OFDM系统频率选择性信道功率分配方案

自适应分配技术根据子信道的瞬时估计值动态地分配传输比特数和发送功率,可以优化正交频分复用（OFDM,Orthogonal Frequency Division Multiplex）系统的整体性能。这里讨论了基于容量优化的自适应比特分配算法,基于误比特率优化的最佳功率分配算法和次佳功率分配算法。仿真结果表明,对不同信道环境下三种算法的特点和性能进行了分析和比较。仿真结果表明,自适应分配技术可以优化系统的容量和误比特率。     

GPON中一种二端动态带宽分配算法的设计与分析

首先对GPON中现有的动态带宽分配算法进行了阐述,然后提出了一种有效QoS保证的二端动态带宽分配算法,并给出了该算法的实现流程图.接着针对几种负载下的不同业务吞吐量情况对该算法进行了分析,最后得出了该算法可以满足动态带宽分配公平性的结论.     

基于博弈论的多雷达多目标分配方法研究

根据雷达网作战需求和作战任务分配准则,以雷达网目标分配效益为目标函数,对雷达网目标分配问题进行了建模,利用潜博弈理论进行了分析,并证明了纳什均衡的可行性、存在性和最优性。基于最佳动态反应设计了迭代目标分配策略选择算法,并分析了算法的复杂度。仿真结果表明:该目标分配策略选择算法具有很好的收敛性,能够在较短时间内寻求近似最优解。当不存在最大目标探测容量限制时,该算法能够获得与穷举法相同的性能。分配决策模型和算法合理便捷,可以较好地解决雷达网多目标分配问题,对实际作战指挥有一定的指导意义。     

基于差值分配的信道分配算法研究

资源的高效利用与服务质量保证是多频时分多址(MF-TDMA)卫星通信系统正常运行的关键技术。通过对典型的周期轮询信道分配算法进行分析,针对该算法实时业务掉线率较高的缺点,提出了差值分配算法。新算法是在周期轮询信道分配算法的基础上,结合业务带宽需求动态变化的特点,将业务带宽申请分为固定部分与差值部分并分别采取不同的分配策略。仿真结果表明,新算法可以有效地降低实时业务的掉线率。     

OFDM系统中多用户组合调制自适应比特分配算法

本文针对多用户OFDM系统,将其信道分配和比特分配相结合,提出了更优的OFDM多用户组合调制自适应分配算法(M CABA)。该算法在系统总的传输速率一定和满足传输质量的基础上,与现有的OFDM自适应算法相比,可以获得更优的功率、信噪比性能和频率效应。并对该算法进行了理论分析和M atlab6.5.1系统仿真。     

802.11无线网状网中基于时频信道的准动态信道分配算法

该文首次在多天线多信道802.11无线网状网中提出了时频信道的概念。时频信道是通过在时间和频率两个维度划分无线资源取得的。这种划分方法增加了信道数量,使信道划分更加精细,为提高系统的信道利用率做了准备。在时频信道的基础上,提出了准动态信道分配算法。该算法可以和现有的固定信道分配算法结合,实现准动态信道分配,根据链路上负载变化,取得最大的吞吐量。该算法先根据固定信道分配算法为各链路分配相同数量的时频信道,剩余部分当作公共信道。在通信过程中,各链路首先使用分配给自己的信道和空闲的公共信道。如果分配给一个链路的信道不够,且别的链路上的信道有空闲,该链路还可以暂时使用这些空闲信道。理论分析和仿真结果证明该算法可以有效提高系统的吞吐量。     

优先级保护的分布式动态频谱分配算法

对认知无线网络中动态频谱分配算法进行了研究,在分析原有的ADP（Asynchronou s Distributed Pricing）算法的前提下,运用合作博弈的理论提出了具有干扰价格因子的A DP算法,分配过程中所有用户发布自己的干扰价格,用户在选择信道和功率的时候需要考虑 到自身的效用和对其它用户的干扰,可以在有效保证高优先级用户性能的前提下最大化网络 效用。仿真结果表明,该算法可以达到纳什均衡并且具有极快的收敛速度,可以提高高优先 级用户的信干噪比。     

MIMO-OFDM系统自适应高效功率分配

基于注水算法和Campello算法的基本思想,提出了一种新的多输入多输出-正交频分复用（MIMO-OFDM）系统自适应混合高效功率分配算法。该算法先基于注水算法采用速率最大化准则计算开关信道的临界值,并对功率进行一次分配,然后基于Campello算法对剩余功率进行再次分配。仿真表明：此高效算法可以实现对信道子载波的功率和比特有效分配,且系统的性能比Campello算法有所改善,并且随着收发天线的增加系统性能逐渐提高。     

GPON系统中基于QoS的动态带宽分配算法的研究

为了实现吉比特无源光网络(GPON)带宽分配的公平性,降低网络的丢包率及传输延时,研究了GPON系统传输汇聚层的帧结构及带宽分配的实现方法,提出了一种新的动态带宽分配(DBA)算法--基于QoS的二层动态带宽分配算法.性能分析与对比表明,这种算法对不同用户和不同等级的业务都具有很好的公平性,并可以降低低等级业务的传输延时.     

