Optimal multiband joint detection in cognitive radio networks with the Taguchi method

This paper studies multiband joint detection in cognitive radio networks with the Taguchi method. At the fusion center, linear fusion rule is adopted to collect the observations from distributed secondary users. We aim to achieve maximum aggregate throughput with limited aggregate interference. The problem is challenging due to its nonconvexity and high computational complexity to find the global optimum. Existing works attempt to convert the problem into convex optimization problem. In this paper, the Taguchi method is employed to estimate the gradient of the aggregate throughput, determine the optimal thresholds of the energy detectors and combination weights of the linear fusion rule regardless of convexity. To optimize thresholds and linear weights simultaneously, we employ newly defined variables to represent the changing ranges of detector thresholds when we search for optimal linear weights. In addition, the sensing duration is another factor to be optimized in the Taguchi method. The simulation results show that the proposed method is efficient and applicable for all classes of cognitive radio without considering convexity. The optimization performance is considerably improved. Moreover, the Taguchi method is insensitive to parameter initialization, which provides a relatively robust output. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed joint spectrum detection and power allocation in multi-band cognitive radio networks

This article proposes a novel dynamic spectrum sharing scheme in distributed multi-band cognitive radio networks. A non-cooperative game has been utilized to model the spectrum sharing among secondary base stations (SBSs). A distributed joint spectrum detection and power allocation algorithm is designed for maximizing the downlink throughput of secondary networks. Simulation results demonstrate that the proposed algorithm converges fast and achieves a better throughput performance than uniform threshold case. Meanwhile, the convergence of algorithm is proved by Nikaido-Isoda (N-I) function method.     

基于认知无线电的多频段跳频通信系统

为充分利用认知无线电对环境频谱的感知能力,设计了一种基于 认知无线电的多频段跳频抗干扰通信系统,通过感知单元动态控制跳频序列生成,实现了干 扰频点的避让。具体实现时,采用低频段可靠传输高频段的频谱感知信息,高频段则主要用 于具体业务传输,利用不同频段实现了频谱控制与应用业务的分离。     

Cooperative relay to improve diversity in cognitive radio networks

Recent studies demonstrated that dynamic spectrum access can improve spectrum utilization significantly by allowing secondary unlicensed users to dynamically share the spectrum that is not used by the primary licensed users. Cognitive radio was proposed to promote the spectrum utilization by opportunistically exploiting the existence of spectrum ?holes.? Meanwhile, cooperative relay technology is regarded widely as a key technology for increasing transmission diversity gain in various types of wireless networks, including cognitive radio networks. In this article, we first give a brief overview of the envisioned applications of: cooperative relay technology to CRNs, cooperative transmission of primary traffic by secondary users, cooperative transmission between secondary nodes to improve spatial diversity, and cooperative relay between secondary nodes to improve spectrum diversity. As the latter is a new direction, in this article we focus on this scenario and investigate a simple wireless network, where a spectrum-rich node is selected as the relay node to improve the performance between the source and the destination. With the introduction of cooperative relay, many unique problems should be considered, especially the issue for relay selection and spectrum allocation. To demonstrate the feasibility and performance of cooperative relay for cognitive radio, a new MAC protocol was proposed and implemented in a universal software radio peripheral-based testbed. Experimental results show that the throughput of the whole system is greatly increased by exploiting the benefit of cooperative relay.     

Gray space detection for cognitive radio networks

In cognitive radio (CR) networks, the gray spaces sensing scheme for classifying whether the energy source is the primary user directly affects quality of service of CR users and the throughput for the secondary networks. In this paper, we proposed a two-stage sensing scheme consisting of a series of consecutive energy detection based on generalized likelihood ratio test (GLRT) detection. Simulation results showed that the proposed sensing scheme could detect primary signal in lower signal-to-nose ratio (SNR) than energy detection, but it needs more sample numbers.     

Cooperative Q-learning based channel selection for cognitive radio networks

Wireless Networks - This paper deals with the jamming attack which may hinder the cognitive radio from efficiently exploiting the spectrum. We model the problem of channel selection as a Markov...     

