A novel weighed cooperative bandwidth spectrum sensing for spectrum occupancy of cognitive radio network

In cognitive radio network(CRN), a secondary user(SU) may utilize the spectrum resource of the primary user(PU) and avoid causing harmful interference to the primary network(PN) via spectrum sensing. In the traditional time spectrum sensing, the SU cannot detect the PU's presence during its transmission, thus increasing interference to the PN. In this work, a novel weighed cooperative bandwidth spectrum sensing method is proposed, which allows multiple SUs to use part of the bandwidth to perform cooperative spectrum sensing throughout the whole frame in order to detect the PU's reappearance in time. The SU's spectrum efficiency is maximized by jointly optimizing sensing bandwidth proportion, number of cooperative SUs and detection probability, subject to the constraints on the SU's interference and the false alarm probability. Simulation results show significant decrease on the interference and improvement on the spectrum efficiency using the proposed weighed cooperative bandwidth spectrum sensing method.     

认知无线电网络频谱聚合策略的性能优化

为了有效提高认知无线电网络频谱共享的性能,综合考虑了集中控制模式下的数据传输质量及信道利用率,研究了基于主用户的频谱聚合策略. 针对一个聚合频谱中的多个信道,面向次级用户建立具有多服务台且传输过程可同步中断的离散时间排队模型. 使用矩阵几何解方法,求解出主用户数据包阻塞率、次级用户数据包平均延迟以及信道利用率等性能指标的表达式. 实验结果表明,在设置频谱聚合容量时,不同性能指标之间存在折中关系. 通过建立成本函数,给出了频谱聚合容量的设置方案,实现了认知无线电网络频谱聚合策略的性能优化.     

Stable-throughput analysis and optimization of cooperative cognitive radio networks based on information and energy cooperation

According to the unsaturated data traffic in wireless communications, this paper studies the interaction between primary users (PUs) and secondary users (SUs) in a cooperative cognitive radio network which is based on information and energy cooperation, and optimizes the stable-throughput of SUs. A probabilistic cooperation scheme has been proposed and the stable-throughput region has been characterized in order to reflect the interaction between PUs and SUs by using the Queuing Theory. Then by deriving the optimal value of the relaying probability, the stable-throughput of secondary users can be maximized under the constraint of the primary queue stability. Simulation results and theoretical analysis show that the probabilistic cooperation scheme can achieve maximal stable-throughputs for SUs, and meanwhile PUs can also have a better performance compared to the non-cooperative case.     

基于计算吞吐量最大化的能量采集边缘计算系统在线资源优化配置

在基于可再生能量收集技术的移动边缘计算(Mobile Edge Computing, MEC)系统中,可再生能量到达和计算卸载无线信道呈现较强的时空变化特性,因此该系统的无线及计算资源管理与用户任务计算之间存在着动态适配的挑战。针对此类问题,本文研究多时隙多用户的能量采集边缘计算系统,建立可再生能量随机到达和无线信道模型以及预测误差模型,以系统总计算吞吐量最大化为准则,通过逐时隙联合优化用户本地计算和计算卸载模块,提出了一种在线滑动窗设计方案, 需要通过调整滑动窗长度M来实现。该方案逐时隙求解凸优化问题,基于离线资源动态管控的最优结构,实时制定资源管理策略,具有较低的计算复杂度。仿真实验结果表明,提出的在线滑动窗设计方案在系统计算吞吐量性能方面优于已有的基准方案,并在对抗信道/能量状态信息预测误差方面有较好的鲁棒性能。     

Optimal spectrum allocation of primary users in light-handed cognitive radio networks

In traditional cognitive radio (CR) network,secondary users (SUs) are always assumed to obey the rule of “introducing no interference to the primary users (PUs) ”.However,this assumption may be not rea...     

定价机制下认知无线电网络频谱接入算法

为了研究认知无线电网络中认知用户频谱接入的决策问题,将认知用户的频谱接入过程视为非合作博弈过程,并考虑到授权用户享有频谱的优先使用权,基于带有服务台故障的M/G/1排队理论建立了系统模型,分析了认知用户个体最优接入策略和社会最优接入策略,并在此基础上提出定价机制使认知用户追求个体利益最大化的目标与社会目标一致,实现社会福利最大化.实验结果表明,基于定价机制的频谱接入策略可以使频谱资源得到相对的优化配置,满足社会整体利益需求.     

