基于生命期模型的无线传感器网络信道分配博弈算法

针对无线传感器网络中节点因干扰过大导致重传能耗增加, 进而节点过早失效、网络生命期缩短的问题, 根据网络拓扑信息和路由信息设计节点的负载模型, 从而构建了节点的生命期模型. 然后利用博弈论将路径增益、交叉干扰和节点生命期等性能参数融入到效益函数中, 构建信道分配博弈模型. 理论分析证明该博弈模型存在纳什均衡. 进而运用最佳回应策略, 在所构建的信道分配博弈模型的基础上, 设计了一种优化网络生命期的抗干扰信道分配算法. 该算法使节点在选择信道时避免与网络中交叉干扰较大的节点和生命期较小的节点使用相同信道, 实现干扰小、能耗低且均衡的信道选择. 理论分析与仿真结果证明该算法最终能够快速地收敛到纳什均衡, 且具有较小的信息复杂度, 从而减小算法本身的通信能耗. 同时, 该算法具有良好的抗干扰性和信道均衡性, 能够有效地延长网络生命期.     

航空通信网络中复杂干扰过滤技术研究

航空通信环境中存在复杂的干扰信号,对正常的通信信号造成强烈的干扰。利用传统算法进行干扰信号过滤,无法避免由于干扰信号过于复杂导致过滤不充分的缺陷。提出一种基于加权残差优化算法的航空通信网络中复杂干扰过滤方法。对原始信号进行降频处理,能够消除峰值干扰信号,提高了信号的准确性。根据加权残差修正优化算法的相关原理,对通信信号进行残差优化处理,经过处理后的通信信号在受到干扰时会形成零陷,实现了对复杂干扰信号的过滤。实验结果表明,利用该算法进行航空通信网络中复杂干扰信号过滤,能够有效提高过滤的准确性,效果令人满意。     

无线传感器网络AMRSSI加密调制定位算法研究

RSSI定位技术在无线传感器网络实际应用中,由于环境的开放性,信号很容易受到敌方的攻击,从而使系统的定位产生错误;通过对RSSI测距定位模型进行分析,提出了基于RSSI新的加密调制定位算法AMRSSI,该定位算法计算简单、保密性强、受外界干扰小;仿真实验表明该算法较普通的基于RSSI的测距方法定位精度上有了明显的改进,适合在通信开销小、硬件要求低的传感器网络节点上应用。     

基于改进卡尔曼滤波的水声通信盲自适应多用户检测算法

针对水声通信网络中遇到的多用户检测中目标用户的多址干扰等检测问题,提出了基于改进Kalman算法的盲自适应多用户检测算法,解决了多用户检测中的多址干扰对水声通信信道用户变动时的干扰抑制问题。仿真分析分别针对同步多用户、异步多用户通信过程,对比了传统Kalman算法及改进的Kalman算法的性能差异,通过仿真对比表明,改进后的Kalman检算法不需要训练序列即可以实现同步和异步通信状态下的多水声目标用户的盲自适应检测,改进后的算法目标检测的信干比比传统算法最大可提高6dB。新算法对于水下多用户检测、区分,准确、稳定的实现基于CDMA协议的快速水声通信具有重要意义。     

基于粒子群的无线紫外光网络快速信道分配方法

针对无线紫外光散射通信中非视距(NLOS)传输特点和信道干扰模型,采用基于粒子群的无线紫外光网络快速信道分配方法,充分考虑了空间角度对信道冲突矩阵的影响,实现了一种定向、快速的信道分配新方法。仿真分析了该算法的平均迭代次数、平均干扰度以及收敛时间与粒子群数目和信道数目的关系。实验结果表明此紫外光网络信道分配方法具有收敛速度快、冲突度小的优势,保障了无线紫外光网络信道分配的快速性和准确性。     

ZigBee网络中基于信道状态预测的WiFi干扰避免方法

针对2.4G频段上WIFI网络对zigbee网络产生的信道干扰问题,提出了一种基于信道状态预测的干扰避免算法。该算法采用隐马尔科夫模型预测下一时刻zigbee网络的16个信道状态,如果指示下一时刻某个信道状态低于某个阀值,就将该信道替换到信道序列的最后一个,从而形成一个新的信道序列,并根据新的信道序列动态调整zigbee网络的工作信道。使该网络工作在最安静的信道上,从而避免来自WIFI的干扰。最后在Simulink中建立了zigbee网络通信模型用于验证该算法,仿真结果表明,与常用的信道分配方法相比,此方法能够根据隐马尔科夫模型预测下一时刻的信道状态,动态更新信道序列。增加了空闲信道选择的命中率。该算法不但节省节点能耗,还缩短传输时延。具有复杂度低、精确度高的特点。     

