认知无线传感器网络中能耗有效的协作频谱感测算法

提出了一种新的认知无线传感器网络中能耗有效的协作频谱感测算法。首先,为了降低分布式传感节点的能耗,假定传感节点的瞬时信噪比和平均信噪比已知,分析频谱感测节点的能耗与最优检测门限值之间的数学模型。然后,结合感测节点选择和判决门限设定理论,研究基于判决节点选择的有效协作频谱感测方案。理论分析和仿真结果表明,算法有效地降低了认知传感器网络的节点总能耗,提高了能耗效率。     

基于频率选择表面的毫米波压缩感知成像

基于频率选择表面,提出了一种毫米波压缩感知成像方法。通过在频率选择表面单元中加载开关二极管,并随机控制它们处于开/关状态,设计了一种可随机切换的新型毫米波成像掩膜板。通过将这种随机掩膜板放置于毫米波天线上,能够构造出相应的随机测量矩阵并获取足够多的有效测量次数。利用恢复重构算法进行了成像仿真验证,结果证实了所提方法的可行性。     

恶意环境中基于能量效率的安全协作频谱感知

频谱感知是认知无线电网络运行的前提,但是在恶意环境中,频谱感知数据存在被篡改的威胁.针对该问题,提出了一种低开销的对称加密方法,采用报文鉴别码对次级用户报告的数据进行鉴权,保证数据的完整性,从而缓解攻击对感知性能的影响.提出了协作频谱感知中能量效率的概念,并通过改变报文鉴别码长度优化能量效率.仿真验证了上述方法的有效性并给出了优化问题的数值解.     

基于循环前缀频域自相关的OFDM信号频谱感知

针对无线通信频谱资源有限并且利用率非常低的问题,研究了认知无线电系统中基于信号典型特征的频谱感知策略,并进行动态频谱检测.提出了一种基于循环前缀频域自相关的频谱感知算法,利用正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号的循环前缀具有循环平稳特性,在信...     

有源频率选择表面研究进展及应用前景

有源频率选择表面(AFSS)是在传统频率选择表面(FSS)单元图形间加载一系列阻抗元件而构成的新型FSS,它具有可调的电磁特性。在分析了AFSS电磁特性调控机理的基础上,综述了AFSS在可调电磁屏蔽室、可调空间电磁滤波器、可调雷达天线等领域的研究进展,并重点阐述了AFSS在智能吸波结构上的应用,最后归纳了AFSS分析方法。     

基于FHT似然比检验的CRN协作频谱感知方案

针对认知无线电网络中由于噪声功率不确定性而影响频谱检测性能的问题,提出了一种基于模糊似然比检验的协作频谱检测方法。首先,将每个次用户(SU)中的噪声不确定性均建模为模糊假设检验(FHT);然后,在FHT上利用似然比检验构建带有阈值的模糊能量检测器,该阈值依赖于噪声功率不确定性边界;最后,在融合中心结合SU的局部硬决策并做出最终决策,从而检测主用户是否存在。通过Monte Carlo模拟受试者ROC曲线及检测概率/SNR曲线验证了本文方法的有效性,仿真结果表明,相比其他几种较新的能量检测器,本文方法获得了更好的检测性能。     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

Improving energy efficiency of incremental relay based cooperative communications in wireless body area networks

In this paper, we investigate the energy efficiency of an incremental relay based cooperative communication scheme in wireless body area networks (WBANs). We derive analytical expressions for the energy efficiency of direct and cooperative communication schemes taking into account the effect of packet error rate. The following communication scenarios specific to a WBAN are considered: (i) in‐body communication between an implant sensor node and the gateway, and (ii) on‐body communication between a body surface node and the gateway with line‐of‐sight (LOS) and non‐LOS channels. The results reveal a threshold behavior that separates regions where direct transmission is better from regions where incremental relay cooperation is more useful in terms of energy efficiency. It is observed that, compared with direct communication, incremental relay based cooperative communication schemes improves the energy efficiency significantly. Further, cooperation extends the source‐to‐destination hop length over, which energy efficient communication can be achieved as compared with direct communication. We also observe that, for both direct as well as cooperative transmission schemes in error prone channels, an optimal packet size exists that result in maximum energy efficiency. Copyright © 2013 John Wiley & Sons, Ltd.     

认知无线电中基于拟合优度的频谱盲检测算法研究

首先,提出噪声方差未知情况下基于t分布的Anderson-Darling的认知无线电频谱盲检测方法,通过计算接收到信道采样样本均值和方差比的分布函数与f分布函数之间的Anderson-darling距离,实现频谱检测.其次,提了基于特征函数的频谱盲检测算法,通过计算接收到的样本经验特征函数与已知特征函数的距离,判决信道中是否存在信号传输.最后,给出了衰落信道下,所提2种基于拟合优度的频谱盲检测算法的虚警概率和检测概率下界.理论和仿真表明,噪声方差未知情况下,所提2种频谱盲检测算法比传统的噪声方差已知时的能量检测法具有更好的性能.在低信噪比和小样本条件下,性能提高表现的尤其明显.     

Enhancing the spectral efficiency and energy efficiency of underwater channel communication by optimal cooperative spectrum sensing using hybrid optimization

Underwater wireless sensor networks (UWSNs) contain quite a lot of components such as vehicles and sensors that are deployed in a specific acoustic area to perform collaborative monitoring and data collection errands. These networks are adopted interactively between diverse nodes and ground‐based stations. Currently, UWSNs face problems and challenges that pertain to limited bandwidth, media access control, high propagation delay, 3D topology, spectrum sensing, resource utilization, routing, and power constraints. This proposal deals with the intelligent spectrum sensing in underwater cognitive sonar communication networks (CSCN). Here, the improved performance of spectrum sensing in underwater communication is attained by optimizing the cooperative spectrum sensing and data transmission. The parameters of system like subchannel allocation and transmission power is optimized by a new hybrid meta‐heuristic algorithm by integrating the concepts of deer hunting optimization algorithm (DHOA) and lion algorithm (LA) termed as lion‐enabled DHOA (L‐DHOA). The main intention of optimizing these parameters is to maximize the spectrum efficiency (SE) and energy efficiency (EE) of the underwater channel communication system. From the analysis, with respect to convergence rate, minimum detection probability, and local sensing time, it is proved that the novel hybrid optimization algorithm keeps a great role in making the trade‐off between the SE and EE in underwater channel modeling.     

Energy efficiency of virtual multi‐input,multi‐output based on sensor selection in wireless sensor networks

In this paper, a weighted node selection technique in wireless sensor networks is proposed. It is an energy‐efficient cooperative technique where a selected number of sensors at the transmitting end are connected with a selected number of sensors at the receiving end to form a virtual multi‐input multi‐output. The proposed technique is based on a weighted selection function that combines geographical location, inter‐sensor distance in a cluster, channel estimate energy, power circuit, channel loss, mobility factor, and residual energy of each sensor. The weight of each of these parameters in the selection function depends on the degree that this parameter affects the energy consumption. Then, the cluster head selects the sensors with better selection parameters that reduce the overall energy consumption. The numerical results show that the proposed weighted node selection technique achieves a significant improvement in the energy consumption, delay, and network lifetime than the conventional techniques with and without the selected number of sensors. Its improvement reaches 15% in the energy consumption that leads to an increase in the network lifetime by four times the network lifetime of other techniques. Copyright © 2012 John Wiley & Sons, Ltd.