干扰温度受限的认知无线电系统中断概率分析

针对一个衰落条件下的多用户认知无线电系统,该系统存在多个并行的认知链路,其发送功率同时受主用户接收端干扰温度的限制以及各自的最大中断概率约束,研究如何通过对各认知链路适当的功率控制来使其非中断传输概率的乘积达到最大,以获得尽可能高的传输效率并保证各链路的共享公平性。首先,对瑞利衰落、信道噪声和用户间信号干扰进行了合理的抽象与建模,并给出了各认知链路的中断概率表达式,将上述各认知链路传输概率乘积最大化问题近似为几何规划问题,从而获得该问题的近似最优解。仿真结果表明,这一近似解与实际最优解基本吻合。     

主用户随机接入/离开模型下的频谱感知性能

经典的频谱感知性能分析方法通常假设主用户信号占满整个感知时隙,但实际上主用户可能在感知时隙的任意时刻接入或离开,针对这一情况,依据主用户随机"接入/离开"行为特征进行建模,在此基础上展开频谱感知性能的分析.首先,根据主用户接入或离开时刻在感知时隙内的位置,分4个场景进行讨论,得到主用户信号在感知时隙内持续时长的概率表达式;然后,采用能量检测方法,通过理论推导获得次用户平均检测概率的函数表达式.数值仿真结果验证了理论推导的合理性,同时表明主用户的随机"接入/离开"行为不仅显著影响感知性能的变化趋势,还使得次用户的感知最大降低达50%以上.     

认知网络中快速自适应功率控制算法

采用sigmoid函数设计了一种自适应效用函数,该函数仅与认知用户的信干噪比门限和当前获得的信干噪比相关,因此可以通过自适应改变信干噪比门限实现认知用户的机会频谱接入,并快速满足其服务质量要求．同时,兼顾用户公平性重新设计代价函数来改善纳什均衡功率解的帕累托有效性．在此基础上基于非合作博弈论提出一种功率控制模型,经证明该模型符合超模博弈,从理论上保证了纳什均衡解的存在性和惟一性．并提出一种自适应功率控制算法,仿真结果表明该算法可以保证约10次迭代收敛,与参考算法相比节省约8％的功耗,在获得的效用上有近15％改善．     

一种空背景下红外弱小目标检测算法

为了检测空背景下的红外弱小目标,提出了一种预测式管道滤波新算法。首先进行单帧检测以获取候选目标,并以该候选目标位置为中心建立预测管道;根据前三帧管道中心位置预测下一帧管道中心位置,从而实现管道随着目标的移动,而且为下一帧的预处理提供先验知识;使用管道滤波算法进行目标检测。由于进入管道预测阶段后,单帧检测只需在预测的管道中心周围进行,由此显著提高了该算法的检测速度和抗干扰能力。仿真实验证明,该算法具有很好的检测性能。     

基于统计特性的多天线能效优化

针对多天线链路,提出基于信道统计特性的传输与能效优化方案.接收端采用基于训练序列的最小均方误差估计获得信道估计值,并基于码本进行有限反馈,从而使得发送端获得信道状态信息并进行波束赋形的数据传输.针对这一传输过程进行能效优化,根据其信道统计特性对最小均方误差估计值和估计误差及码本反馈量化值和反馈误差进行统计分析,进而形成针对能效度量的统计分析和能效优化模型,并给出能效最大化的训练功率及数据功率分配方案.仿真结果表明,与已有静态功率分配方案相比,提出方案可以有效地提高系统能效性,且在快速时变信道环境下,以极低复杂度获得趋近于已有动态功率分配方案的性能.     

机会频谱接入中能量有效感知接入策略联合设计

在非时隙主用户网络中,为了提高认知无线网络中认知用户的能量有效性,基于序贯决策理论提出了一种新的自适应机会频谱接入算法。该算法以最大化能量有效性为目标,通过建立感知接入联合优化模型,使得认知用户能够以最优的信道感知时间和传输功率接入信道。同时,在功率控制过程中引入认知用户请求数据包长度,使得传输功率可以基于数据包长度自适应控制。上述目标优化求解过程中,借助于非线性分式规划理论将其转化为线形规划问题,并运用二分搜索算法寻求最优解。仿真结果表明,所提算法能够实现感知性能和感知能耗的有效折中,有效提高认知用户的能量有效性。     

Estimation for Traffic Arrival Rate and Service Rate of Primary Users in Cognitive Radio Networks

In order to estimate the traffic arrival rate and service rate parameters of primary users in cognitive radio networks, a hidden Markov model estimation algorithm (HMM-EA) is proposed, which can provide better estimation performance than the energy detection estimation algorithm (ED-EA). Firstly, spectrum usage behaviors of primary users are described by establishing a preemptive priority queue model, by which a real state transition probability matrix is derived. Secondly, cooperative detection is utilized to detect the real state of primary users and emission matrix is derived by considering both detection and false alarm probability. Then, a hidden Markov model is built based on the previous two steps, and evaluated through the forward-backward algorithm. Finally, the simulations results verify that the HMM-EA algorithm outperforms the ED-EA in terms of convergence performance, and therefore the secondary user is able to access the unused channel with the least busy probability in real time.     

