无线传感器网络中支持并行传输的信道与功率联合优化博弈算法

针对无线传感器网络中干扰日益增大引起网络容量下降、能耗增加的问题,该文建立了信道分配与功率控制联合优化博弈模型。在该模型中链路将既能保持自身成功传输又不影响其它链路传输的信道作为可选信道,以实现链路的并行传输。继而基于该模型设计了一种支持并行传输的信道分配与功率控制联合优化博弈算法(JCPGC)。该算法利用最佳响应策略对模型求解,并通过超模博弈等理论证明了JCPGC能够收敛到纳什均衡。此外,该算法充分考虑信道分配和功率控制之间独立又相互影响的关系提高了网络容量。仿真实验结果表明,JCPGC具有大容量、低干扰和低能耗的特性。     

无线传感器网络基于容量和传输能耗的功率与信道联合博弈算法

针对无线传感器网络(WSNs)日益增大的干扰导致网络容量下降的问题,同时考虑到网络能量有限性,该文综合网络容量和链路传输能耗,构建了高容量低传输能耗的功率控制与信道分配联合博弈模型,并通过理论分析证明该模型存在最优功率和最优信道。继而采用最佳响应策略,在该博弈模型基础上提出了一种功率控制与信道分配联合优化算法(PCOA),理论证明其能收敛到纳什均衡状态,且具有较小的信息复杂度。最后,仿真结果表明,PCOA算法能够达到降低网络干扰和链路能耗,增大网络容量的目的。     

基于节点密度的混合式多信道分配算法

为了减小无线传感器网络中的同频干扰和避免网络堵塞问题,文章提出了一种基于节点密度的混合式多信道分配算法。该算法通过考虑链路干扰以及节点密度等因素,来解决局部严重同频干扰问题,实现各信道负载均衡,减少网络阻塞。仿真实验结果分析表明,该算法能有效地解决网络中同频干扰问题,较好地均衡各信道的网络负载,在数据业务较重的情况下,网络性能仍比较良好。     

基于GRU和LSTM组合模型的车联网信道分配方法

针对车联网中高通信需求和高移动性造成的车对车链路(Vehicle to Vehicle, V2V)间的信道冲突及网络效用低下的问题,提出了一种基于并联门控循环单元(Gated Recurrent Unit, GRU)和长短期记忆网络(Long Short-Term Memory, LSTM)的组合模型的车联网信道分配算法。算法以降低V2V链路信道碰撞率和空闲率为目标,将信道分配问题建模为分布式深度强化学习问题,使每条V2V链路作为单个智能体,并通过最大化每回合平均奖励的方式进行集中训练、分布式执行。在训练过程中借助GRU训练周期短和LSTM拟合精度高的组合优势去拟合深度双重Q学习中Q函数,使V2V链路能快速地学习优化信道分配策略,合理地复用车对基础设施(Vehicle to Infrastructure, V2I)链路的信道资源,实现网络效用最大化。仿真结果表明,与单纯使用GRU或者LSTM网络模型的分配算法相比,该算法在收敛速度方面加快了5个训练回合,V2V链路间的信道碰撞率和空闲率降低了约27%,平均成功率提升了约10%。     

基于PSO的D2D蜂窝网络联合信道分配和功率控制

为解决蜂窝用户(Cellular Users, CU)和终端直通(Device to Device, D2D)用户之间的干扰管理问题,提高无线蜂窝网络吞吐量,提出了一种基于粒子群优化的联合信道分配和功率控制方案。提出了具有不同约束条件的2个联合信道分配和功率控制问题,并将离散信道和连续功率联合分配给CU和D2D对,允许任意数量的D2D对与一个CU共享同一信道。通过设计适应度值避免算法陷入局部最优或产生不可行的解决方案,并使算法收敛到全局最优。通过搭建仿真网络模型进行测试验证,并与随机粒子群优化算法进行对比分析。实验结果表明,所提方法可有效提高蜂窝网络中的D2D通信网络吞吐量,且与随机粒子群优化算法相比,所提方法在D2D吞吐量、蜂窝吞吐量以及整体网络吞吐量方面具有明显优势。     

同频异构femtocell联合子信道和功率分配算法

摘要：针对macro-femto同频融合网络中基于资源分配的干扰抑制问题,提出一种联合子信道和功率分配算法来抑制同频干扰。该算法通过对MU进行功率控制并采用跨层切换消除同频跨层干扰,对FU进行联合信道和功率分配消除同频层内干扰;跨层切换问题是在每一层网络目标中断概率约束下通过优化网络吞吐量实现,而基于联合信道和功率分配的同频干扰抑制问题是在切换MU的目标数据速率和其他MU以及FU干扰门限约束下,通过优化FU的和速率实现。理论分析和仿真结果表明,该算法能够提高FU的和速率,增大femtocell的网络容量,并可增加femtocell的部署数目。     

