基于HAGA的D2D-NOMA资源分配优化算法

针对无线系统带宽资源有限、基站负载压力大、传输时延长等问题,提出一种基于非正交多址接入技术的D2D系统吞吐量最大化资源分配算法。在不同用户的服务质量约束条件下,建立D2D系统吞吐量最大化资源分配模型。该模型的优化目标是一个混合整数非线性规划问题,将其解耦为信道匹配与功率分配2个子问题并分别进行处理,利用自适应惩罚函数法处理约束条件并提出一种基于爬山策略的自适应遗传算法以对问题进行求解。仿真结果表明,与GA、AGA算法相比,该算法能够有效提高D2D系统的吞吐量,且收敛性能更好。     

基于家庭基站密度的自适应无线资源分配策略

针对飞蜂窝(又叫家庭基站)中干扰严重、资源利用率低等问题,提出一种基于家庭基站密度的自适应无线资源分配策略。通过频率分割抑制宏蜂窝与飞蜂窝间的干扰,依托资源复用和功率控制抑制飞蜂窝之间的干扰,并基于自组织网络技术实现家庭基站接入点(FAP)的自动配置。仿真和性能分析表明,策略在最大限度提高无线资源利用率的同时,基本实现了零干扰,并将系统总吞吐量提高了20%;尤其适用于家庭基站密集或无线资源紧张的应用场合。     

无线MIMO系统的上行资源分配算法研究

在存在同信道干扰的无线MIMO系统中,为具有多种QoS需求的调度业务分配资源是一个具有挑战性的问题.提出一种实用的、基于SDMA的贪婪资源分配(SGRA)算法.在高效的干扰管理基础上,SGRA算法可以执行两阶段启发式计算和搜索.在第1阶段,包括上行调度和子信道分配的贪婪资源分配首先在时域频域二维进行;在第2阶段,资源分配被扩展到时域频域空域三维进行.SGRA的算法复杂度低,适用于实际无线通信系统.仿真结果表明,与同类算法相比,SGRA算法可以提高系统吞吐量,更好地保证实时业务的时延和最小数据速率需求,同时兼顾系统公平性.     

基于功率控制的无线Mesh网络拓扑控制

针对无线Mesh网络中由于无线信号干扰而造成的端到端吞吐量并不理想问题,提出一种采用功率控制构造无线Mesh网络拓扑的算法,通过调整节点的传输功率到一个合理的水平来降低干扰以提高信道的空间复用度,从而改善网络的吞吐量。结合流量模型和干扰模型计算整个网络的吞吐量。仿真结果表明,该拓扑控制能够提高无线Mesh网络的吞吐量。     

5G超密集异构网络带内无线回传资源分配方案

为实现5G超密集异构网络中无线回传链路和接入链路之间的最优资源分配,研究多用户场景下双层异构网络的联合用户调度和功率分配问题,在队列稳定和无线回传资源有限的情况下,综合考虑用户调度、功率分配和干扰控制等因素,对带内无线回传的最优资源分配问题进行数学建模并求解,基于李雅普诺夫优化理论提出联合用户调度和功率分配的优化算法。将优化问题解耦为网络内各个用户的调度以及宏基站和小基站的功率分配过程,采用MOSEK求解器和二分类方法获得用户调度向量,利用拉格朗日乘子法求解功率分配问题,并通过队列的时刻更新过程实现最优资源分配。仿真结果表明,在多用户场景下,该方案能够有效提升网络总吞吐量以及网络效用,并且毫米波频段的通信性能优于传统蜂窝网络频段。     

异构蜂窝网络中功率和资源分配博弈算法研究

基于D2D和中继异构蜂窝网络进行资源复用可获得系统性能增益,但同时也使得网络中的干扰更加复杂。针对该问题,提出功率和资源分配博弈（PRAG）算法,通过功率控制和资源分配对D2D和中继异构蜂窝网络进行干扰协调。基于代价参数设定D2D和中继链路效用函数,确定最佳发射功率。在此基础上,将生成的效用值矩阵参与博弈,选择合适的蜂窝用户进行资源复用。仿真结果表明,与等功率分配随机（EPAR）算法相比,PRAG算法能够在消耗更少功率的基础上获得更大的系统吞吐量。     

Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference

Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms.     