多载波认知无线电无线携能通信资源分配算法

认知无线电可通过频谱感知提高资源利用率,但会产生感知能耗,降低传输能量.为了保证认知无线电的传输性能,提出认知无线电可利用多载波实现无线携能通信,并分配通信资源,实现系统性能优化.认知无线电利用部分子载波传输信息,采集剩余子载波上主用户射频能量,补充感知耗能.提出的子载波和子载波功率联合优化算法,在保证能量、干扰和总功率受约束的基础上,可最优化系统的吞吐量和能量.仿真结果表明,能量采集会占用传输资源,需要合理分配子载波,使其在速率和能量间取得性能折中.提出的算法通过采集能量补充感知能耗有效地提高了系统吞吐量.     

风力发电机旋转样本谱及疲劳寿命预测

为了考虑桨叶旋转效应,准确进行风力发电机疲劳寿命预测,提出了基于旋转样本谱的风力发电机疲劳寿命预测模型.借助Fourier变换,推导了考虑旋转效应的旋转样本谱,并与Von Karman谱(一种固定点紊流风谱)进行比较.在旋转样本谱的基础上,提出了源于Palmgren-Miner线性损伤准则的风力发电机疲劳寿命预测模型,并以1.25MW风力发电机为例进行疲劳寿命分析.结果表明,与固定点紊流风谱相比,旋转样本谱的能量分布发生了根本变化,其能量由低频向高频移动,在高频段曲线会出现多峰情况;基于旋转样本谱的疲劳寿命分析更接近实际情况,而基于Von Karman谱进行风力发电机疲劳寿命预测不够精确,且偏于不安全.     

删余协作频谱感知性能分析及优化

提出了一种新的基于删余的协作频谱感知方法,通过减少实际发送的本地决策值数来节约控制信道带宽,降低检测性能对认知用户数的依赖; 分析了这种删余协作频谱感知在感知信道和报告信道均存在衰落下的性能,它可以有效解决报告信道衰落所带来的尾感知问题,降低了虚警率; 提出了进一步优化算法,算法在确保主用户受到足够保护的前提下,通过寻找最优的次用户数和相应的检测门限使次用户的接入机会最大化．仿真结果与理论分析相一致．     

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.     

Velocity forecasts using a combined deep learning model in hybrid electric vehicles with V2V and V2I communication

Vehicle velocity forecast is an important clue in improving the performance of energy management in hybrid electric vehicles(HEV). This paper presents a new combined model for predicting vehicle's velocity time series. The main features of the model are to combine the feature extraction capability of deep restricted Boltzmann machines(DBM) and sequence pattern predicting capability of bidirectional long short-term memory(BLSTM). Hence, the model is named as DBMBLSTM. In addition, the DRMBLSTM model utilizes the vehicle driving information and roadside infrastructure information provided respectively through vehicle-to-vehicle(V2V) and vehicle-to-infrastructure(V2I) communication channels to predict vehicle velocity at various length of prediction horizon. Furthermore, the predictions results of this study are compared with the state of the art of vehicle velocity forecasts. The root mean square error(RMSE) is used as an evaluation criteria of predictions accuracy. Finally,these compared prediction model are applied in model predictive control(MPC) energy management strategy for the verifications of fuel economy improvement of a HEV. Simulation results confirm that the proposed combined deep learning model performs better than other five prediction methods. Therefore, it is a means of arriving at a reliable forecast model for HEV.     

基于小波和回声状态网络的交通流多步预测模型

针对交通流的含噪混沌特征,提出了一种基于小波回声状态网络的交通流多步预测模型。该模型利用小波多尺度分解方法,屏蔽了噪声成分对交通流动力学特性的干扰,同时提取了占有交通流绝大部分能量的混沌低频成分。在采用多路分量并行预测的方式下,充分发挥了回声状态网络对混沌低频分量的强大多步预测能力,从而保障了交通流多步预测的精度。对北京市西直门桥的实测交通流的预测结果表明:该模型的多步预测精度比传统的回声状态网络模型有了较大幅度的提升,在保证预测精度的前提下,最大可预测的步长也相应的增加。     

基于循环平稳特征的OFDM主用户感知的仿真研究

循环平稳特征可用于认知无线电系统主用户的感知,本文针对OFDM信号分析其循环谱特征,采用频域平滑估计方法对循环谱及其感知性能进行仿真,结果表明在低信噪比下基于循环平稳特征感知的性能优于能量检测。