莱斯信道下基于特征值的频谱感知技术

针对衰落环境下频谱利用率的提高,采用了一种基于接收信号自相关矩阵的特征值的检测方法。该方法基于随机矩阵理论,用最大最小特征值作为检验统计量来检测授权用户是否存在,从而改善频谱利用率。将随机产生的BPSK信号和捕获的DTV信号分别作为信号源在莱斯衰落信道下进行信号检测仿真。实验表明与传统能量检测方法的对比,该检测算法在莱斯衰落信道下具有良好的检测性能。     

物理层网络编码分组的机会中继

为提升物理层网络编码方案的抗衰落性能,该文提出了一种基于物理层网络编码的机会中继方案(Opportunistic Relaying based-on Physical-layer Network Coding,PNC-OR),该方案利用物理层网络编码的基本思想、有效提升网络吞吐的同时,通过中继节点的分布式选择,也能够使系统获得多用户分集增益,提高了系统的抗衰落性能。针对双向无线中继信道中端到端信息交换的情形,推导了准静态衰落环境下PNC-OR中多个目的节点接收信息的和容量。数值结果显示：和机会中继、传统网络编码两种方案相比,PNC-OR具有更高的频谱效率,并且随着中继节点的增多,频谱效率也越高。     

认知车载网的频谱感知性能分析

认知车载网中不同的衰落传播信道会影响频谱感知的性能.为了描述不同信道下的频谱感知性能,分析了加性高斯白噪声信道、瑞利衰落信道和Nakagami-m衰落信道条件下的频谱感知单用户能量检测概率和协作能量检测概率,重点是Nakagami-m衰落信道、检测衰落因子、次用户的数量和信噪比这几个参数对协作频谱感知性能的影响.仿真结果表明,通过对不同信道特性的准确了解能够帮助车辆在不同衰落信道环境下提高频谱的检测概率.     

基于信噪比加权的合作频谱检测算法

认知无线电作为一种先进的技术,它可以通过有效的利用未被主用户使用的频谱来提高频谱的利用效率。然而,由于无线环境的复杂性,单节点频谱检测的可靠性大大下降,虽然现有的合作频谱检测算法在一定程度上提高了频谱检测的性能,但仍未达到最佳。基于此,本文提出了一种信噪比加权的合作频谱检测算法来提高信号的检测概率,然后在加性高斯信道(AWGN)和瑞利衰落(Rayleigh)信道下对该算法进行了仿真验证。仿真结果表明:该算法能大大提高了信号的检测性能,具有很强的抗衰落能力。     

Rician信道下基于双门限的能量检测性能分析

针对认知无线电频谱检测中无线传输环境的复杂性,选用Rician信道模拟信号传输过程中的多径衰落,使用双门限能量检测算法减少噪声不确定性的影响。提出一种Rician信道下基于双门限的能量检测算法,推导了检测概率公式,并定义了误检概率来量化系统检测误差的大小。仿真分析了Rician信道下信噪比和因子K的变化对能量检测性能的影响,并通过仿真表明双门限算法较传统单门限算法,能够有效降低系统进行能量检测的误检概率。     

分布式多入多出正交频分复用快衰落感知估计

针对分布式多输入多输出正交频分复用(MIMO-OFDM)快衰落系统,为了消除快衰落信道的干扰,提出一种分布式MIMO-OFDM系统快衰落信道估计方法.该方法利用分布式快衰落信道间的感知信息在空间、时延和多普勒频移上具有的互相关性,求取三维互相关联合稀疏信道模型.推导预相关随机导频测量矩阵,结合分布式压缩感知算法,以能量有效的方式,对快衰落稀疏信道参数进行联合压缩测量和重构,得到各分布式MIMO接收端任意的稀疏信道系数.理论分析与仿真结果都表明,该方法与传统的信道估计方法相比,可以明显提高系统频谱效率和误码率,减少计算复杂度.     

瑞利衰落环境中一种能量有效的多无线电信道搜索机制研究

针对当前频谱搜索机制在能量有效方面的不足,该文提出了一种在瑞利衰落条件下基于部分可测马尔科夫决策过程(POMDP)的多无线电信道搜索机制MRCSS。该机制通过对瑞利衰落环境中信道状态建立POMDP模型来分析和推导出能效最佳信道,并以此指导用户的信道选择。仿真结果表明该机制能较传统搜索机制更有效地减少感知时间和节省能耗,从而达到提高频谱感知性能的目的。     

正交空时分组编码系统的信号检测技术

正交空时分担编码（OSTBC）技术可以提高信道容量和误码性能,准静态平坦衰落信道和时变平坦衰落信道下正交空时分组编码率的信号检测技术得到广泛研究。利用正交频分复用技术（OFDM）,研究了时变多径衰落信道下OSTBC-OFDM的信号检测方法,提出了一种能够有效利用无线信道的多径传播效应的发射天线数目等于4的OSTBC信号检测算法,仿真结果表明,发射天线书等于4,接收天线数等于2时,与已有信号检测算法相比,提出的算法有4.5dB性能增益。     

