Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

Sensor node-assisted asynchronous cooperative spectrum sensing for cognitive radio network

In order to take advantage of the asynchronous sensing information, alleviate the sensing overhead of secondary users （SUs） and improve the detection performance, a sensor node-assisted asynchronous cooperative spectrum sensing （SN-ACSS） scheme for cognitive radio （CR） network （CRN） was proposed. In SN-ACSS, each SU is surrounded by sensor nodes （SNs）, which asynchronously make hard decisions and soft decisions based on the Bayesian fusion rule instead of the SU. The SU combines these soft decisions and makes the local soft decision. Finally, the fusion center （FC） fuses the local soft decisions transmitted from SUs with different weight coefficients to attain the final soft decision. Besides, the impact of the statistics of licensed band occupancy on detection performance and the fact that different SNs have different sensing contributions are also considered in SN-ACSS scheme. Numerical results show that compared with the conventional synchronous cooperative spectrum sensing （SCSS） and the existing ACSS schemes, SN-ACSS algorithm achieves a better detection performance and lower cost with the same number of SNs.     

基于认知无线电的频谱检测技术研究

信息时代无线通信飞速发展,许多需要较宽频谱和较高下载速率的业务,如多媒体通信业务,已经成为无线服务的重点对象。认知无线电是一种智能的无线通信技术,可以通过感知周围环境来自动调整其发射机参数,其核心思想是利用已分配但未获得充分利用的频谱,从而提高频谱利用率避免对主用户造成干扰是认知无线电最需要解决的问题,频谱感知则是实现这一目标的前提。     

Cluster‐based coordination scheme for cooperative cognitive radio networks

In this paper, a cluster‐based two‐phase coordination scheme for cooperative cognitive radio networks is proposed considering both spectrum efficiency and network fairness. Specifically, candidate secondary users (SUs) are first selected by a partner selection algorithm to enter the two‐phase cooperation with primary users (PUs). In phase I, the selected SUs cooperate with PUs to acquire a fraction of time slot as a reward. In phase II, all SUs including the unselected ones share the available spectrum resources in local clusters; each of which is managed by a cluster head who participated in the cooperation in phase I. To improve the total network utility of both PUs and SUs, the maximum weighted bipartite matching is adopted in partner selection. To further improve the network performance and communication reliability, network coding is exploited during the spectrum sharing within the cluster. Simulation results demonstrate that, with the proposed cluster‐based coordination scheme, not only the PUs' transmission performance is improved, but also SUs achieve spectrum access opportunities. Copyright © 2015 John Wiley & Sons, Ltd.     

Sensing‐throughput tradeoff for cooperative multiple‐input single‐output cognitive radio

In this paper, we propose a new cooperative multiple‐input single‐output (MISO) cognitive radio (CR) system, which can use some of the antennas to transmit its data and the others to help to transmit the data of the primary user (PU) by performing cooperative communication if the presence of the PU is detected through the cooperative spectrum sensing. A new cooperative sensing‐throughput tradeoff model is proposed, which maximizes the aggregate rate of the CR by jointly optimizing sensing time and spatial sub‐channel power, subject to the constraints of the aggregate rate of the PU, the false alarm and detection probabilities, the aggregate interference to the PU and the aggregate power of the CR. Simulation results show that compared with the conventional scheme, the proposed cooperative scheme can achieve the larger aggregate rate of the CR, while keeping the aggregate rate of the PU invariable with the increasing of the interference. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimization of 2‐stage cooperative spectrum for cognitive radio networks using multi‐antenna energy detectors

Cooperative spectrum sensing, a kind of spectrum sensing scheme in cognitive radio (CR), uses multiple CR relays. To increase performance, this study uses multi‐antenna CR relays and beam‐forming reception. The required bandwidth for reporting channels in cooperative spectrum sensing is crucial. Two‐stage cooperative spectrum sensing is proposed to increase performance without increasing the required bandwidth. The cooperative spectrum sensing is also optimized to allow the CR networks to facilitate the best decision‐making. This study determines the detection performance when beam‐forming reception is used. Numerical simulations are used to validate the effectiveness of the method. It is shown that beam‐forming reception outperforms square‐law combining (SLC) for low SNR values. This study proposes a 2‐stage cooperative spectrum sensing method, which uses multi‐antenna CR relays and beam‐forming reception. The cooperative spectrum sensing is also optimized to allow the CR networks to facilitate the best decision‐making. Numerical simulations are used to validate the effectiveness of the method.     