Adaptive joint bandwidth and power allocation in heterogeneous wireless access environment

Joint bandwidth and power allocation for a multi-radio access(MRA)system in a heterogeneous wireless access environment is studied.Since both the number of users being served by the system and the wireless channel state are time-varying,the optimal resource allocation is no longer a static optimum and will change with the varying network state.Moreover,distributed resource allocation algorithms that require iterative updating and signaling interactions cannot converge in negligible time.Thus,it is unrealistic to assume that the active user number and the wireless channel state remain unchanged during the iterations.In this paper,we propose an adaptive joint bandwidth and power allocation algorithm based on a novel iteration stepsize selection method,which can adapt to the varying network state and accelerate the convergence rate.A distributed solution is also designed for the adaptive joint resource allocation implementation.Numerical results show that the proposed algorithm can not only track the varying optimal resource allocation result much more quickly than a traditional algorithm with fixed iteration stepsize,but can also reduce the data transmission time for users and increase the system throughput.     

OFDMA techniques in multicellular networks with total frequency reuse

Orthogonal frequency division multiple access (OFDMA) techniques are investigated in this paper. Five subchannel allocation algorithms are analysed and their performance in a multicellular environment is evaluated with simulations. Four schemes of lower complexity, suitable for the early deployment of wireless systems, are compared with a more computationally demanding scheme with respect to their blocking probability, loading factor and offered bit rate. The channel condition of each carrier is calculated and its knowledge is used for power controlled adaptive modulation, as an essential feature of the OFDMA technique. The general radio resource management process is divided into two steps: in the first step a base station allocates carriers to users while in the second step the modulation and power levels for each allocated carrier are defined.The simulation results demonstrate that a wireless system in its early deployment phase (up to 15–30% blocking probability) can employ simple OFDMA techniques capable of achieving high throughput. Furthermore, it is demonstrated that two of the proposed lower complexity schemes, (those based on cell coordination), offer good performance gain for higher data rate services. Nevertheless, these schemes achieve relatively lower gains with adaptive modulation, when compared with the techniques which exploit interference averaging or adaptive interference mitigation.     

Data traffic scheduling algorithm for multiuser OFDM system with adaptive modulation considering fairness among users

Orthogonal frequency division multiplexing (OFDM) is regarded as a very promising digital modulation technique for achieving high rate transmission. However, the increasing number of wireless data users and the deployment of broadband wireless networks have brought about issues of fairness among users and system throughput. In this paper, we propose an efficient scheduling algorithm to maximize system throughput while providing a level of fairness among users for non-real-time data traffic in the downlink of a multiuser OFDM system. We establish a practical scheduling procedure to implement our scheme considering fairness among users and also formulate the resource allocation problem for rate, power, and subcarrier allocation as an integer program that maximizes system throughput. Next, we present a computationally efficient heuristic algorithm for a problem based on the Lagrangian relaxation procedure. Through the computing simulation, we show that the proposed scheme performs better than other schemes in terms of both system throughput and fairness among users.     

