A new feature extraction and attacking node classification framework using PDCFE‐HPSMM model in cognitive radio networks

The increasing demand of wireless communication introduces a challenge to an effective spectrum utilization. In wireless communication systems, the Cognitive Radio (CR) has emerged as a new key technology to address this issue, which allows an opportunistic access to the spectrum. The CRs form a CRN by extending the radio link features to network layer functions. The existing CR based wireless communication techniques has some drawbacks such as, inability to differentiate interference or noise from primary signals, it does not distinguish the different types of noise, low performance, not effective in spread spectrum detection, long observation time and high computational cost. To overwhelm these disadvantages, a novel method, namely, partial distribution based cyclostationary feature extraction–hidden probability state Markov model (PDCFE‐HPSMM) is proposed in this work. The main intention of this technique is to extract the node features, classify the attacker nodes and predict the licensed and unlicensed bandwidth. At first, the CRN is formed with some set of CR nodes, and the communication links between the nodes are estimated. Then, the node features are extracted by employing the PDCFE technique. After that, the attacking nodes are classified based on those features with the help of a HPSMM classification technique. If the attacker is present in the network, the link between the attacking nodes to other nodes is disconnected; otherwise, the communication link is updated. In this work, the Rayleigh channels are used to predict the licensed and unlicensed bandwidth. Again, the HPSMM model is employed to optimally select the channel, and the scheduling technique is implemented to check the status of the channel for message transmission. If the channel is not busy, the message signals are multiplexed and transmitted to the receiver via the selected channel. The novel concept of this paper is, the proposed PDCFE technique extracts the features of the nodes in CRN; based on these features, the attacker nodes in the network are classified with the help of HPSMM technique. Moreover, the HPSMM is used to select the optimal channel for message transmission. The experimental results evaluate the performance of the proposed system in terms of bit error rate (BER), error rate, relay, false detection rate (FDR) and cumulative distribution function (CDF). Copyright © 2016 John Wiley & Sons, Ltd.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

DCR‐MAC: distributed cognitive radio MAC protocol for wireless ad hoc networks

The MAC protocol for a cognitive radio network should allow access to unused spectrum holes without (or with minimal) interference to incumbent system devices. To achieve this main goal, in this paper a distributed cognitive radio MAC (DCR‐MAC) protocol is proposed for wireless ad hoc networks that provides for the detection and protection of incumbent systems around the communication pair. DCR‐MAC operates over a separate common control channel and multiple data channels; hence, it is able to deal with dynamics of resource availability effectively in cognitive networks. A new type of hidden node problem is introduced that focuses on possible signal collisions between incumbent devices and cognitive radio ad hoc devices. To this end, a simple and efficient sensing information exchange mechanism between neighbor nodes with little overhead is proposed. In DCR‐MAC, each ad hoc node maintains a channel status table with explicit and implicit channel sensing methods. Before a data transmission, to select an optimal data channel, a reactive neighbor information exchange is carried out. Simulation results show that the proposed distributed cognitive radio MAC protocol can greatly reduce interference to the neighbor incumbent devices. A higher number of neighbor nodes leads to better protection of incumbent devices. Copyright © 2008 John Wiley & Sons, Ltd.     

联合循环平稳特征PCA与RVM的频谱感知

针对无线信道环境中低信噪比情况下主用户信号检测率较低的问题,提出了一种基于循环平稳特征主成分分析(PCA)与相关向量机(RVM)的认知网络频谱感知算法。该算法结合了主成分分析算法与相关向量机分类方法,应用于解决认知网络频谱感知问题。首先对信号循环平稳特征参数进行特征提取,通过主成分分析进行降维提取信号主成分,生成训练样本和待测样本,并完成对相关向量机的训练,再采用训练完成的相关向量机算法分别对有无主用户情况下的信号进行分类检测,最后获得主用户信号存在性的感知判断。仿真实验表明,与人工神经网络、支持向量机和最大最小特征值算法相比较,所提算法在低信噪比情况下具有较高的分类检测性能,检测率最大可提高61.6%,有效地实现了对主用户信号的感知。     

Beamforming for inter‐relay interference reduction in MIMO‐aided two‐path successive relaying

