Optimal Energy-Efficient Transmission for Hybrid Spectrum Sharing in Cooperative Cognitive Radio Networks

In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.

Cooperative Jamming for Enhancing Security of Cognitive Radio Networks with Multiple Primary Users

In cognitive radio networks(CRNs), through recruiting secondary user(SU) as friendly jammer, the secrecy rate obtained by primary user(PU) can be improved. Previous work only considered a simple scenario with a single PU in their frameworks. In this paper, we will consider a more complicated scenario with multiple PUs and try to investigate the cooperative jamming between multiple PUs and a single SU. When there are multiple PUs in CRN, in order to obtain more spectrum for data transmission, SU will cooperate with multiple PUs at the same time. Considering that both PU and SU are rational and selfish individuals, the interaction between PUs and SU is formulated as a multi-leaders and single-follower Stackelberg game, wherein PU is the leader and SU is the follower. And the Stackelberg Equilibrium(SE) is considered as the final decisions accepted by all PUs and SU. Furthermore, we also prove that when a specific condition is satisfied, the existence of SE can be guaranteed. And a Gauss-Jacobi iterative algorithm is proposed to compute a SE. Finally, simulation results are given to verify the performance and demonstrate that both of the PUs' secrecy rate and the SU's transmission rate can be improved through cooperation.

Power Allocation for Cooperative Communications in Non-Orthogonal Cognitive Radio Vehicular Ad-Hoc Networks

To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.

A weighted selection combining scheme for cooperative spectrum prediction in cognitive radio networks

A weighted selection combining （WSC） scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity. First, a genetic algorithm-based neural network （GANN） is designed to perform spectrum prediction in consideration of both the characteristics of the primary users （PU） and the effect of fading. Then, a fusion selection method based on the iterative self-organizing data analysis （ISODATA） algorithm is designed to select the best local predictors for combination. Additionally, a reliability-based weighted combination rule is proposed to make an accurate decision based on local prediction results considering the diversity of the predictors. Finally, a Gaussian approximation approach is employed to study the performance of the proposed WSC scheme, and the expressions of the global prediction precision and throughput enhancement are derived. Simulation results reveal that the proposed WSC scheme outperforms the other cooperative spectrum prediction schemes in terms of prediction accuracy, and can achieve significant throughput gain for cognitive radio networks.

Cooperative Spectrum Sensing for Cognitive Radio-Wireless Sensors Network Based on OR Rule Decision to Enhance Energy Consumption in Greenhouses

Wireless sensors networks (WSNs) combined with cognitive radio have developed and solved the limited space of the frequency spectrum. In this paper, we propose different types of spectrums sensing and their own decisions depend on the probabilities that applied into fusion center, and how these probabilities’ techniques help to enhance the energy consumption of WSNs. In the same way, the importance of designing balanced distribution between the wireless sensors networks and their own sinks. This research also provides an overview of security issues in CR-WSN, especially in Spectrum Sensing Data Falsification (SSDF) attacks that enforces harmful effects on spectrum sensing and spectrum sharing. We adopt OR rule as four types of CRSN sensing protocolin greenhouses application by using Matlab and Netsim simulators. Our results show that the designing balanced wireless sensors and their sinks in greenhouses are very significant to decrease the energy, which is due to the traffic congestion in the sink range area. Furthermore, by applying OR rule has enhanced the energy consumption, and improved the sensors network lifetime compared to cognitive radio network.

A Fault-Tolerant Cooperative Spectrum Sensing Algorithm over Cognitive Radio Network Based on Wireless Sensor Network

A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effects complicate handling such attackers even further. This enforces the system to acquire authentication. Actually, the decision maker needs to determine the reliability or trustworthiness of the shared data. In this paper, the evaluation process is considered as an estimation dilemma on a set of evidences obtained through sensor nodes that are coordinated in an underlying wireless sensor network. Then, a likelihood-based computational trust evaluation algorithm is proposed to determine the trustworthiness of each sensor node's data. The proposed procedure just uses the information which is obtained from the sensor nodes without any presumptions about node’s reliability. Numerical results confirm the effectiveness of the algorithm in eliminating malicious nodes or faulty nodes which are not necessarily conscious attackers.