Game theoretic distributed uplink power control for CDMA networks with real-time services

In this paper, the issue of efficient power allocation in the uplink of CDMA wireless networks supporting real-time services with various QoS constraints, is addressed. Within the proposed framework, utility functions are adopted to reflect a user’s degree of satisfaction with respect to its actual throughput requirements satisfaction and respective power consumption. The corresponding problem is formulated as a non-cooperative game where users aim selfishly at maximizing their utility-based performance under the imposed limitations. The existence and uniqueness of a Nash equilibrium point of the proposed Uplink Power Control (UPC) game is proven, at which all users have attained a targeted SINR threshold value or transmit with their maximum power, leading essentially to an SINR-balanced system. Moreover, a distributed iterative algorithm for reaching UPC game’s equilibrium is provided. The properties of equilibrium in a pure optimization theoretical framework are studied, and the tradeoffs between users’ overall throughput performance and real-time services’ QoS requirements satisfaction, in channel aware resource allocation processes, are revealed and quantified. Through modeling and simulation the efficacy of the introduced framework and proposed UPC algorithm are demonstrated and evaluated.     

超密集网络中基于干扰协调的资源分配算法

超密集网络中,严重的小区间干扰制约了终端用户的数据速率,针对该问题,该文提出一种基于干扰协调的资源分配方案。该方案分为两个模块：第一模块基于毫微微接入点(Femtocell Access Points, FAPs)间的干扰程度,将干扰强的FAPs分到同一簇内,同簇内的FAPs共享频带资源,通过FAPs间的协作使不同簇之间实现频谱的复用;第二模块基于最大功率和最低速率的公平性准则进行最优功率分配,动态分配资源。仿真结果表明,该算法在超密集网络场景下能够有效控制FAPs间的干扰,最大化系统吞吐量。     

M-CORD下无线接入网络资源分配研究

针对M-CORD架构将传统的无线接入网络解耦并虚拟化的特征,考虑软件定义网络（SDN）的集中控制和全局监测作用,研究无线接入网侧资源的动态分配及优化问题。将数据中心的计算资源纳为资源分配考虑因素之一,综合干扰阈值、前传网络容量限制、用户移动性、服务最低资源保障以及计算资源限制五方面,推导出M-CORD架构下无线接入网资源分配公式,通过改进基于增量的贪心分配算法,求得资源分配的次优解。仿真结果验证了改进算法在M-CORD架构下对无线接入网资源分配的适用性。     

多速率CDMA系统下行波束成形的联合多变量优化

下行波束成形能用来限制由于高速率数据用户引起的干扰，也能改善系统性能。另一方面，功率控制、数据速度分配也是改善无线多媒体通信频谱利用率的两种基本技术。在文章里，阐述了DS—CDMA系统中给定系统吞吐量和软的目标SIR门限值条件下，下行波束成形权值和数据速率的优化问题。基于上面的内容，给出了一种改进的IVPW算法，可以将其应用于未来的无线通信系统，为所有用户提供稳定的最大吞吐量。     

一种自适应跨层空间子信道分配算法——基于多用户MIMO／OFDM系统

MIMO／OFDM是未来宽带无线通信接口的有效架构。本文提出了一种自适应跨层空间子信道分配算法，在多用户MIMO／OFDM系统中，联合链路层截短ARQ（T-ARQ）技术，以获取物理层最大的系统吞吐量为目标，推导了子载波分配准则，并给出了相应的算法流程。仿真结果表明，该算法具有良好的性能，有效地提高了系统的传输速率。     

基于认知OFDM系统的功率分配算法

在正交频分复用的认知无线电系统中,授权用户会受到认知用户频带内子载波带外功率泄漏的干扰。针对这一问题,提出了一种基于幂函数分布的次优化功率分配方案,通过线性约束的凸优化数值运算,有效降低了最优方案中运算的复杂度。给出了在认知用户发射功率约束条件下的信道吞吐量分析。仿真结果表明,所提出的方案在满足授权用户干扰门限约束条件下,提高了现有功率分配方案的认知用户信道吞吐量。     

Optimal user scheduling and power control in multi-user cognitive broadcast systems