一种新的快衰落信道下的差分Unitary时空编码调制方法

该文提出了一种新的基于循环对角群码的差分Unitary 时空编码调制方法,这种新方法通过改变发送符号的顺序来降低快衰落信道时变对解码造成的影响,从而提高在快衰落信道下的性能。这种性能的提高是以处理时延和额外能量开销的增加为代价的,在实际应用中需要在这两者之间寻求平衡,处理时延越大,额外的能量开销就越小,反之亦然。 与传统的差分Unitary时空编码调制方法比较,理论分析和matlab做的Monte Carlo仿真结果表明,在快衰落信道下,提出的差分Unitary时空编码调制方法可获得明显的性能增益,能够显著降低系统的成对差错概率和误比特率。     

基于信道统计特征的认知无线电协作频谱检测

针对认知无线电到融合中心间的控制信道为Nakagami-m衰落信道的情况,研究了认知无线电协作频谱检测问题,推导出融合中心利用衰落信道统计特征的似然比协作频谱检测公式.该方法不需要瞬时信道状态信息,简化了协作频谱检测过程,便于实际应用.通过仿真对融合中心的协作频谱检测性能进行了分析,结果表明:利用衰落信道统计特征的似然比协作频谱检测的性能较利用瞬时信道状态信息的似然比频谱检测性能略有下降,但是在高信噪比或衰落不严重的情况下,二者的性能非常接近,认知无线电节点个数对两种频谱检测方法间的性能差距几乎没有影响.     

基于非参量累积和的合作频谱感知

针对认知无线电网络中频谱感知的检测时延降低问题,提出了基于非参量累积和的合作频谱感知算法。本地认知用户预处理频谱观测数据,获得观测数据相对于信念值的正向漂移和负向漂移。为了缩短检测延迟,认知用户只将数据的正向漂移同步传输至融合中心。融合中心融合正向漂移得到判决信息,采用非参量累积和算法依时间序列顺序累加判决信息,判断主用户是否正在使用授权频段。为了解决不传输负向漂移引起的虚警问题,改进算法提出融合中心可以保留首次判决,经过等待时间间隔后再作出最终判决。相对于传统的软融合算法,改进融合规则的合作频谱感知算法具有较低的检测延迟。     

衰落环境下一种高能效协作频谱感知算法

在认知无线网络中,对于电池供电的认知设备,如何高效地利用其能量资源极为重要。在将能量效率(能效)定义为认知网络频谱利用效率和平均功率消耗之比的基础上,提出了一种高能效优化算法,在加性高斯白噪声(AWGN)信道、Rayleigh衰落信道和Nakagami衰落信道条件下使融合中心门限达到最优,并求得了最佳的参与协作的用户数。通过蒙特卡洛仿真对认知网络的能效进行了性能评估,结果表明所提算法能有效提升认知网络的能量效率。     

一种适用于超宽带脉冲信号检测的改进CUSUM算法

将最快检测技术应用于超宽带脉冲信号检测中,具体采用改进的CUSUM(Cumulative Sum)算法来检测超宽带脉冲信号。首先分析了经过多径信道衰减后的超宽带脉冲信号概率分布特性,进一步提出了适用于超宽带脉冲信号检测的改进CUSUM算法。理论分析和仿真证明了所提改进算法性能优越且实现复杂度低。该算法克服了块检测算法的信噪比门限效应,且具有最优的检测延迟性能,相同虚警限制下其检测性能明显优于能量检测算法。     

基于累积和的改进超宽带循环平稳检测算法

针对超宽带循环平稳检测存在的门限难以设定、低信噪比下检测延迟较大的问题,提出了基于累积和的改进超宽带循环平稳检测算法。首先将信号整个三维循环谱归一化为二维灰度图,与噪声对应的灰度图比较差异,再将两类图像放入卷积神经网络（Convolutional Neural Network,CNN）自行训练提取特征,解决门限难以确定的问题。若分析三维循环谱的时间块长过短,将导致信号灰度图特征在有无噪声情况下区别不大;若块长过长会导致检测延迟较大。为此,采用累积和算法提取网络全连接层输出的信号概率作为累积和的观测统计量,自适应检测所需采样时间长度。将所提算法与传统循环平稳检测以及结合了CNN的循环平稳检测进行对比,仿真表明所提算法在低信噪比下性能最优。     

A sparsity and compression ratio joint adjustment method for collaborative spectrum sensing

Spectrum sensing is the fundamental task for Cognitive Radio (CR). To overcome the challenge of high sampling rate in traditional spectral estimation methods, Compressed Sensing (CS) theory is developed. A sparsity and compression ratio joint adjustment algorithm for compressed spectrum sensing in CR network is investigated, with the hypothesis that the sparsity level is unknown as priori knowledge at CR terminals. As perfect spectrum reconstruction is not necessarily required during spectrum detection process, the proposed algorithm only performs a rough estimate of sparsity level. Meanwhile, in order to further reduce the sensing measurement, different compression ratios for CR terminals with varying Signal-to-Noise Ratio (SNR) are considered. The proposed algorithm, which optimizes the compression ratio as well as the estimated sparsity level, can greatly reduce the sensing measurement without degrading the detection performance. It also requires less steps of iteration for convergence. Corroborating simulation results are presented to testify the effectiveness of the proposed algorithm for collaborative spectrum sensing.     

