能是5G移动通信系统的目标之一.基于速率自适应(RA)准则提出了一种提高小区边缘用户性能的子载波和功率的联合资源分配算法,该算法分为子载波分配和混合功率分配两步,在提高小区边缘用户性能的同时,最大化链路吞吐量.仿真结果表明,小区边缘用户吞吐量增益为25％以上,混合功率分配下的系统吞吐量逼近全部用户使用注水法时的系统吞吐量,并且降低了运算复杂度.     

多小区放大转发系统基于用户公平性的分布式资源分配

全频率复用的OFDMA系统中,小区间干扰严重降低了整个系统,特别是小区边缘的频谱效率。文中考虑了多小区放大转发系统下行链路的资源管理,须联合优化用户调度、载波和功率的分配,并设计了一个分布式的资源分配算法,算法基于本小区局部信息分步完成用户调度和功率控制,小区之间只需要较少的交互信息。仿真结果表明,文中算法较传统算法具有更好的系统性能。     

OFDMA系统下行链路自适应带宽与子载波分配方案

该文分析了OFDMA系统下行链路自适应资源分配问题,在系统总功率约束下提出了最小化系统中断概率的次最佳两步子载波分配算法。首先分析用户带宽分配与子载波功率分配特点,在此基础上提出了根据系统可用资源、用户QoS要求及信道状态为用户分配带宽和子载波的两步分配算法。仿真结果表明,该文提出的算法能在极小化系统中断概率的同时满足总功率约束。     

基于子载波配对的多用户协作中继系统资源分配算法

针对多用户协作中继系统中的功率最小化问题,提出了一种基于联合子载波配对及分配的资源分配算法。首先根据不同用户的目标速率要求及平均信道增益进行子载波数目的分配;然后以信道条件最佳为准则,提出了一种联合子载波配对及分配的多用户迭代算法,以实现对每个用户的中继链路和直传链路分别进行子载波配对及虚拟配对;最后利用注水算法对子载波进行功率分配,从而保证各用户以最小功率进行传输。仿真结果表明,该算法在满足用户目标速率的情况下,能够进行有效的子载波配对及分配,从而最小化系统的发射功率。     

基于用户画像与关联规则的全域电力资源调度算法

为解决应用调度算法进行全域电力资源调度,资源剩余率依旧较高的问题,提出结合用户画像与关联规则的新型调度算法,实现全域电力资源的合理分配。运用双聚类算法,对整个调度区域内所有用户用电数据进行分析,构建电力用户画像从而描述用户用电个性化需求;以用户画像为基础,建立以满足用户需求为核心的全域资源分配模式;总结全域内资源调度子任务,计算不同子任务之间的支持度和置信度,结合关联规则实现子任务的分组;根据子任务组进行资源分域,在每个分域中设置二级调度中心,再与全域一级调度中心相连接,实现全域资源集中调度。实验结果表明,所提调度算法应用后,电力测试系统每日的全域资源剩余率出现了大幅降低,仅保持在12%左右。该算法具有较好的实际应用价值。     

Scheduling and Resource Allocation Strategy for OFDMA Systems Over Time-Varying Channels

A cross-layer scheduling and resource allocation (SRA) strategy for an adaptive modulation and coding (AMC) based orthogonal frequency multiple access (OFDMA) system is proposed. The objective of this paper is to maximize the system throughput as a function of the bit error rate (BER) and the spectral efficiency based on the selected modulation and coding schemes (MCSs). The proposed strategy contains two main algorithms. Firstly, the scheduling algorithm that aims to maximize the average system throughput by arranging the users in distinct queues according to their priorities and selecting the best user of each queue individually in order to guarantee a fair user service amongst different priority levels. Secondly, the resource allocation algorithm that allocates the user, bit and power based on the channel conditions of the scheduling users and the transmission power constraints. The transmitter of the investigated AMC-OFDMA system at the assigned base station (BS) divides the transmitted OFDMA frame into sub-channels and assigns each sub-channel to a scheduled user. In this paper, we compare the performance of the proposed SRA with the conventional first in first out (FIFO) queuing based scheduling and resource allocation strategies used for an AMC-OFDMA system. The simulation results show that the investigated AMC-OFDMA system based on the proposed SRA strategy outperforms the conventional approaches.     