To effectively reduce the inter‐relay interference (IRI) in two‐path successive relaying, two beamforming schemes are proposed in this paper, utilizing multiple‐antenna relay nodes. Specifically, the two cooperation nodes perform receive combining of the source signal and transmit beamforming of the relayed signal alternately in the successive relaying process. As a result, the IRI between them can be effectively suppressed, thanks to the additional degree of freedom provided by the multiple‐input multiple‐output inter‐relay channel. In the first beamforming scheme, the source‐to‐destination signal‐to‐interference‐plus‐noise ratios (SINR) of separate paths are maximized with approximation, leading to a minimum variance distortionless response beamformer under the high SINR condition. To further improve the system performance, noting that the received SINRs of the two paths have impact on each other due to the mutual coupling of the beamformers, the sum of mean squared errors from these two transmission paths is minimized in the second scheme. Based on this performance criterion, a suboptimal beamformer design is developed numerically through cyclic minimization of the sum of mean squared error cost function. Simulation results demonstrate the superiority of both proposed beamforming schemes in terms of symbol error rate and the achievable system rate, in particular, at high IRI levels. Copyright © 2016 John Wiley & Sons, Ltd.     

Modified Bayesian algorithm‐based compressive sampling for wideband spectrum sensing in cognitive radio network using wavelet transform

This paper presents the implementation of a modified version of Bayesian relevance vector machine (RVM)‐based compressive sensing method on cognitive radio network with wavelet transform for spectrum hole detection. Bayesian compressive sensing is used in this work to deal with the complexity and uncertainty of the process. The dependency of the Bayesian compressive sensing on the knowledge of noise levels in the measurement has been relaxed through the proposed Bayesian RVM‐based compressive sensing algorithm. This technique recovers the wideband signals even with fewer measurements maintaining considerably good accuracy and speed. Wavelet transform is used in this paper to enable the detection of primary user (PU) even in the low regulated transmission from unlicensed user. The advantage of this approach lies in the fact that it enables the evaluation of all possible hypotheses simultaneously in the global optimization framework. Simulation study is performed to evaluate the efficacy of the proposed technique over the cognitive radio environment. The performance of the proposed technique is compared with the conventional Bayesian approach on the basis of recovery error, recovery time and covariance to verify its superiority.     

RAD‐EI: A routing attack detection scheme for edge‐based Internet of Things environment

Internet of Things (IoT) offers various types of application services in different domains, such as “smart infrastructure, health‐care, critical infrastructure, and intelligent transportation system.” The name edge computing signifies a corner or edge in a network at which traffic enters or exits from the network. In edge computing, the data analysis task happens very close to the IoT smart sensors and devices. Edge computing can also speed up the analysis process, which allows decision makers to take action within a short duration of time. However, edge‐based IoT environment has several security and privacy issues similar to those for the cloud‐based IoT environment. Various types of attacks, such as “replay, man‐in‐the middle, impersonation, password guessing, routing attack, and other denial of service attacks” may be possible in edge‐based IoT environment. The routing attacker nodes have the capability to deviate and disrupt the normal flow of traffic. These malicious nodes do not send packets (messages) to the edge node and only send packets to its neighbor collaborator attacker nodes. Therefore, in the presence of such kind of routing attack, edge node does not get the information or sometimes it gets the partial information. This further affects the overall performance of communication of edge‐based IoT environment. In the presence of such an attack, the “throughput of the network” decreases, “end‐to‐end delay” increases, “packet delivery ratio” decreases, and other parameters also get affected. Consequently, it is important to provide solution for such kind of attack. In this paper, we design an intrusion detection scheme for the detection of routing attack in edge‐based IoT environment called as RAD‐EI. We simulate RAD‐EI using the widely used “NS2 simulator” to measure different network parameters. Furthermore, we provide the security analysis of RAD‐EI to prove its resilience against routing attacks. RAD‐EI accomplishes around 95.0% “detection rate” and 1.23% “false positive rate” that are notably better than other related existing schemes. In addition, RAD‐EI is efficient in terms of computation and communication costs. As a result, RAD‐EI is a good match for some critical and sensitive applications, such as smart security and surveillance system.     

The off‐grid frequency selective millimeter wave channel estimation

Broadband millimeter wave (mmW) systems are a promising pioneer of cellular communication for next generation which is utilizing the hybrid baseband/analog beamforming structures along with the miniature massive antenna arrays at both sides of the communication link. mmW channel with an available unlicensed spread spectrum is frequency selective because the signal bandwidth can be larger than the coherence bandwidth. Due to the sparse nature of mmW channel, extracting compressive sensing model of the system is preferable. In fact, exploiting the sparse structure will lead to the reduction of the computational complexity, because there is a reduction in the channel training length compared with the conventional methods such as least square estimation. Most of the prior works have considered on‐grid quantized departure/arrival angles in the input/output antennas to obtain a sparse virtual channel model. However, the sparse angles in the physical channel model are continuous where this continuity indicates a mismatch between the physical angles and the on‐grid angles. Such a mismatch will contribute to unwanted components in the virtual channel model. Given these extra components, the conventional compressive sensing tools are unable to recover the channel. In this paper, we propose two solutions for overcoming the problem caused by off‐grid angle selection. The first is based on the vector shaping, and the second one is based on the sparse total least square concepts. Simulation results demonstrate that the proposed methods both could obtain an adequate channel recovery and are preferable regarding computational complexity concerning the newly developed surrogate method.     