Characterization and exploitation of heterogeneous OFDM primary users in cognitive radio networks

The fundamental features of cognitive radio (CR) systems are their ability to adapt to the wireless environment where they operate and their opportunistic occupation of the licensed spectrum bands assigned to the primary network. CR users in CR systems should not cause any interference to primary users (PUs) of the primary network. For this purpose, CR users need to accurately estimate the features and activities of the primary users. In this paper, a novel characterization of heterogeneous PUs and a novel reconfigurability solution in CR networks are introduced. The characterization of PUs consists of a detector and classifier that distinguishes between heterogenous PUs. The PU characteristics stored in radio environmental maps are utilized by an interference/throughput adapter for the optimization of CR parameters. The performance of the proposed solutions is evaluated by showing false alarm and missed detection probabilities of the detector/classifier in a multipath fading channel with additive white Gaussian noise. Moreover, the impact of the PU characteristics on the CR throughput is analyzed.     

The effect of Weibull fading channel on cooperative spectrum sensing network using an improved energy detector

This paper analyses the performance of proposed cooperative spectrum sensing (CSS) network in Weibull fading environment. First, we have derived the novel analytic expressions for probabilities of missed detection and false alarm in Weibull fading channel, assuming an improved energy detector (IED), selection combining diversity scheme and multiple antennas at each cognitive radio (CRs). Next, performance is analyzed using complementary receiver operating characteristics curves, total error rate, average channel throughput, and network utility function curves for the proposed CSS network. The optimal performance of CSS network is achieved by optimizing the CSS network parameters. The closed form of expressions for the optimum value of number of CRs, arbitrary power of received signal, and detection threshold at each CR are derived using OR-Rule and AND-Rule at fusion center (FC). The average channel throughput and network utility function analysis are evaluated using \(k=1+n\) and \(k=N-n\) fusion rules at FC. Finally, the impact of several network parameters such as, multiple antennas at each CR (M), number of CRs (N) in CSS network, Weibull fading parameter (V), arbitrary power of received signal (p), and sensing channel SNR (\({\bar{\gamma }})\) on the performance of proposed CSS network are investigated using the simulation results. The performance comparison between conventional energy detector and an IED has been highlighted with the simulations.     

QoS保证的多信道混合接入CRN频谱共享策略设计

根据既不对主用户(Primary Radio user,PR)产生干扰,又对认知无线电用户(Cognitive Radio user,CR)提供QoS保证的原则,将认知无线电网络(Cognitive Radio Network,CRN)中多信道接入频谱共享问题建模为混合整数非线性规划。采用多级功率限制保证PR不被干扰,以CR物理层能够提供的速率作为信道和功率分配的依据,提出将能够为CR提供最大传输速率的信道分配给该CR的分配策略,将混合整数非线性规划转化为整数线性规划,并给出集中式启发算法和基于功率速率比(Power Rate Ratio,PRR)最小的分布式启发算法求解该整数线性规划。仿真结果表明,文中给出的算法能够提供较高的CRN吞吐量和较好的CR用户QoS保证。     

A unified spectrum sensing and throughput analysis model in cognitive radio networks

Cognitive radio (CR) is a newly developed technology for increasing spectral efficiency in wireless communication systems. In the CR networks, there exist two traditional spectrum‐sharing technologies called spectrum overlay and spectrum underlay. A new hybrid overlay/underlay paradigm has also been discussed in the literature. In this work, we create a unified spectrum sensing and throughput analysis model, which is suitable for overlay, underlay, and hybrid overlay/underlay paradigms in the CR networks. In the proposed model, the energy detection scheme is employed for the spectrum sensing in the network in which the co‐channel interference is present among primary users and secondary users (SUs). The SUs' throughput in the proposed CR system model is then analyzed. The simulations are also carried out for demonstrating the performance of overlay, underlay, and hybrid overlay/underlay paradigms. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic handover algorithm with interference cancellation in 5G networks for emergency communication

The integration of 5G networks with cognitive radio (CR) technology enables the software‐defined networking (SDN) infrastructure to support emergency applications. In future, CR can be integrated with 5G and many wireless networks like Wi‐Fi, WSN, and MANET for efficient spectrum utilization with higher data rate and lower latency. This CR technology allows unlicensed users to access the licensed spectrum, whenever it is free. In this paper, an efficient SDN architecture with cognitive ability for emergency network is proposed in which the SDN controller prolong communication between disaster victims and first responders and so the first responders can arrive at the spot directly and rescue the victims. The SDN controller has cognitive ability so that the victims can utilize the vacant licensed band to communicate with the first responders, thereby improving the spectrum utilization of the network. Another two main challenges during emergency are the occurrence of interference and link failure. The proposed dynamic handover algorithm with interference cancellation (DHAIC) cancels the interference between the nodes inside the network and performs dynamic handoff, whenever link failure occurs between the cluster head (CH) and the controller. An optimum throughput and minimal delay is achieved to ensure the network performance.