区分服务的资源分配算法在OFDMA-PON中的应用

通过研究OFDMA-PON中基于区分服务的资源分配算法,提出固定子载波分配和动态子载波分配两种算法,针对其中的参数进行研究并对二者的性能进行了比较。结果表明,两种算法均可以保证高优先级业务的性能,固定分配算法计算复杂度低,更适合高负载网络;动态子载波分配算法则在低负载时能有效提升系统性能。     

基于用户需求的改进型CSGC频谱分配算法

针对基于图论着色模型的频谱分配算法目前未能很好解决用户自身需求这一重要问题,研究了基于用户需求的改进型颜色敏感的图论着色(Color Sensitive Graph Coloring,CSGC)频谱分配算法。该算法通过降低已满足需求用户的分配优先级,使系统未满足的带宽需求总量达到最小化,在保证原CSGC算法性能的同时,较好地实现了频谱分配与自身需求相匹配。仿真结果表明该算法是有效的。     

多用户分布式MIMO-OFDM系统中天线与子载波分配算法研究

本文针对多用户分布式MIMO-OFDM系统中的资源联合分配问题,提出了一种基于端口选择的天线与子载波分配算法。该算法依据计算复杂度容限设定用户通信静态端口数,以此为每个用户选取信道状况最好的通信端口进行通信,进而通过天线端口与下属用户的相互配合,并行地完成天线与子载波的分配。仿真结果表明,该算法在系统天线数大于用户数的情况下容量性能优于MASA算法,且其端口并行处理机制可以有效提高资源分配效率。     

可重构分组密码指令集处理器自动映射方法研究

计算资源与寄存器资源分配是可重构处理器自动并行映射的重要问题,该文针对可重构分组密码指令集处理器的资源分配问题,建立算子调度参数模型和处理器资源参数模型,研究了分组密码并行调度与资源消耗之间的约束关系;在此基础上提出基于贪婪思维、列表调度和线性扫描的自动映射算法,实现了分组密码在可重构分组密码指令集处理器上的自动映射。通过可用资源变化实验验证算法并行映射的有效性,并对AES-128算法的映射效果做了横向对比验证算法的先进性,所提自动映射算法对分组密码在可重构处理中的并行计算研究有一定的指导意义。     

Distributed SNR-Based Power Allocation in Wireless Parallel Amplify-and-Forward Relay Transmissions Using Cournot Game

In wireless communications, power allocation plays a paramount role in sustainable network lifetime prolongation with quality-of-service and network interference reduction. This paper investigates a distributed power allocation problem in wireless parallel amplify-and-forward (AF) relay transmissions. Particularly, the objective is set to minimize the total transmit power while guaranteeing the signal-to-noise ratio (SNR) requirement at the destination node. The distributed SNR-based power allocation problem is formulated and modeled as a Cournot game. Moreover, a distributed SNR-based power allocation algorithm is proposed to solve the Cournot game. The proposed distributed SNR-based power allocation algorithm is proved to converge to a unique equilibrium. To evaluate the distributed method, a centralized optimal SNR-based power allocation algorithm is also proposed. Numerical results show that the proposed distributed SNR-based power allocation algorithm can achieve comparable performance to the centralized optimal SNR-based power allocation algorithm.     

动态频谱分配的连通分支并行处理

关键词快速无干扰的动态频谱分配是实现认知无线电的关键技术之一。针对现有图论频谱分配算法均存在时间开销过大这一瓶颈问题,引入并行原理和连通分量理论,提出了一种连通分支并行处理新方法。该方法可应用于目前所有基于图论着色模型的分配算法,在保证算法原有效益的基础上,能够显著降低频谱分配过程的时间。研究了连通分支并行处理方法的应用实例,结果验证了该方法是快速有效的,更加适应时变的认知无线电环境。     

Design and analysis of parallel file downloading algorithms in peer-to-peer networks

It is well known that the method of parallel downloading can be used to reduce file download times in a peer-to-peer (P2P) network. There has been little investigation on parallel download and chunk allocation for source peers with random service capacities. The main contribution of this paper is to address the problem of efficient parallel file download in P2P networks with random service capacities. A precise analysis of the expected download time is given when the service capacity of a source peer is a random variable. A general framework is developed for analyzing the expected download time of a parallel download and chunk allocation algorithm, and is applied to the analysis of several algorithms. Two chunk allocation algorithms for parallel download are proposed. It is observed that the performance of parallel download can be significantly improved by using the method of probing high-capacity peers. One such algorithm is proposed and its expected parallel download time is analyzed. The performance of these parallel file download algorithms in P2P networks with random service capacities are compared. The above parallel download algorithms are extended to multiple file download by dividing source peers into clusters. It is noticed that there is an important issue of optimal parallelism which minimizes the combined effect of intracluster and intercluster overhead of parallel download and load imbalance.     