Quickest physical‐layer MGD anomaly detection for jamming attacks in centralized modulated wideband converter‐based ROC curve

In wireless communication systems, physical‐layer security menaces have evolved from jammers. Jammers, due to their furtive nature, make wireless communication systems vulnerable. The novelty in this work is to combine centralized modulated wideband converter, which is a networking system developed from the modulated wideband converter–based sub‐Nyquist sampling theory with a multivariate Gaussian distribution (MGD) anomaly detector‐based receiver operating characteristic curve that plot the detection rate (DR) versus false alarm rate (FAR) at various threshold values. We supposed the presence of a group of jammers in the spectrum corrupted with the primary source signal and noise. The received primary signal at each cognitive radio (CR) receiver is converted in to a digital signal using an analog‐to‐information converter. Each CR receiver give minimum number of samples denoted N₁. All these compressed samples from every CR receiver are collected in the form of matrix called compressed sampling matrix, which is considered directly as the input of the MGD detector. The intelligent MGD detector proposed in the level of fusion center is based on the characteristics of the MGD. The numerical results show that this new system of combination detects faster anomalies perfectly in the presence of jammers in the spectrum in real‐time scenarios. Performance evaluation is performed in terms of DR versus FAR at different detection threshold values, under the presence of attacks in the system. By employing well‐known machine learning algorithms called MGD, the performance of this new proposed system shows good.     

Sub‐Nyquist rate ADC sampling‐based compressive channel estimation

To realize high‐speed communication, broadband transmission has become an indispensable technique in the next‐generation wireless communication systems. Broadband channel is often characterized by the sparse multipath channel model, and significant taps are widely separated in time, and thereby, a large delay spread exists. Accurate channel state information is required for coherent detection. Traditionally, accurate channel estimation can be achieved by sampling the received signal with large delay spread by analog‐to‐digital converter (ADC) at Nyquist rate and then estimate all of channel taps. However, as the transmission bandwidth increases, the demands of the Nyquist sampling rate already exceed the capabilities of current ADC. In addition, the high‐speed ADC is very expensive for ordinary wireless communication. In this paper, we present a novel receiver, which utilizes a sub‐Nyquist ADC that samples at much lower rate than the Nyquist one. On the basis of the sampling scheme, we propose a compressive channel estimation method using Dantzig selector algorithm. By comparing with the traditional least square channel estimation, our proposed method not only achieves robust channel estimation but also reduces the cost because low‐speed ADC is much cheaper than high‐speed one. Computer simulations confirm the effectiveness of our proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

An enhanced two‐phase SVM algorithm for cooperative spectrum sensing in cognitive radio networks

Cognitive radio (CR) networks have emerged recently to address the problem of spectrum scarcity. As reliable spectrum sensing (SS) is vital in low signal‐to‐noise ratio (SNR) for CR networks, we propose a novel method of enhancing support vector machines (SVM) classifier named as 2‐Phase SVM for the task of SS in a cooperative sensing structure. In this study, the vectors containing energy levels of primary users (PU) are considered as feature vectors and are fed into the classifier during training and test phase. First, the classifier is trained; afterward, the test feature vectors are labeled as channel available class or channel unavailable class in an online fashion by using 2‐Phase SVM, which is applied during two phases compared with the conventional SVM algorithm. The performance of suggested cooperative SS method is evaluated by receiver operating characteristic (ROC) curve and the functionality of our proposed algorithm is qualified in terms of misclassification error rate in addition to misclassification risk. The results reveal that 2‐Phase SVM outperforms previous methods since it not only increases the classification accuracy and reduces the misclassification risk but also enhances the detection probability.     

