基于合约制的认知网络协作频谱共享模型

为了提高认知无线电网络中主用户的能效和谱效,提出了一种基于合约制的协作频谱共享新模型。在该模型中,当主用户信道质量差时,次用户为其提供中继服务;作为回报,在主用户信道质量好时,次用户可以在一定的干扰约束下以underlay的模式和主用户共享频谱。在此框架下引入经济学中的合约理论,将主次用户间的协作问题建模为合约设计问题,并建立了主次用户评价合约收益的效用函数,将提高主用户的能效和谱效问题转变为设计合约使主用户获得最大效用的优化问题,并利用差分进化算法对该问题求解。最后,在不同的环境下,将主用户协作与不协作获得的效用进行对比,结果表明,主用户在没有额外投入频谱资源的条件下,不仅节省了发送功率,而且有效地提高了数据传输速率,进而提高了能效和谱效。     

一种5G分布式联合传输策略研究

在5G超密集网络UDN部署的低功率节点覆盖下,小区覆盖重叠严重导致了小区间存在较大的同层干扰,由用户话务在时间和空间上分布不均匀而产生的小区负载不均衡造成了小区网络资源的严重浪费,小区用户体验大幅度降低。基于5G网络和TDD-CoMP技术的新特征,构建了一种以用户为中心的5G分布式联合传输模型,对模型中的干扰、功耗以及速率解决方案进行了分析,最后得出一种可有效降低系统能耗,提升用户整体的速率的5G分布式联合传输策略研究方案。     

基于半定规划方法的多个窃听用户认知网络物理层安全优化设计

针对具有多个多天线窃听者的认知无线电网络(CRN),为了使系统保密速率达到最大,该文把对主用户的干扰设计成为一个约束条件,通过对次用户发送端传输协方差矩阵的优化设计来提高物理层安全性能。在已知信道状态信息(CSI)时利用矩阵性质和Charnes-Cooper变换,将该非凸函数转化为一个半定规划(SDP),从而得到次用户发送端的优化方案。仿真结果表明,相对于现有二次优化传输策略,该方案能够使系统的保密速率更大,并在复杂度方面具有优势。     

基于帧重要性认知的网络差错控制策略

提出一种适用于认知网络的认知差错控制策略(CEC),该策略根据认知数据帧被转发所经历的跳数和类型的重要性智能地为丢失数据帧选择最佳差错控制机制来改善认知网络的通信性能。建立了认知网络能效模型,数学分析和仿真比较表明:该策略能够有效地提高认知网络多媒体数据传输的可靠性,同时保持高能效。     

基于边缘云计算的光纤无线网络优化设计

为了提升网络边缘数据处理能力,满足终端大带宽和低时延的要求,构建了基于边缘基础设施的云计算平台,设计了具有动态带宽调整的光纤网络模型。提出了一种基于边缘云计算的时序优化算法,并将其应用于光纤无线网络。通过OPNET软件仿真分析了时序优化算法的传输时延均值,结果显示,优化后最大时延为43.1 ms,仅为传统方法的34.2%。实验对局域网内多个终端之间的数据通信进行分析,讨论了三种算法的传输能效、光纤信道利用率及传输能耗。实验结果显示,采用时序优化算法的测试结果具有明显改善,其传输能效提升了近1倍,边缘云数据传输时延均值信道利用率提升了约6.2%,网络传输能耗均值最优。该光纤无线网络模型及其优化算法在传输时延、信道利用率以及网络能耗方面具有明显提升。其在提升光纤通信链路选择及边缘端数据交互中具有一定的优势。     

认知 mesh 网络服务区分的动态频谱接入策略

动态频谱接入策略是实现认知无线电网络高效利用频谱的关键。与传统认知无线电网络不同,认知mesh网络中不同QoS需求的多类型业务共同接入,为适应这一特点,提出服务区分的动态频谱接入策略。策略依据业务的QoS需求确立优先级,针对不同优先级业务采取不同的信道接入方案,实时业务依据最优传输延迟期望选择接入信道集合,在减小传输延迟的同时降低数据传输过程授权用户出现的概率,普通业务选择最优理想传输成功概率的信道,降低信道切换概率。理论与实验结果表明,与传统的认知网络频谱接入策略相比,提出的策略能提供不同业务的服务区分,满足实时业务的低延迟需求,降低数据传输的中断率,同时在授权信道空闲率与网络负载较大时吞吐量性能较优。     