基于Dual-Mode MMA+MDD 双模式T/2分数间隔盲均衡算法的研究

均衡技术是用来解决通信系统中码间干扰的常用方法.针对传统恒模算法的收敛速度和稳态剩余码间干扰大的缺点,将双模式多模算法和改进型判决引导算法结合起来,并且应用于分数间隔盲均衡器中.该算法初期用双模式算法收敛均衡器,然后切换到改进型判决引导算法中进一步收敛,由于分数间隔均衡器解决了波特间隔均衡器因抽样率不高带来的频谱混叠问题,从而进一步地提高了均衡效果.蒙特卡罗仿真表明,该算法不仅收敛速度快,而且得到较低的剩余码间干扰.     

一种裕量最大的高速载波比特功率分配算法

在国家电网公司Q/GDW 1379.4-2013技术规范对智能电能表载波通信单元功率消耗的限定要求下,为保障低压远程电力集抄台区本地通信链路的传输速率稳定可靠,给智能用电实时交互平台提供带宽支持,提出了一种裕量最大的高速载波比特功率分配算法。该算法以兼并窄带载波和宽带载波优势的G3-PLC技术为应用对象,使用约束注水法限定各子载波的传输比特数,根据时变的电力信道增益自适应调整比特功率分配方案,并响应通信服务质量QoS对系统误码率和目标传输速率的要求,结合信噪比门限算法对约束注水法进行界定和优化,得到了功率裕量最大化的表达式。仿真结果表明：提出的算法优于低反馈开销算法,能够适应低压电力线信道。在系统目标传输速率为200kbps时,达到了最大裕量值20,极大程度地降低了通信单元调制解调芯片实际的功率消耗。     

基于正交频分复用无源光网络的动态带宽分配算法研究

介绍了一种应用于未来大容量、多业务接入场景下的称为光正交频分复用无源光网络的下一代接入网技术,并提出了一种基于此结构的称为基于服务质量需求的固定周期流水线轮询动态带宽分配算法.该算法通过应用二级带宽分配机制、带宽预申请机制和最小带宽申请优先原则等方法,有效地保障了在大容量、多业务接入场景下各个业务不同的服务质量需求.为研究其性能,建立了该算法的仿真模型并进行了对比仿真.仿真结果显示该算法以低时延和低抖动有效地支持快速转发业务,同时平衡了确保转发业务和尽力而为业务之间的优先性和相对公平性,并且实现了不同光网络单元间的同优先级业务带宽分配的公平性.与传统的动态带宽分配算法算法相比,基于服务质量需求的固定周期流水线轮询动态带宽分配算法具有执行效率高、算法复杂度低、性能良好等优点,并且能够更好地适应光正交频分复用无源光网络的特性,发挥网络最大的性能.     

一种无线传感器网络健壮性可调的能量均衡拓扑控制算法

无线传感器网络中, 应用环境的干扰导致节点间距不能被准确度量. 所以利用以节点间距作为权重的闭包图(EG)模型构建的拓扑没有考虑环境的干扰, 忽略了这部分干扰带来的能耗, 缩短了网络生存时间. 针对无线传感器网络拓扑能量不均的特点和EG模型的缺陷, 首先引入节点度调节因子, 建立通信度量模型和节点实际生存时间模型; 其次量化网络节点度, 从而获取满足能量均衡和网络生命期最大化需求的节点度的取值规律; 然后利用该取值规律和函数极值充分条件解析推导出网络最大能量消耗值和最长生存时间, 并获得最优节点度; 最后基于以上模型提出一种健壮性可调的能量均衡拓扑控制算法. 理论证明该拓扑连通且为双向连通. 仿真结果说明网络能利用最优节点度达到较高的健壮性, 保证信息可靠传输, 且算法能有效平衡节点能耗, 提高网络健壮性, 延长网络生命周期.     