Joint spectrum sensing and resource allocation optimization using genetic algorithm for frequency hopping–based cognitive radio networks

In cognitive radio (CR) networks, secondary users should effectively use unused licensed spectrums, unless they cause any harmful interference to the primary users. Therefore, spectrum sensing and channel resource allocation are the 2 main functionalities of CR networks, which play important roles in the performance of a CR system. To maximize the CR system utility, we propose a joint out‐of‐band spectrum sensing and operating channel allocation scheme based on genetic algorithm for frequency hopping–based CR networks. In this paper, to effectively sense the primary signal on hopping channels at each hopping slot time, a set of member nodes sense the next hopping channel, which is called out‐of‐band sensing. To achieve collision‐free cooperative sensing reporting, the next channel detection notification mechanism is presented. Using genetic algorithm, the optimum sensing and data transmission schedules are derived. It selects a sensing node set that participate the spectrum sensing for the next expected hopping channel during the current channel hopping time and another set of nodes that take opportunity for transmitting data on the current hopping channel. The optimum channel allocation is performed in accordance with each node's individual traffic demand. Simulation results show that the proposed scheme can achieve reliable spectrum sensing and efficient channel allocation.     

Frequency shift filter‐based multi‐carrier transceiver

It is well known that orthogonal frequency division multiplexing (OFDM) is sensitive to carrier frequency offset (CFO) and suffers from a high peak‐to‐average ratio. In addition, the performance of OFDM is severely affected by strong co‐channel interference and strong narrowband interference. To mitigate the limitations of OFDM, we propose a new multi‐carrier transceiver based on frequency‐shift filter. A frequency‐shift filter can separate spectrally overlapping sub‐carrier signals by exploiting the spectral correlation inherent in the cyclostationary modulated signals. To increase spectral efficiency, we increase the percentage of spectral overlap between two adjacent sub‐channels. We derive an upper bound and a lower bound on the bit error rate performance of the proposed multi‐carrier transceiver in additive white Gaussian noise channel and frequency‐nonselective Rayleigh fading channel, respectively. Compared with OFDM, our simulation results show that the proposed multi‐carrier transceiver is much less sensitive to CFO and has a lower peak‐to‐average ratio; moreover, without any additional interference suppression technique, the proposed transceiver has the advantage of being able to mitigate strong co‐channel interference with CFO from the intended multi‐carrier signal and mitigate strong narrowband interference in additive white Gaussian noise channel and in Rayleigh fading channel in which a large CFO between the transmitted signal and the received signal often occurs. Copyright © 2011 John Wiley & Sons, Ltd.     

An end‐to‐end channel allocation scheme for a wireless mesh network

Co‐channel interference seriously influences the throughput of a wireless mesh network. This study proposes an end‐to‐end channel allocation scheme (EECAS) that extends the radio‐frequency‐slot method to minimize co‐channel interference. The EECAS first separates the transmission and reception of packets into two channels. This scheme can then classify the state of each radio‐frequency‐slot as transmitting, receiving, interfered, free, or parity. A node that initiates a communication session with a quality of service requirement can propagate a channel allocation request along the communication path to the destination. By checking the channel state, the EECAS can determine feasible radio‐frequency‐slot allocations for the end‐to‐end path. The simulation results in this study demonstrate that the proposed approach performs well in intra‐mesh and inter‐mesh communications, and it outperforms previous channel allocation schemes in end‐to‐end throughput. Copyright © 2013 John Wiley & Sons, Ltd.     

Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

Vehicular Ad hoc NETwork (VANET) is considered as the appropriate candidate for provisioning risk‐free environment that confirms secure cooperation and very minimal congestion among the vehicular nodes in the network. The establishment and maintenance of connectivity between vehicular nodes are determined to be influenced by the existence of Non‐Line‐of‐Sight (NLOS) nodes that introduce channel congestion and broadcasting storm into the network during emergency message delivery. Thus, NLOS nodes need to be localized with optimality for enhancing the emergency data delivery rate with minimized latency degree and energy consumption in the network. In this paper, Harris Hawk Optimization Algorithm (HHOA)‐based NLOS nodes Localization Scheme (NLOS‐LS) (HHOA‐NLOS‐LS) is proposed for facilitating reliable data dissemination among vehicular nodes under emergency situations. HHOA utilizes chasing styles and cooperative behavior of Harris hawks termed as surprise pounce for efficient localization based on reference nodes. In particular, the intelligent strategy of Harris hawks' behavior in attacking the prey in all directions is included for localizing the NLOS nodes from the reference nodes positioned in all directions of the network. It is capable of localizing the NLOS nodes based on adaptive localizing (chasing) styles attained through reference nodes dependingon the dynamic nature of NLOS nodes. The simulation results prove that the mean localization rate is improved by 23.21%, mean neighborhood awareness rate by 19.82%, mean emergency message delivery rate by 18.32% and mean channel utilization by 17.28% when compared to the baseline Weighted Inertia‐based Dynamic Virtual Bat Algorithm (WIDVBA)‐based NLOS‐LS (WIDVBA‐NLOS‐LS), Cooperative Volunteer Vehicular Nodes (CVVN)‐based NLOS‐LS (CVVN‐NLOS‐LS), Vote Selection Mechanisms and Probabilistic Data Association (VSMPDA)‐based NLOS‐LS (VSMPDA‐NLOS‐LS), and Weighted Distance Hyperbolic Prediction (WDHP)‐based NLOS‐LS (WDHP‐NLOS‐LS) for a varying number of vehicular nodes in the network.     