考虑恶意节点的CRN合作频谱感知方法

基于带有恶意节点的更为实际的频谱感知环境,研究了基于合作感知的频谱共享网络模型,次级用户将会根据合作感知结果动态地调整其发射功率。为了防止恶意节点对感知系统的感知性能造成严重影响,研究了如何进行合作感知以提高感知性能。在一定的检测概率和相关功率约束下,建立了一个以最大化次级网络的吞吐量为目标函数的优化问题。仿真实验首先突出说明了恶意节点数目对频谱感知影响重大,同时还表明无论是否存在恶意节点,提出的算法均可有效地计算出最优的感知时间和发射功率,且在降低最大干扰功率限制和最大发射功率限制时,网络的吞吐量是增大的。     

Cooperative spectrum sensing using amplify-and-forward relaying with partial relay selection in cognitive radio networks

Cooperative spectrum sensing has been shown to be an effective approach to improve the detection performance by exploiting the spatial diversity among multiple cognitive nodes. By using the amplify-and-forward relaying with partial relay selection, this paper proposes a novel cooperative spectrum sensing scheme, which provides higher detection performance and is interesting in distributed cognitive radio networks. In the proposed sensing scheme, the “best” cognitive relay by means of partial relay selection technique amplifies and forwards the signals transmitted from the primary user (PU) to the cognitive user (CU). Then the CU detects PU’s states (i.e., presence or absence) via an energy detector. Moreover, the average missed-detection probability of proposed sensing scheme is studied over Nakagami-m fading channels, where m is a positive integer. In particular, the tight closed-form lower bounds of the average missed-detection probability are presented for the convenience of performance evaluation in practice. Finally, numerical results are provided to validate the derived closed-form lower bounds and the influence of the number of cognitive relays on the detection performance is also discussed.     

An efficient joint algorithm for reducing PAPR of SC-FDMA system in cognitive radio networks

Cognitive radio (CR) has been proposed as a solution for the spectrum scarcity problem. This paper investigates single-carrier frequency division multiple access (SC-FDMA) for cognitive radios. Recently, SC-FDMA has been suggested as a candidate for multicarrier based CR systems. In this paper, we propose enhanced techniques to reduce the peak to average power ratio (PAPR) in SC-FDMA for Cognitive Radio Network (CRN). We start by showing the effect of two standard PAPR reduction techniques (interleaver based and selective mapping) to reduce the PAPR in SC-FDMA based CR. Then, a proposed joint algorithm interleaver with selective mapping in a way that is suitable for SC-FDMA based CR will be proposed that results in a lower PAPR than using them individually. Simulation results show that the SC-FDMA with proposed techniques has a lower PAPR when compared with the conventional SC-FDMA system for CRN, while the complexity of the system slightly increases. Results also reveal that the no. of interleavers and SLM sequences must be chosen carefully in order to limit the PAPR with slightly increases in the complexity of the system.

     

Cooperative and fair MAC protocols for cognitive radio ad-hoc networks

Wireless Networks - A secondary user (SU) in multichannel cognitive radio ad hoc network (CRAHN) has a limited transmission range, which may raise a hidden multichannel sensing problem. In...     

Low-complexity centralized joint power and admission control in cognitive radio networks

This letter introduces a centralized joint power and admission control algorithm for cognitive radio networks. Its novelty lies in the proposed admission metric. Unlike those in existing algorithms, our metric predetermines the admission order of N secondary users which intend to access the network. This allows us to search a group of admitted secondary users with the bisection method. The proposed algorithm is shown by simulation to achieve a comparable performance to existing algorithms, and the computational complexity is reduced from O(N³) to O(N² log₂ N).     

Adaptive power control and beam-forming joint optimization in cognitive radio networks

A novel adaptive power control and beam-forming joint optimization algorithm is proposed in cognitive radio(CR) underlay networks,where cognitive network share spectrum with primary network which spectrum is licensed.In this paper,both primary base station(PBS) and cognitive base station(CBS) are all equipped with multi antennas,while each primary user(PU) and cognitive user(CU) has only one antenna.Different from traditional algorithms,an adaptive weight factor generating solution is supplied to different access users(both PUs and CUs) in this paper,and the different priority of users is also considered,because PUs have higher priority,the weight factor of PUs is fixed as constant and signal-to-interference and noise ratio(SINR) threshold is unchanged,while for CUs,it is set adaptively and SINR threshold is also changed accordingly.Using this algorithm,the transmit power is decreased,which relax the strict requirements for power amplifier in communication systems.And moreover,owing to PUS has fixed SINR threshold,the calculated SINR at receiver is nearly unchanged,but for CUs,the SINR is changing with the adaptive weight factor.Under the assurance of quality of service(QoS) of PUs,the solution in this paper can enable CRs access to the CR network according to adaptive SINR threshold,therefore which supplies higher spectrum utilization efficiency.     

Iterative optimization of detection threshold and throughput for secondary users in multiband cognitive radio systems

In cognitive radio(CR) systems,efficient spectrum sensing ensures the secondary user(SU) to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by ...     