面向业务的弹性光网络光路损伤感知能效路由策略

针对弹性光网络中物理损伤导致业务频谱利用率低和传输能耗高问题,该文提出一种面向业务的链路损伤感知频谱分区(LI-ASP)能效路由策略。在LI-ASP策略中,为降低不同信道间非线性损伤,基于负载均衡设计一个综合考虑链路频谱状态和传输损伤的路径权重公式,根据调制方式的频谱效率和最大传输距离构造分层辅助图,从最高调制等级开始,为高质量业务选择K条边分离的最大权重传输路径;为低质量业务选择K条边分离的最短能效路径。然后,LI-ASP策略根据业务速率比值对频谱分区,采用首次命中(FF)和尾端命中(LF)联合频谱分配方式,减少不同传输速率业务间的交叉相位调制。仿真结果表明,该文所提LI-ASP策略在有效降低带宽阻塞率的同时,减少了业务传输能耗。     

计弱连接条件下网络数据多信道传输节点路径调控方法

针对传统方法在计弱连接条件下调控网络数据传输路径时,无法均匀调整传输节点路径上的信息量,导致数据传输能耗较大且数据传输效率低,提出一种计弱连接条件下网络数据多信道传输节点路径调控方法。构建网络数据多信道传输节点模型,确定最佳的数据传输节点路径队列,使传输节点路径上的信息量均匀传输。利用信道分配的路径调控方法进行数据传输节点路径优化,有效降低数据传输能耗,提高了数据多信道节点传输效率,完成对计弱连接条件下网络数据多信道传输节点路径的调控。实验结果表明,该方法有效提高了数据多信道节点传输的效率,可有效解决传统方法存在的弊端,对该领域发展有着重要意义。     

无线传感器网络中一种基于OSTBC的高效协作传输技术

针对发端能量受限的无线传感器网络提出了一种基于OSTBC的高效虚拟MIMO协作传输策略.在无线传感器网络的每个簇内采用一种全速率的分布式OSTBC传输方案,同时对调制方式的星座大小进行优化,创建了一种更高效的无线传感器网络和MIMO通信相结合的模型.针对该模型在接收端进行迭代译码,并推导出该系统的总能耗函数和网络时延算式.通过仿真显示,该模型不仅能够极大的降低发端能耗,对任意协作节点数目均能够实现全速率传输,解决了传统分布式空时码用于无线传感器网络时发端的数据积压问题,减小了网络时延.因此本协作传输模型从能量消耗和网络时延两方面对无线传感网的性能进行了提升,能够为无线传感网的应用提供有意义的参考.     

感知频谱共享下的多天线功率优化分配算法研究

本文构建了一种在感知结果下具有多天线次用户的频谱共享模型,该模型由单入单出主用户对和多入单出认知用户对构成。当认知用户感知到主用户占用信道时,主用户向认知用户发送Message信息,使得认知用户发射端能够得知主用户对干扰总功率的限制要求,通过自适应地调整认知用户发射机的发射功率,以保证其对主用户不造成有害干扰;如果主用户未占用信道,认知用户立刻以最大发射功率占用信道。并分别在主用户存在和不存在两种情况下,优化认知用户发射机各天线的发射功率来最大化系统总的数据传输率。最后,通过数值仿真来验证推导出的功率分配策略,并对其进行分析和讨论。仿真结果表明:相比于机会频谱接入（Opportunistic Spectrum Access, OSA）和基于感知的频谱共享（Sensing-based spectrum sensing）模式,推导的功率分配策略在提出的模型中可以获得更高的信息传输率。      

无线EH认知物联网网络资源分配研究

由于5G技术的快速发展,基于能量采集的认知物联网(Internet of things,IOT)具有很大的应用前景.针对无线物联网网络中存在的"doubly-near-far"问题,考虑在认知物联网网络中将能量采集与信息接收站分开管理,提出了一个基于能量采集的异构认知物联网网络模型,实现用户能效的最大化.此外,该模型不...     

面向能量受限传感网的最优数据收集策略

本文研究了能量受限条件下无线传感器网络(wireless sensor networks,WSNs)的最优数据收集策略问题.首先,传感器节点周期性采集数据并通过卡尔曼滤波器(Kalman filter,KF)对信息进行预处理以滤除噪声.其次,考虑到通信为主要耗能环节,设计最优数据发送策略令节点在特定轮内发送数据,使得满足网络生存周期前提下,基站获得的数据精度最高.具体来说,针对单跳网络,给出可使基站误差方差最小化的数据发送策略;在此基础上,进一步提出面向多跳网络的改进数据发送策略.最后,利用仿真和原型实验验证所提策略的有效性.     