Spectrum sensing in cognitive radio networks and metacognition for dynamic spectrum sharing between radar and communication system: A review

The massive growth in mobile users and wireless technologies has resulted in increased data traffic and created demand for additional radio spectrum. This growing demand for radio spectrum has resulted in spectrum congestion and mandated the need for coexistence between radar and interfering communication emitters. To address the aforementioned issues, it is critical to review existing policies and evaluate new technologies that can utilize spectrum in an efficient and intelligent manner. Cognitive radio and cognitive radar are two promising technologies that exploit spectrum using dynamic spectrum access techniques. Additionally, introducing the bio-inspired concept ‘metacognition’ in a cognitive process has shown to increase the effectiveness and robustness of the cognitive radio and cognitive radar system. Metacognition is a high-order thinking agent that monitors and regulates the cognition process through a feedback and control process called the perception–action cycle. Extensive research has been done in the field of spectrum sensing in cognitive radio and spectral coexistence between radar and communication systems. This paper provides a detailed classification of spectrum sensing schemes and explains how dynamic spectrum access strategies share the spectrum between radar and communication systems. In addition to this, the fundamentals of cognitive radio, its architecture, spectrum management framework, and metacognition concept in radar are discussed. Furthermore, this paper presents various research issues, challenges, and future research directions associated with spectrum sensing in cognitive radar and dynamic spectrum access strategies in cognitive radar.     

5G-based wideband cognitive radio system design with cooperative spectrum sensing

Since the 5G bandwidth is very large, there are a large number of non-continuous idle spectrum in 5G communication. In this paper, we have designed transmitter and receiver of a 5G-based wideband cognitive radio (CR) system with cooperative spectrum sensing, in order to improve transmission performance and avoid interference signals. Each CR user marks the spectrum availability for getting the sub-basis function through doing Inverse Fast Fourier Transform (IFFT) with the product of spectrum marker vector and random phase vector. The cooperative spectrum sensing can be realized by cascading the sub-basis functions of all the users. Multiple access of the CR system is also proposed to access much non-continuous idle spectrum. The simulation results have shown that the proposed CR system can avoid the interference effectively and outperform the spread spectrum system obviously.     

基于贝叶斯网络的认知引擎设计与重配置

以往的通信行为指导系统未来通信, 以满足用户需求并适应环境变化, 是认知无线电系统的核心所在, 为此提出了一种基于贝叶斯网络的认知引擎, 用于解决在复杂多变的电磁环境与用户需求条件下, 认知无线电系统参数自适应调整的问题. 通过对系统过去通信行为样本数据, 进行结构学习和参数学习建立认知引擎, 将系统当前环境状态和用户需求信息经预处理作为推理的证据, 应用引擎决策出系统此时最佳的工作参数, 完成系统参数重构. 本文利用OPNET工具建立一个移动无线网络完成仿真实验, 仿真结果表明该认知引擎能有效地使移动无线网络适应环境变化, 改善端到端通信性能, 进一步验证了建模方法的可行性.     

A spectrum auction algorithm based on joint power control and beamforming in small cell networks

Spectrum auction is considered as a suitable approach to efficiently allocate spectrum among unlicensed users. However, in previous studies of spectrum auction, competition can hardly be reflected in the traditional spectrum allocation and the spectrum efficiency is still not high after the allocation. In this paper, we enhance the factor of competition in the auctions, in which bidders need to pay for the competition and the interference to macro cell users (MUs). We consider a communication system with one macro cell and several small cells, thus a licensed radio spectrum is shared by both MUs and small cell users (SUs). A truthful auction algorithm is proposed for spectrum allocation and the spectrum is divided into multiple channels in different time slots, so that SUs can make their choice for bidding under the guidance of history. In order to raise the communication quality, we propose a power control and beamforming algorithm in the heterogeneous network to enhance the system performance. Simulation results are presented to verify the effectiveness of the proposed algorithm in the small cell network.     

Route selection for interference minimization to primary users in cognitive radio ad hoc networks: A cross layer approach

An opportunistic routing problem in a cognitive radio ad hoc network is investigated with an aim to minimize the interference to primary users (PUs) and under the constraint of a minimum end-to-end data rate for secondary users (SUs). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying techniques are considered for message forwarding by SU nodes in the network. Unlike popular transmit power control based solutions for interference management in cognitive radio networks, we adopt a cross layer approach. The optimization problem is formulated as a joint power control, channel assignment and route selection problem. Next, closed form expression for transmission power is derived and corresponding channel selection scheme and routing metric are designed based on this solution. The proposed route selection schemes are shown to depend not only on gains of the interference channels between SUs and PUs but also on the values of the spectrum sensing parameters at the SU nodes in the network. Two distributed routing schemes are proposed based on our analysis; (i) optimal_DF and (ii) suboptimal_AF. The routing schemes could be implemented using existing table driven as well as on demand routing protocols. Extensive simulation results are provided to evaluate performance of our proposed schemes in random multihop networks. Results show significant reduction in PUs’ average interference experience and impressive performance as opportunistic routing schemes can be achieved by our schemes compared to traditional shortest path based routing schemes. Performance improvement is also reported over prominent recent schemes.     