A reliable cooperative spectrum detection scheme in cognitive radio networks

Reliable spectrum detection of the primary user (PU) performs an important role in the cognitive radio network since it’s the foundation of other operations. Spectrum sensing and cognitive signal recognition are two key tasks in the development of cognitive radio (CR) technology in both commercial and military applications. However, when the CR terminals receiving signals have little knowledge about the channel or signal types, these two tasks will become much more difficult. In this paper, we propose a reliable cooperative spectrum detection scheme, which combines the cooperative spectrum sensing with distributed cognitive signal recognition. A novel improved cooperative sensing algorithm is achieved by using a credibility weight factor and the “tug-of-war” rule, which is based on the double threshold detection and Dempster–Shafer theory, to determine whether the PU signals exist. In this scheme, cognitive signal recognition can be used to identify the signal type when the PU signal is present. During the cognitive signal recognition processing, the CR terminals make local classification of the received signals by using Daubechies5 wavelet transform and Fractional Fourier Transform, and send their recognition results to the globe decision making center. A distributed processing uses these cognitive terminals’ local results to make final decisions under the Maximum Likelihood estimation algorithm. Simulation results show that the proposed method can achieve good sensing probability and recognition accuracy under the Additive White Gaussian Noise channel.     

Multicast communications in cognitive radio networks using directional antennas

This paper presents a study on multicast communications in cognitive radio networks (CRNs)using directional antennas. The objective is to maximize the throughput of the CRN. The spectrum is divided into multiple channels and licensed to the primary network. While the CRN is accessing the spectrum, the interference power is carefully controlled to avoid impacting the operation of the primary network. The mathematical model is presented and subsequently formulated as a mixed integer non‐linear programming (MINLP) problem, which is non‐deterministic polynomial‐time hard. Therefore, a greedy algorithm is designed to approximate the optimal performance. The MINLP problem is then relaxed and an upper bound is developed. Simulation results are presented to compare the performance of the greedy algorithm and the upper bound, which demonstrates the efficacy of the greedy algorithm as well as the tightness of the upper bound. Copyright © 2012 John Wiley & Sons, Ltd.     

基于人工智能技术的认知无线网络重构决策算法

认知无线网络引入重构技术以实现对复杂时变环境的动态适应,为在认知无线网络中实现重构,提出了重构架构模型,并在此模型基础上进行重构决策算法的研究,提出了基于人工智能技术的重构决策算法。该决策算法包括了推理过程和学习过程,使重构技术在认知无线网络感知能力、推理能力和学习能力的帮助下实现了对环境的适应并同时维护和提升了系统性能。     

Enhancing cooperative spectrum sensing in cognitive radio ad hoc networks using priority-based two-stage detection model

Cooperation among unlicensed secondary users was more significant in cognitive radio ad hoc networks (CRAHNs). The main challenges of CRAHNs now a day address the main issues of spectrum scarcity and underutilization. Due to the lack of channel sensing, cooperative spectrum sensing (CSS) is the main challenge in CRAHNs. Efficient CSS is more essential to enhance the detection of performance by utilizing the theoretical studies of spatially distributed secondary users (SUs). This paper uses the priority-based two-stage detection model (PBTSDM) to analyze the cooperation strategy among secondary users (SUs) and primary users (PUs). SUs in distributed CSS sense continuously amongst themselves and take unified decision on the presence or absence of PUs by using entropy-based energy detection mechanism. The simulation results reveal that the sensing accuracy in terms of sensing time and energy efficiency (in terms of minimum energy consumption) increased significantly by using the proposed scheme.

     

Securing cognitive radio networks

Cognitive radio is a promising technology aiming to improve the utilization of the radio electromagnetic spectrum. A cognitive radio device uses general purpose computer processors that run radio applications software to perform signal processing. The use of this software enables the device to sense and understand its environment and actively change its mode of operation based on its observations. Unfortunately, this solution entails new security challenges. Our objective in this paper is to analyze the security issues of the main recent developments and architectures of cognitive radio networks. We present vulnerabilities inherent to those systems, identify novel types of abuse, classify attacks, and analyze their impact on the operation of cognitive radio‐based systems. Moreover, we discuss and propose security solutions to mitigate such threats. Copyright © 2010 John Wiley & Sons, Ltd.     

On cognitive processes in cognitive radio networks

In this article we model the cognitive processes and evaluate their impact on the performance of cognitive radio networks (CRN). Operation of the cognitive radio nodes, can be characterized by two types of processes: communication processes such as packets transmission, and cognitive processes such as estimation of the network state and decision-making for dynamic resource allocation. We propose a continuous time Markov chain model of CRN that couples these processes into unified queueing framework and analyze it by means of the matrix-geometric approach. From the obtained results, we derive the performance measures of CRN such as average delay and throughput, and establish their dependencies on the underlying cognitive processes. Additionally, we design an efficient policy for accessing the vacant channels and managing the transmission-sensing trade-off, which arises when transmissions and sensing are mutually exclusive. The policy search is carried out by the stochastic optimization method of cross-entropy. The optimized policy leads to significantly enhanced performance of CRN.