Cooperative Spectrum Sensing Deployment for Cognitive Radio Networks for Internet of Things 5G Wireless Communication

Recently,Cooperative Spectrum Sensing(CSS)for Cognitive Radio Networks(CRN)plays a significant role in efficient 5G wireless communication.Spectrum sensing is a significant technology in CRN to identify underutilized spectrums.The CSS technique is highly applicable due to its fast and efficient performance.5G wireless communication is widely employed for the continuous development of efficient and accurate Internet of Things(IoT)networks.5G wireless communication will potentially lead the way for next generation IoT communication.CSS has established significant consideration as a feasible resource to improve identification performance by developing spatial diversity in receiving signal strength in IoT.In this paper,an optimal CSS for CRN is performed using Offset Quadrature Amplitude Modulation Universal Filtered Multi-Carrier Non-Orthogonal Multiple Access(OQAM/UFMC/NOMA)methodologies.Availability of spectrum and bandwidth utilization is a key challenge in CRN for IoT 5G wireless communication.The optimal solution for CRN in IoT-based 5G communication should be able to provide optimal bandwidth and CSS,low latency,Signal Noise Ratio(SNR)improvement,maximum capacity,offset synchronization,and Peak Average Power Ratio(PAPR)reduction.The Energy Efficient All-Pass Filter(EEAPF)algorithm is used to eliminate PAPR.The deployment approach improves Quality of Service(QoS)in terms of system reliability,throughput,and energy efficiency.Our in-depth experimental results show that the proposed methodology provides an optimal solution when directly compares against current existing methodologies.

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,cognitive radio networks(CRNs)may also impose some challenges due to the ever increasing complexity of network architecture,the increasing complexity with configuration and management of large-scale networks,fluctuating nature of the available spectrum,diverse Quality-of-Service(QoS)requirements of various applications,and the intensifying difficulties of centralized control,etc.Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm.In this paper,fundamentals of CR,including spectrum sensing,spectrum management,spectrum mobility and spectrum sharing,have been surveyed,with their paradigms of self-organization being emphasized.Variant aspects of selforganization paradigms in CRNs,including critical functionalities of Media Access Control(MAC)- and network-layer operations,are surveyed and compared.Furthermore,new directions and open problems in CRNs are also identified in this survey.

New Optimal Power Allocation for Bidirectional Communications in Cognitive Relay Network Using Analog Network Coding

Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information with the assistance of a relay node under interference power constraints.In order to enhance the transmit rate and maintain fairness between two source terminals,a practical 2-phase analog network coding protocol is adopted and its optimal power allocation algorithm is proposed.Numerical results verify the superiority of the proposed algorithm over the conventional direct transmission protocol and 4-phase amplify-and-forward relay protocol.

Cache-Enabled in Cooperative Cognitive Radio Networks for Transmission Performance

The proliferation of mobile devices that support the acceleration of data services(especially smartphones)has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents.Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user’s effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching.

Detection time analysis for the multiple-user cooperative spectrum sensing scheme in cognitive radio networks

In this paper, a novel multiple-user cooperative spectrum sensing （MCSS） scheme is proposed to achieve the spatial diversity gains for cognitive radio （CR） networks, where only the best relay, selected among all the candidate relays in accordance with the quality of channel conditions, is utilized to cooperatively detect the primary user. Closed-form expressions of detection time for the traditional non-cooperative and the proposed MCSS schemes are derived over Rayleigh fading channels. In addition, numerical experimentations are conducted to make a performance comparison between the noncooperative sensing and our scheme. The result shows that by exploiting the multiple-user cooperation, the detection time is reduced greatly and moreover, diversity gains obtained by the MCSS scheme increase with a rise in the number of candidate relays.

Optimal fusion rule for cooperative spectrum sensing in cognitive radio networks

In this paper, we analyze performance of cooperative spectrum sensing under counting rules when exponential model is utilized to characterize the burst nature of primary user （PU） link. Our objective is to minimize the average error probability （AEP） so that the link utilization in the considered link achieves its maximum. We derive a closed-form expression of AEP as well as the probability of interference （PoI） by classifying cognitive transmission into six events. Then, we consider the minimization of AEP over counting rules under the constraint of interference. As the solution, we develop an efficient algorithm to evaluate the optimal fusion rule. Finally, we verify our analysis in numerical results.

Energy efficiency optimization of cognitive relay network based on cooperative spectrum sensing

This paper focuses on the energy efficiency of cognitive relay （CR） networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio （SNR） is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.

Cooperative automatic modulation recognition in cognitive radio

In this article, a new effective method of cooperative modulation recognition （CMR） is proposed to recognize different modulation types of primary user for cognitive radio receivers. In the cognitive radio （CR） system, two CR users respectively send their feature parameters to the cooperative recognition center, which is composed of back propagation neural network （BPNN）. With two users＇ cooperation and the application of an error back propagation learning algorithm with momentum, the center improves the performance of modulation recognition, especially when one of the CR users＇ signal-to-noise ratio （SNR） is low. To measure the performance of the proposed method, simulations are carried out to classify different types of modulated signals corrupted by additive white Gaussian noise （AWGN）. The simulation results show that this cooperation algorithm has a better recognition performance than those without cooperation.