标志位频谱感知方法研究

文章提出了一种新的标志位频谱感知方法,主要由数据采集和频谱感知两部分组成.前者主要基于标准的压缩感知技术,研究了一种标志位数据采集方法,仅保留测量数据的标志位信息,从而减少了测量数据的存储量.后者基于一致恢复原理和共轭梯度算法来构造频谱感知算法.仿真结果表明,标志位频谱感知方法可以在降低数据采集量及存储量的同时完美获取原始信号的频谱信息.该方法可以应用于无线通信、电子对抗、智能吸波结构以及感知无线电的前端频谱测量设计阶段中. 关键词： 频谱感知 标志位压缩感知 智能吸波结构     

认知无线电网络中利用FEC和DE的多节点频谱感知算法

针对认知无线电网络(CRN)中空闲频谱感知困难的问题,本文提出了基于前向纠错和差分进化算法的多节点频谱感知算法。首先,利用基于差分进化算法的协同检测完成信号感知;然后,研究了信道噪声对频谱感知性能的影响;最后,分析了前向纠错技术在信道存在噪声时对频谱感知性能的影响。仿真实验将纠错和无纠错控制信道的不同信噪比作为依据,采用三种不同的检测方法评估了本文算法。仿真实验结果表明,在存在噪声的认知无线电网络中,本文算法提高了系统的性能和检测概率,且协同感知算法的性能随着节点数目的增加而提高,该算法适合应用于实时性要求较高的应用程序。     

Single decision reporting for cooperative spectrum sensing under erroneous feedback channels with Byzantine attack

Spectrum sensing based on a single user suffers from low detection performance due to fading, shadowing, and hidden node problems. Cooperative spectrum sensing (CSS) is thought to be a potential method to overcome these issues and improve detection performance in determining the available spectrum in cognitive radio (CR). However, CSS suffers in case of erroneous reporting channels, and it is also susceptible to Byzantine attacks by malicious users (MUs). In this paper, we first analyze the traditional CSS under erroneous feedback channels. And then, we extend the analysis to include erroneous reporting channels in the presence of the Byzantine attack. We propose a single decision reporting (SD-R) algorithm immune to erroneous reporting channels. The proposed algorithm also improves the performance under the Byzantine attack. With the proposed algorithm, MUs can attempt only false alarm attacks, whereas the miss detection attack is not possible. An extensive analysis is carried out, and the plots are shown to prove the superiority of the proposed algorithm.     

Leakage-based beamforming via game theory for reverse spectrum auction in cellular offloading systems

The explosion of mobile traffic and highly dynamic property often make it increasingly stressful for a cellular service provider to provide sufficient cellular spectrum resources to support the dynamic change of traffic demand in a day. In this paper, considering the dynamic characteristic of the cellular network traffic demand, we not only proposed an optimal, truthful reverse auction incentive framework, but also proposed a valuation function which is based on third-party access points’ capacity. We consider spectrum sharing in a third-party network where several secondary users (SUs) share spectrum with a primary user (PU). A leakage-based beamforming algorithm is proposed via game theory to maximize the sum utility of third-party access points subject to the signal-to-leakage-and-noise (SLNR) constraint of SUs and PU interference constraint. The sum throughput maximization problem is formulated as a non-cooperative game, where the SUs compete with each other over the resources. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can achieve a high sum throughput and converge to a locally optimal beamforming vector.     

一种基于授权信道特性的认知无线电频谱检测算法

针对认知无线电系统中频谱检测的频率直接影响系统容量以及与授权用户产生冲突的概率问题,分析了授权用户频谱使用的特性, 对授权用户行为进行统计建模, 提出一种自适应频谱检测算法. 引入控制因子, 在保证认知无线电系统稳定性的约束下, 自适应调整频谱感知的频率从而提高频谱利用率并减小系统冲突概率和检测开销, 进而降低了系统的能量消耗. 仿真结果表明, 该算法在保证不对授权用户产生干扰和一定的系统稳定性条件下, 有效地提高了系统的容量,并且具有良好的实用性和灵活性. 关键词： 认知无线电 自适应频谱检测 绿色通信 最大似然