认知网络中协作感知吞吐量的优化

为了提高集中式认知网络的吞吐量,提出了基于信任度的吞吐量优化算法.该算法在主用户充分保护的前提下,以认知用户的吞吐量为目标函数,融合中心采用双门限值对本地感知结果进行融合.从理论上证明了吞吐量是全局漏检概率的增函数,当全局漏检概率等于门限值时,吞吐量达到最大值.并利用牛顿迭代法求出单节点概率,然后采用遍历法可得到认知用户吞吐量最大值.仿真结果表明,当信噪比为-14 dB时认知用户融合优化算法相对"AND准则"OR准则"以及"HALF准则"归一化吞吐量分别提高了0.62、0.3和0.09.     

Different sensing durations‐based cooperative spectrum sensing in cognitive radio systems

In order to provide more accurate detection of the primary user's activity in cognitive radio (CR) systems, cooperative spectrum sensing is proposed. The transmit diversity can also be employed by cooperative spectrum sensing to improve the performance of decision reporting. Hence, in the reporting channels between the cognitive users and the base station (BS), space time block code (STBC) scheme is considered in each cluster with time division multiple access (TMDA) method. In this paper, to improve the time efficiency in the case that one cluster makes sensing report, whereas the others do nothing but wait for their orders, we set each cluster with different sensing durations and the clusters will not stop the spectrum sensing until their results are reported. Furthermore, we also adopt the flexible sensing durations to decrease unnecessary energy consumption based on the clusters’ sensing sensitivities. Simulation results and analysis show the better detection performance and time efficiency of the proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

Improved cooperative spectrum sensing based on the reputation in cognitive radio networks

Cognitive radio (CR) is a promising technology to improve the utilisation of wireless spectrum resources. Spectrum sensing is the core functionality in CR networks (CRN). When there exist malicious users (MUs) in CRN and MUs start to attack the network after accumulating reputation to some extent, the performance is deteriorated. In this paper, a scheme is proposed by employing Orthogonalized Gnanadesikan–Kettenring (OGK) to mitigate the effect of MUs without the assistance of trusted nodes, and it can improve the robustness of CRN. Simulations verify the effectiveness of the proposed scheme.     

Joint cooperative spectrum sensing and channel selection optimization for satellite communication systems based on cognitive radio

Cognitive radio has attracted considerable attention because of its ability to make full use of the available spectrum resources for wireless terrestrial communication networks. In addition, the satellite communication scenario, which requires a transparent air interface to integrated/hybrid Satellite–Terrestrial communication systems and provides a supplement for other multimedia services, will cause frequency scarcity. Satellite communication systems based on cognitive radio are available under scenarios that involve transmission with changing communications. In this paper, a cooperative spectrum‐sensing algorithm based on a time or bandwidth‐based cooperative spectrum‐sensing model of an integrated/hybrid cooperative satellite communication system is proposed. Moreover, the concept of weighted cooperative spectrum sensing is introduced. Compared with the traditional single‐user spectrum‐sensing algorithm, the cooperative spectrum sensing is able to cope with the interference to the primary user caused by a secondary user better. In addition, multiple earth stations that use some part of the bandwidth cooperatively to perform spectrum sensing throughout the whole frame can detect the presence of primary user in time. The satellite component combines the sensing results from earth stations to reach a final decision, and the optimal combination weights to maximize the detection probability of the secondary user are obtained. Numerical results that demonstrate the performance of the proposed algorithm are presented. Copyright © 2015 John Wiley & Sons, Ltd.     

Cross‐layer optimization for full‐duplex cognitive radio network with cooperative spectrum sensing

In this paper, the cross‐layer optimal design of multihop ad hoc network employing full‐duplex cognitive radios (CRs) is investigated. Firstly, the analytical expressions of cooperative spectrum sensing performance for multihop CR networks over composite fading channels are derived. Then, the opportunistic throughput and transmit power of CRs are presented based on the derivation of false alarm and missed detection probability. Finally, a multiobjective optimization model is proposed to maximize the opportunistic throughputs and minimize the transmitting power. Simulation results indicate that Pareto optimal solution of sensing duration, decision threshold, and transmit power can be achieved by cross‐layer multiobjective optimization, it can balance the conflicts between different objective functions and reap the acceptable outcomes for multihop CR network.     

A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. 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.     