基于功率谱密度的通信辐射源个体识别方法

为阻止设备克隆、重放攻击和用户身份假冒等问题的发生,准确识别和认证物联对象,提出一种基于功率谱密度指纹特征与智能分类器的通信辐射源个体识别方法。利用接收机采集I路射频基带信号;通过方差轨迹检测截取稳态信号片段,并对稳态信号片段进行数据标准化处理;计算数据标准化处理后的稳态信号片段的功率谱密度得到特征向量,将所述特征向量作为发射机的射频指纹;最后利用智能分类器识别所述射频指纹,完成通信辐射源个体识别。通过对同厂家、同型号、同批次的8个无线数传电台E90-DTU设备和100个WiFi网卡设备的实验测试表明,本文所提方法在视距(LOS)场景、视距场景与非视距(NOS)场景的混合场景、低信噪比场景、大数量物联设备场景都具有良好的识别准确率。     

Utility‐based resource allocation in uplink of OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically on the basis of non‐interfering to licensed users. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA‐based cognitive radio networks. The objective is to maximize the system utility, which is used as an approach to balance the efficiency and fairness of wireless resource allocation. First, a theoretical framework is provided, where necessary and sufficient conditions for utility‐based optimal subcarrier assignment and power allocation are presented under certain constraints. Second, based on the theoretical framework, effective algorithms are devised for more practical conditions, including ellipsoid method for Lagrangian multipliers iteration and Frank–Wolfe method for marginal utilities iteration. Third, it is shown that the proposed scheme does not have to track the instantaneous channel state via an outage‐probability‐based solution. In the end, numerical results have confirmed that the utility‐based resource allocation can achieve the optimal system performance and guarantee fairness. Copyright © 2009 John Wiley & Sons, Ltd.     

Simultaneous Information and Power Transfer for Multi‐antenna Primary‐Secondary Cooperation in Cognitive Radio Networks

In this paper, cognitive radio and simultaneous wireless information and power transfer (SWIPT) are effectively combined to design a spectrum‐efficient and energy‐efficient transmission paradigm. Specifically, a novel SWIPT‐based primary‐secondary cooperation model is proposed to increase the transmission rate of energy/spectrum constrained users. In the proposed model, a multi‐antenna secondary user conducts simultaneous energy harvesting and information forwarding by means of power splitting (PS), and tries to maximize its own transmission rate under the premise of successfully assisting the data delivery of the primary user. After the problem formulation, joint power splitting and beamforming optimization algorithms for decode‐and‐forward and amplify‐and‐forward modes are presented, in which we obtain the optimal PS factor and beamforming vectors using a golden search method and dual methods. Simulation results show that the proposed SWIPTbased primary‐secondary cooperation schemes can obtain a much higher level of performance than that of non‐SWIPT cooperation and non‐cooperation schemes.     

Secure multicast routing protocols in mobile ad‐hoc networks

A mobile ad‐hoc network (MANET) is a collection of autonomous nodes that communicate with each other by forming a multi‐hop radio network. Routing protocols in MANETs define how routes between source and destination nodes are established and maintained. Multicast routing provides a bandwidth‐efficient means for supporting group‐oriented applications. The increasing demand for such applications coupled with the inherent characteristics of MANETs (e.g., lack of infrastructure and node mobility) have made secure multicast routing a crucial yet challenging issue. Recently, several multicast routing protocols (MRP) have been proposed in MANETs. Depending on whether security is built‐in or added, MRP can be classified into two types: secure and security‐enhanced routing protocols, respectively. This paper presents a survey on secure and security‐enhanced MRP along with their security techniques and the types of attacks they can confront. A detailed comparison for the capability of the various routing protocols against some known attacks is also presented and analyzed. Copyright © 2013 John Wiley & Sons, Ltd.