Dual-target WOA spectrum sharing algorithm based on Stackelberg game

In order to solve the complex spectrum allocation problem,a dual-target whale optimization algorithm (WOA) with strong parallel computing capabilities was introduced,and a Stackelberg game model was proposed that could effectively reflect the actual spectrum requirements,and a dual-target WOA optimized distributed antenna system (DAS) spectrum sharing scheduling algorithm was designed.Simulation results show that performance comparison is performed from multiple indicators such as optimal pricing and user benefits.The proposed algorithm has a good spectrum sharing allocation effect,can achieve fair and effective spectrum allocation,and provides an important reference for the future communication network spectrum sharing mode.     

Memory binding for performance optimization of control-flow intensive behavioral descriptions

This paper presents a memory binding algorithm for behaviors, used in application-specific integrated circuits (ASICs), that are characterized by the presence of conditionals and deeply nested loops that access memory extensively through arrays. Unlike previous works, this algorithm examines the effects of branch probabilities and allocation constraints. First, we demonstrate, through examples, the importance of incorporating branch probabilities and allocation constraint information when searching for a performance-efficient memory binding. We also show the interdependence of these two factors and how varying one without considering the other may greatly affect the performance of the behavior. Second, we introduce a memory binding algorithm that has the ability to examine numerous bindings by employing an efficient performance estimation procedure. The estimation procedure exploits locality of execution, which is an inherent characteristic of target behaviors. This enables the performance estimation technique to look at the global impact of the different bindings, given the allocation constraints. We tested our algorithm using a number of benchmarks from the parallel computing domain. A series of experiments demonstrates the algorithm's ability to produce bindings that optimize performance, meet memory allocation constraints, and adapt to different resource constraints and branch probabilities. One limitation of our algorithm is that, in its current form, it is not well suited for system-on-a-chip synthesis where there is complex communication between general-purpose microprocessors that use custom-designed arrays. Results show that the algorithm requires 41% fewer memories with a performance loss of only 0.2% when compared to a parallel memory architecture. When compared to the best of a series of random memory bindings, the algorithm improves schedule performance by 22%.     

Capacity enhancement of a multi-user OFDM system using dynamic frequency allocation

A dynamic subcarrier allocation algorithm is developed and studied in order to improve the capacity of a multi-user OFDM system in the downlink environment. The proposed algorithm uses a decentralized approach and considers the instantaneous channel response of each user in parallel. In order to reduce the complexity of the system, the available subcarriers are divided into a number of partitions and the algorithm attempts to allocate the partition with the highest average channel gain to each user. However, situations may arise whereby two or more users attempt to select the same partition. As such, an important aspect of the algorithm is to resolve such conflicts. Based on the above allocation plan, adaptive modulation is employed for each user on the allocated partitions. The results obtained show that the proposed dynamic allocation scheme outperforms a static allocation scheme in terms of a lower BER and a higher system capacity for the same SNR. In addition, it is possible to obtain performance improvements at the expense of an increase in the system complexity by dividing the subcarriers into a larger number of partitions.     

认知无线电网络中基于协作中继的资源分配算法

在认知无线电网络的协作中继机制下,中继节点利用其和源节点以及目的节点的不同公共信道为二者的通信转发数据,可以有效解决次用户的通信需求和可用带宽之间的矛盾,提高频谱利用率和系统吞吐量。基于协作中继的认知无线电网络中,不同通信链路上可能存在公共可用信道,使信道和中继的分配问题变得复杂。本文研究了公共信道存在的情况下系统的资源分配问题,基于网络最大流理论提出了两种算法:并行算法和贪婪算法,并分析了算法复杂度。仿真结果表明,两种算法都能够更有效地分配资源,提高频谱利用率,改善网络吞吐量。并行算法可以得到最优解,但其复杂度随信道公用程度的上升增长迅速,受节点并行处理能力的限制,只适用于信道公用程度较低的情况。贪婪算法不一定能得到最优解,但其复杂度较低,并且信道公用程度高时接近最优解,因此超出节点的并行处理能力后,可以选择贪婪算法。