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。     

无线Mesh网络集中式信道分配算法设计

以集中式无线Mesh网络(WMN)为基础,分析和研究了传统多信道分配算法,并在此基础上提出了以节点优先级和分组为特点的多接口多信道分配算法(Channel Assignment based on Rank of Node and Link group,CAR-NL),该算法结合节点分级和链路负载预期评估机制,通过节点链路分组按级分配信道。通过仿真实验表明,该算法能有效提高无线Mesh网络多业务流并发执行时系统整体吞吐量,并实现较低的丢包率。     

基于反向链路状态的动态优化信道分配

本文提出了一种基于反向链路载干比的信道分配优化模型.这种模型较原有的兼容矩阵模型更接近实际系统,并且能够应用于分析干扰自适应信道分配方案.本文在提出这种模型的同时,对比了该模型和原有模型在描述信道分配问题的精度和能力上的优劣.此外,本文还提出了使用改进遗传算法求解该模型下信道分配问题的方法.分析和实验均说明本文提出的模型对实际环境进行了更精确的描述,通过使用这种模型求解信道分配问题能够更好利用信道资源.     

认知网络中基于中继的频谱资源分配

根据无线认知中继网络上、下行链路子载波的信道特性,研究认知网络的频谱资源分配,提出一种上、下行链路子载波联合优化的分配算法。该算法根据子信道增益差值因子的大小分配下行链路子载波,以源节点和中继节点功率最小化为优化目标配对上行链路子载波,以用户的实时需求分配子载波的比特和功率,有效降低了系统的发射功率,提高了系统吞吐量。仿真结果表明,与启发—集中式和分布式辅助反馈传输功率分配算法比较,该联合优化算法的单位比特功耗降低了1.5~3 dBμW,误比特率性能提高了1个数量级左右。     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

基于拓扑分割的无线Mesh网络信道分配策略

该文根据无线Mesh网络流量呈现树状拓扑汇聚的特点提出基于拓扑分割的信道分配策略。依据无线干扰对不同链路的影响程度,把无线干扰分类为有确定方向的纵向干扰和横向干扰;提出沿着纵向干扰方向逐跳分割网络拓扑算法;提出最少信道隔离纵向干扰和为吞吐量最小的子拓扑增加信道的子拓扑间信道分配策略;提出横向干扰分块的子拓扑内信道使用方法;理论分析子拓扑内的冲突域及网络性能瓶颈,仿真研究子拓扑的吞吐性能及信道分配顺序。仿真结果表明,隔离纵向干扰和增加信道的分配策略能够有效保证和提升网络吞吐量,横向干扰分块的方法优于802.11s中定义的公共信道框架多信道机制。     

基于混沌神经网络的移动通信信道分配方法研究

该文应用混沌神经网络求解信道分配问题,给出了信道分配的能量函数表达式和混沌神经网络模型,研究了判别混沌神经网络混沌特性的Lyapunov指数法,讨论了网络模型参数对网络混沌特性的影响,提出了基于混沌神经网络的信道分配算法.仿真结果表明,混沌神经网络具有复杂的瞬态混沌特性,它比Hopfield网络具有更强的搜索全局最优解的能力,和更快的收敛速度.     

Virtually fixed channel assignment in cellular mobile networks with recall and handoffs

A promising approach for implementing channel assignment and control in cellular mobile telephone networks is the virtually fixed channel assignment (VFCA) scheme. In VFCA channels are allocated to cells according to the fixed channel assignment (FCA) scheme, but cells are allowed to borrow channels from one another. As such, VFCA maintains the efficiency of FCA, but adds the flexibility lacking in FCA. One feature of a VFCA network is that, to prevent co-channel interference, it requires several channels to be locked to serve a single call that borrows a channel. This feature raises the concern that VFCA may lead to chain reaction in channel borrowing among cells and cause the network performance to degrade, especially under heavy traffic conditions. In this paper, we propose the virtually fixed channel assignment with recall (VFCAWR) scheme: The network is implemented according to VFCA, but a cell can recall a locked channel to service an arriving handoff call, which occurs when a mobile unit crosses the boundary of its cell. We model the network as a three-dimensional Markov chain and derive its steady-state performance. Through modification of this basic model, we evaluate two dynamic channel assignment strategies, the virtual channel reservation (VCR) strategy and the linear switch-over (LSO) strategy, which exploit the unique borrowing/recall capability of VFCAWR to reduce the weighted cost of blocking fresh and handoff calls by reserving several virtual channels (the channels that may be borrowed from adjacent cells when necessary) for handoff calls. We validate the analytical models by simulation; the simulation test cases show that our models accurately predict the system performance measures of interest. Numerical and simulation results also show that both dynamic strategies outperform conventional channel reservation schemes based on fixed channel assignment and hybrid channel assignment. This revised version was published online in June 2006 with corrections to the Cover Date.     