Cognitive radio systems should not only have the ability to sense and exploit "frequency spectrum holes",but also the ability to sense and utilize "spatial spectrum holes".In this paper,we consider the issue of maximizing the throughput of the cognitive systems by fully utilizing "spatial spectrum holes" brought in by multiple cognitive users,in the scenario where a pair of licensed users and a cognitive broadcast system share multiple spectrum bands.By exploiting the channel reciprocity under the premise that the licensed system adopts the time-division-duplexing (TDD) mode,we propose a more practical cognitive access scheme that can sense the interference at the licensed user caused by the cognitive transmitter,based on the existing feedback signals from the licensed user to the licensed base station.Taking both interferences from the licensed base station to the cognitive receiver and from the cognitive transmitter to the licensed user into consideration,we investigate the optimal user scheduling and power allocation scheme that can maximize the ergodic sum rate of the cognitive system.We show that scheduling the user whose channel gain to interference and noise ratio (CGINR) is the largest for each frequency band is optimal.We also derive the dynamic power allocation scheme meeting the three practical constraints,i.e.,the transmitter’s average transmission power constraint,the power amplifier’s instantaneous transmission power constraint,and the interference power constraint at the licensed user.The result shows that in different coherent time intervals and different frequency bands,the power allocation has a multi-level waterfilling structure.Theoretical analysis shows that the strategy scheduling user with the largest CGINR introduces significant performance improvement compared with the traditional strategy scheduling user with the largest channel gain to noise ratio (CGNR).We also illustrate the impact of power constraints and the number of users on system performance by simulation.     

e-MAC:一种面向Ad Hoc网络的高吞吐量MAC协议

解决ad hoc网络中隐藏节点问题、暴露节点问题的最终目的是减少节点间的冲突,提高网络空间复用率,从而提高网络吞吐量.现有MAC协议在解决隐藏节点问题时着重于彻底消除网络中的隐藏节点,忽略了网络空间复用率,即使能够彻底解决隐藏节点问题,也不能有效提高网络吞吐量.同样,现有协议在解决暴露节点问题时着重于如何允许暴露节点并行发送数据,忽略了暴露节点接收数据的问题,也影响了网络空间复用率.提出了一种高效的MAC协议e-MAC,协议采用两种方法提高网络空间复用率:首先,协议中接收节点根据接收到发送节点的信号强度动态调整忙音发射功率,使忙音恰好覆盖所有的隐藏节点,在彻底解决隐藏节点问题的同时,提高网络空间复用率;其次,隐藏节点接收到RTS消息后,通过判断RTS消息信号强度与信道中干涉信号的强度之比来决定是否接收数据,允许满足信噪比要求的接收节点接收数据,进一步提高网络空间复用率.仿真结果验证了协议的有效性,在任意拓扑结构下,e-MAC协议的平均吞吐量比DUCHA(dual channel access)协议高87%.     

认知无线电网络非协作博弈功率分配算法研究

发现干扰节点,并将功率适当地分配至各个可用频谱上,以提高节点数据率和网络吞吐量,是认知无线电网络当前的研究热点.本文提出一种基于非协作博弈功率分配方法(PANG),以提高认知无线网络系统吞吐量.PANG将认知网络节点功率分配问题转化为非协作博弈问题,并采用线性代价因子的方法抑制功率分配时的盲目性.理论分析表明,PANG存在纳什均衡点,具有帕累托最优解.本文使用Matlab对PANG算法进行仿真,仿真结果表明,PANG算法能够比PIWF算法更加合理的进行功率分配,并有效的提高系统吞吐量.     

QoS scheduling of uplink resources in OFDMA networks

Orthogonal frequency division multiple access (OFDMA) transmission is the technology of choice for fourth generation (4G) wireless networks (802.16, 3GPP and 3GPP2). In both uplink and downlink directions, resources can be allocated in three dimensions, frequency, time and power. The uplink resource allocation problem is more complicated due to the limited transmission power of the subscriber stations (SS). In this paper we consider the uplink resource allocation problem for generic OFDMA wireless networks and derive the optimal scheduler taking into account constraints, such as quality of service (QoS), that were not considered in previous works.