Reputation-based linear cooperation for spectrum sensing in cognitive radio networks

We propose a reputation-based cooperative spectrum sensing scheme in cognitive radio (CR) networks to solve the uncertainty resulting from the multipath fading and shadowing effect. In the proposed scheme, each cooperative CR user has a reputation degree that is initialized and adjusted by the central controller, and used to weight the sensing result from the corresponding CR user in the linear fusion process at the central controller. A simple method for adjusting the reputation degree of CR users is also presented. We analyzed and evaluated the detection performance of the reputation-based cooperative spectrum sensing scheme. Simulation results showed that our proposed scheme alleviates the problem of corrupted detection resulting from destructive channel conditions between the primary transmitter and the CR user. The performance of our proposed scheme was improved compared to the average-based linear cooperation scheme, and was similar to that of the optimal linear cooperation scheme with feasible computational complexity. Moreover, our proposed scheme does not require knowledge of channel statistics.

基于流形神经网络的协作频谱感知

针对传统频谱感知在复杂信号环境,如低信噪比和多路径衰落等情况下的性能局限,提出了一种基于黎曼流形神经网络的创新性协作频谱感知方案。该方法首先通过将多个协作用户的信号矩阵映射到黎曼流形上,生成具有几何特性的协方差矩阵。接着,利用黎曼流形神经网络进行高效的信号特征分类和频谱感知。黎曼流形神经网络不仅充分发挥了黎曼流形在非欧几里得数据结构上的优势,而且结合了神经网络强大的表达能力,从而在各种复杂环境下都展示出显著优越的频谱感知性能。通过一系列详细的仿真实验,证明了该方法在多样化环境下的优越性能,展示了其在实际无线通信系统中的潜在应用价值。

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper, we present a non-transferable utility coalition graph game （NTU-CGG） based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing （OFDMA） based cognitive radio networks to maximize both system throughput and system faimess. In this algorithm, with the assistance of others SUs, SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs. So this scheme can effectively exploit both space and frequency diversity of the system. Performance results show that, NTU-CGG significantly improves system faimess level while not reducing the throughput comparing with other existing algorithms.

Managing Energy Consumption of Wireless Sensors Networks in Multiple Greenhouses

An extensive area implementation of fully observed greenhouses motivates on research, especially in remote greenhouses. However, implementation of wireless sensor networks (WSNs) is still needed for investigation. Cognitive radio sensor networks (CRSNs) took advantage of using the cognitive radio (CR) concept to which allowed wireless sensor networks to dynamically access into white space channels which is unused channels. In this paper, we adopted the Generalized Implicit-OR as CRSN sensing protocol to reduce the energy consumption and increase the network lifetime in multiple numbers of greenhouses. Our results showed that enhanced energy consumption and improved network lifetime compared to ordinary WSN.

基于随机共振和信息几何的协作频谱感知方法

为提高频谱感知系统在低信噪比环境下对微弱信号的感知性能,提出了一种基于随机共振技术和信息几何理论的频谱感知方法。首先通过随机共振技术增强输入信号的能量,以提高感知信号的信噪比。然后,基于信息几何理论将信号矩阵的协方差矩阵对应成流形上的点,并计算流形上样本点之间的散度距离作为感知信号的特征数据。最后,采用BP神经网络对信号特征数据进行分类,有效避免了决策阈值的计算,快速实现了频谱决策。仿真实验证明,所提方法在低信噪比条件下具有更好的感知性能,有效提高了复杂环境下的频谱检测概率。

基于多头自注意力机制的协作频谱感知算法

针对协作频谱感知中部分用户受到阴影、衰落等影响导致在低信噪比环境下对微弱信号的感知性能急剧降低及部分聚类模型没有充分利用能量向量的问题,提出一种基于多头自注意力机制的协作频谱感知算法。各次用户独立采样数据,融合中心收集各次用户的能量数值并构成能量向量作为自注意力网络的输入;设计基于多头自注意力机制的网络模型,利用该网络自动学习信号和噪声的能量向量特征,有效提取局部特征,实现智能协作频谱感知。仿真结果表明,该频谱感知算法性能优于对比算法,在信噪比为-14 dB、虚警概率为0.001时,该算法检测概率高于对比算法0.29~0.4。