Reverse Link Performance of DS-CDMA Cellular Systems through Closed-Loop Power Control, Base Station Assignment, and Antenna Arrays in 2D Urban Environment

The interference reduction capability of antenna arrays, base station assignment, and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm and base station assignment method based on minimizing the transmitter power (BSA-MTP) technique for direct sequence-code division multiple access (DS-CDMA) receiver in a 2D urban environment. This receiver consists of conjugate gradient adaptive beamforming and matched filter in two stages using antenna arrays. In addition, we study an analytical approach for the evaluation of the impact of power control error (PCE) on the DS-CDMA cellular systems. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly improve the network bit error rate in comparison with conventional methods. Our proposed methods can also significantly save total transmit power and extend battery life in mobile units. In addition, we show that the convergence speed of the SSPC algorithm is faster than that of conventional algorithms. Finally, we discuss two parameters of PCE and channel propagation conditions (path-loss parameter and variance of shadowing) and their effects on the capacity of the system via some computer simulations.     

Distributed channel assignment combined with routing over multi-radio multi-channel wireless mesh networks

In order to realize the reduction of equipment cost and the demand of higher capacity,wireless mesh network(WMN) router devices usually have several interfaces and work on multi-channels.Jointing channel allocation,interface assignment and routing can efficiently improve the network capacity.This paper presents an efficient channel assignment scheme combined with the multi-radio link quality source routing(MR-LQSR) protocol,which is called channel assignment with MR-LQSR(CA-LQSR).In this scheme,a physical interference model is established:calculated transmission time(CTT) is proposed as the metric of channel assignment,which can reflect the real network environment and channel interference best,and enhanced weighted cumulative expected transmission time(EWCETT) is proposed as the routing metric,which preserves load balancing and bandwidth of links.Meantime,the expression of EWCETT contains the value of CTT,thus the total cost time of channel assignment and routing can be reduced.Simulation results show that our method has advantage of higher throughput,lower end-to-end time delay,and less network cost over some other existing methods.     

An efficient channel assignment algorithm for multicast wireless mesh networks

Multicast can enhance the performance of wireless mesh networks (WMNs) effectively, which has attracted great attentions in recent years. However, multicast communication in WMNs requires efficient channel assignment strategy to reduce the total network interference and maximize the network throughput. In this paper, the concept of local multicast is proposed to measure interference and solve hidden channel problem in multicast communication. Basing on the concept, we propose a channel assignment algorithm considering the interference of local multicast and forwarding weight of each node (LMFW). The algorithm fully considers partially overlapped channels and orthogonal channels to improve the network performance. Simulations show that the proposed algorithm can reduce interference and improve network capacity of WMNs.     

认知MIMO系统中改进的干扰信道学习算法

针对认知MIMO系统中认知用户获知干扰信道的问题,提出了一种改进的盲信道学习算法。该算法用循环雅可比方法估计干扰信道矩阵的零空间,其参数是利用主用户的功率控制机制,通过二分搜索法获得。然后以抑制认知用户对主用户的干扰为目标,提出在学习过程中动态调整二分搜索精度的方法来改善算法收敛性能。理论分析和仿真结果表明,所提算法比BNSL算法收敛速度明显加快,信道学习过程中对主用户的干扰有明显改善。      

A non-cooperative game-theoretic approach to channel assignment in multi-channel multi-radio wireless networks

Channel assignment in multi-channel multi-radio wireless networks poses a significant challenge due to scarcity of number of channels available in the wireless spectrum. Further, additional care has to be taken to consider the interference characteristics of the nodes in the network especially when nodes are in different collision domains. This work views the problem of channel assignment in multi-channel multi-radio networks with multiple collision domains as a non-cooperative game where the objective of the players is to maximize their individual utility by minimizing its interference. Necessary and sufficient conditions are derived for the channel assignment to be a Nash Equilibrium (NE) and efficiency of the NE is analyzed by deriving the lower bound of the price of anarchy of this game. A new fairness measure in multiple collision domain context is proposed and necessary and sufficient conditions for NE outcomes to be fair are derived. The equilibrium conditions are then applied to solve the channel assignment problem by proposing three algorithms, based on perfect/imperfect information, which rely on explicit communication between the players for arriving at an NE. A no-regret learning algorithm known as Freund and Schapire Informed algorithm, which has an additional advantage of low overhead in terms of information exchange, is proposed and its convergence to the stabilizing outcomes is studied. New performance metrics are proposed and extensive simulations are done using Matlab to obtain a thorough understanding of the performance of these algorithms on various topologies with respect to these metrics. It was observed that the algorithms proposed were able to achieve good convergence to NE resulting in efficient channel assignment strategies.