Research on energy-efficient physical-layer secure transmission mechanism in decode-and-forward cooperative networks

The maximization problem of secure energy efficiency (EE) in decode-and-forward relay networks was investigated considering the power and energy constraints in physical-layer secure transmission.An iterative algorithm for power allocation was proposed based on fractional programming and DC (difference of convex functions) programming.This algorithm jointly allocated power for source and relay nodes to achieve energy-efficient secure transmission,subject to the peak power constraint of each node and the minimum secrecy rate requirement of the system.Simulation results demonstrate that the propose algorithm can improve the secure EE significantly compared with the conventional secrecy rate maximization strategy.     

Energy harvesting,cooperative spectrum sensing,and data transmission improvement in energy‐efficient multichannel cognitive sensor networks

In this paper, we investigate the energy harvesting capability in a multichannel wireless cognitive sensor networks for energy‐efficient cooperative spectrum sensing and data transmission. Spectrum sensors can cooperatively scan the spectrum for available channels, whereas data sensors transmit data to the fusion center (FC) over those channels. We select the sensing, data transmission, and harvesting sensors by setting the sensing time, data transmission time, and also harvesting time to maximize the network data transmission rate and improve the total energy consumption in the multichannel network under global probability of false alarm and global probability of detection constraints. We formulate our optimization problem and employ the convex optimization method to obtain the optimal times and nodes for spectrum sensing, data transmission, and harvesting energy in each subchannel for multiband cognitive sensor networks. Simulation results show that in our proposed algorithm, the network data transmission rate is improved while more energy is saved compared with the baseline methods with equal sensing time in all subchannels.     

基于速率约束的OFDM中继链路能效最优资源分配策略

该文研究解码转发(DF)模式的OFDM中继链路的能效最大化资源分配问题。与现有典型的固定速率最小化发射功率或无约束最大化能效算法不同,该文考虑电路功率消耗的前提下,将问题建模为以最大化系统能效为目标,同时考虑用户最小速率需求、源节点S和中继节点R各自总发射功率约束下的联合子载波配对和最优功率分配问题。证明了速率和功率联合约束条件下中继链路全局能效最优解的唯一性,在此基础上提出一种低复杂度联合最优资源分配策略。仿真结果表明,该文所提方案能够在最小速率和S/R节点最大发射功率约束下自适应分配功率资源,实现系统能效最优,并能够降低链路的中断概率。     

认知小蜂窝网络中基于能效的下行资源分配算法

在认知小蜂窝网络框架下,对基于OFDMA技术的下行联合频谱资源块和功率分配问题进行了研究。小蜂窝基站在分布式结构下采用开放式接入方式共享空闲频谱资源以最大化其能量效率,基站间的竞争关系使系统资源的动态分配过程可建模为非合作博弈模型。由于最大化具有多个限制条件的分数形势的能量效用函数属于非凸最优问题,可通过将其转化为等价的减数形势,并从串行和并行迭代的角度进行求解。在给定资源块分配策略后,原有博弈模型可被重新建模为便于独立求解发射功率的等价子博弈模型。仿真结果表明,所提算法在干扰受限的通信环境下能收敛到纳什均衡,并有效提高了系统资源利用率和能量效率。     

Wakeup strategy based on multi-objective optimization for fixed relay nodes

In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.     

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

Energy efficiency optimization for HCNs based on small base station transmission power allocation

In the research of green communication, considering the base station (BS) power allocation from the perspective of energy efficiency (EE) is meaningful for heterogeneous cellular networks (HCNs) optimization. The EE of two-tier HCNs was analyzed and a new method for the network EE optimization was proposed by adjusting the small BS transmitting power. First, the HCNs ware modeled by homogeneous Poisson point processes (PPPs), and the coverage probability of BSs in each tier was derived. Second, according to the definition of EE, and the closed-form of EE was given by deriving the total power consumption and total throughput of HCNs respectively. At last, the analytical performance of the EE of HCNs on the small BS transmission power was analyzed, and a small BS power optimization algorithm was proposed to maximize the EE. Simulation results show that, the transmission power of small BS has a significant impact on the EE of HCNs. Furthermore, by optimizing the transmission power of small BS, the EE of HCNs can be improved effectively.