Competitive Resource Sharing Based on Game Theory in Cooperative Relay Networks

This letter considers the problem of resource sharing among a relay and multiple user nodes in cooperative transmission networks. We formulate this problem as a sellers’ market competition and use a noncooperative game to jointly consider the benefits of the relay and the users. We also develop a distributed algorithm to search the Nash equilibrium, the solution of the game. The convergence of the proposed algorithm is analyzed. Simulation results demonstrate that the proposed game can stimulate cooperative diversity among the selfish user nodes and coordinate resource allocation among the user nodes effectively.     

面向电网业务质量保障的5G高可靠低时延通信资源调度方法

该文研究面向电网业务质量保障的5G 高可靠低时延通信(URLLC)的资源调度机制,以高效利用低频段蜂窝通信系统内有限的频谱和功率资源来兼顾电力终端传输速率和调度时延、调度公平性,保障不同电力业务的通信质量（QoS）。首先,基于URLLC的高可靠低时延传输特性,建立电力终端多小区下行传输模型。然后,提出面向系统下行吞吐量最大化的资源分配问题模型并对其进行分步求解,分别提出基于定价机制与非合作博弈的功率分配算法和基于调度时延要求的改进比例公平算法（DPF）动态调度信道资源。仿真结果表明,提出的资源调度方法能在保证一定传输可靠性和公平性的条件下降低电力终端调度时延,满足不同业务等级的QoS需求,与已知算法对比有一定的优越性。     

Distributed Scheduling and Dynamic Pricing in a Communication Network

This paper studies dynamic resource allocation in a decentralized communication network. The temporal aspect in the decentralized resource allocation problem presents new challenges, e.g., in optimizing the delay-throughput trade-off under user-specific delay costs. A dynamic bandwidth allocation game modelling an agent-based network is presented. The dynamic noncooperative game achieves Pareto-efficient bandwidth allocation that can be implemented by a greedy algorithm with pricing. Optimal dynamic pricing is discussed for the efficient sharing of network resources. An ad hoc wireless network is an example of such self-organizing decentralized system: the mobile nodes need not be directly connected to a base station. Another application of the model is to consider distributed uplink scheduling, based on local information, in a WCDMA network. The discretized control variable of a mobile node is either the received power/QoS-level or the binary decision on packet transmission.     

Dynamic Resource Allocation for Downlink Multiuser MIMO-OFDMA/SDMA Systems

In this paper, new dynamic resource allocation algorithms are investigated for the downlink of multiuser multiple-input multiple-output orthogonal frequency-division multiple-access and space-division multiple-access (MU-MIMO-OFDMA/SDMA) systems. Firstly, a mathematical formulation of the optimization problem is presented with the objective of maximizing the total system throughput under the constraints of each user’s quality of service (QoS) requirement and the integer modulation orders available on each spatial subchannel. Secondly, since it is difficult to obtain the optimal solution to the joint optimization problem, the whole optimization procedure is divided into two steps, namely, the subcarrier-user scheduling and the resource allocation. In the first step, a new metric is proposed to measure the spatial compatibility of multiple users, each with multiple receive antennas, based on which a new scheduling algorithm is designed to identify the optimal sets of selected users over all subcarriers. In the second step, two dynamic resource allocation algorithms are developed to assign radio resources to the scheduled users subcarrier by subcarrier. Simulation results demonstrate that the proposed algorithms outperform the traditional allocation methods based on random scheduling scheme. Especially, the performance of the algorithm, combined with power reuse strategy, approaches closely to that of the optimal allocation method based on user selection.     

多用户MIMO系统中的一种基于博弈论的功率控制

多输入多输出(MIMO)系统是未来移动通信热点技术之一。单小区多用户MIMO多接入系统性能受限于同信道干扰。该文提出了采用博弈论的分析方法,对系统进行分布式功率控制,优化系统资源配置。仿真结果表明,该文建立的非合作博弈模型是合理的,而分布式功率控制算法也是有效可行的。     

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.     

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Nonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)–based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real‐life scenarios is generally nonfull buffer. In this paper, we propose User Demand–Based Proportional Fairness (UDB‐PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time‐varying. UDB‐PF extends the PF‐based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network‐wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB‐PF yields better sum rate (throughput) while PUSF provides better network‐wide user satisfaction results compared with the PF‐based user scheduling. We also observed that the GA‐based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.