基于合作博弈的多信道认知无线网络中的频谱共享算法简

采用合作博弈对多信道认知无线网络中的频谱共享问题进行了建模分析,提出了次用户在各信道上的信干噪比乘积作为合作博弈的效用函数。次用户在各信道上保证对主用户的干扰小于一定门限的要求下,通过最大化各自效用函数的乘积来进行功率分配。由于最大化次用户效用函数的乘积问题是非凸的,通过变量替换将其转化为了一个等价的凸优化问题,利用该凸优化问题的对偶分解,提出了一种次用户间的频谱共享算法。仿真结果表明,所提算法在次用户和速率与公平性之间进行了有效折中。     

Adaptive dual‐radio spectrum‐sensing scheme in cognitive radio networks

In this paper, a novel spectrum‐sensing scheme, called adaptive dual‐radio spectrum‐sensing scheme (ADRSS), is proposed for cognitive radio networks. In ADRSS, each secondary user (SU) is equipped with a dual radio. During the data transmission, with the received signal‐to‐noise ratio of primary user (PU) signal, the SU transmitter (SUT) and the SU receiver (SUR) are selected adaptively to sense one channel by one radio while communicating with each other by the other one. The sensing results of the SUR are sent to the SUT through feedback channels (e.g., ACK). After that, with the sensing results from the SUT or the SUR, the SUT can decide whether the channel switching should be carried out. The theoretical analysis and simulation results indicate that the normalized channel efficiency, defined as the expected ratio of time duration without interference to PUs in data transmission to the whole frame length, can be improved while satisfying the interference constraint to PUs. After that, an enhanced ADRSS is designed by integrating ADRSS with cooperative spectrum sensing, and the performance of ADRSS under imperfect feedback channel is also discussed. Copyright © 2011 John Wiley & Sons, Ltd.     

Smart antenna‐assisted spectrum sensing for robust detection in cognitive radio networks

In this paper, we consider the problem of multiband spectrum sensing by employing smart antenna arrays at the cognitive receiver. Although energy detection is widely used for spectrum sensing in cognitive radio networks because of its simplicity and accuracy, it is severely deteriorated by the noise uncertainty. This paper introduces robust spectrum sensing techniques to circumvent this difficulty, which operate simultaneously over the total frequency channels rather than a single channel each time. To enhance the detection performance, the proposed schemes jointly utilize the information of eigenvalues and eigenvectors, signal and noise subspace components in conjunction with the likelihood functions and Gerschgorin radii. Neither subjective decision threshold setting nor the estimation of noise power is required in our schemes, making them robust to noise uncertainty. Simulations are presented to validate the performance of the proposed schemes, and the results show that our schemes can outperform other existing spectrum sensing methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Detection efficiency of cooperative spectrum sensing in cognitive radio network

Sensing the spectrum in a reliable and efficient manner is crucial to cognitive radio. To combat the channel fading suffered by the single radio, cooperative spectrum sensing is employed, to associate the detection of multiple radios. In this article, the optimization problem of detection efficiency under the constraint of detection probability is investigated, and an algorithm to evaluate the required radio number and sensing time for maximal detection efficiency is presented. To show the effect of cooperation on the detection efficiency, the proposed algorithm is applied to cooperative sensing using the spectral correlation detector under the Rayleigh flat fading channel.     

Cluster‐based adaptive multispectrum sensing and access in cognitive radio networks

Spectrum sensing and access have been widely investigated in cognitive radio network for the secondary users to efficiently utilize and share the spectrum licensed by the primary user. We propose a cluster‐based adaptive multispectrum sensing and access strategy, in which the secondary users seeking to access the channel can select a set of channels to sense and access with adaptive sensing time. Specifically, the spectrum sensing and access problem is formulated into an optimization problem, which maximizes the utility of the secondary users and ensures sufficient protection of the primary users and the transmitting secondary users from unacceptable interference. Moreover, we explicitly calculate the expected number of channels that are detected to be idle, or being occupied by the primary users, or being occupied by the transmitting secondary users. Spectrum sharing with the primary and transmitting secondary users is accomplished by adapting the transmission power to keep the interference to an acceptable level. Simulation results demonstrate the effectiveness of our proposed sensing and access strategy as well as its advantage over conventional sensing and access methods in terms of improving the achieved throughput and keeping the sensing overhead low. Copyright © 2012 John Wiley & Sons, Ltd.     

多无人机协作的认知通信网络中能/谱效折中优化

在无人机（Unmanned Aerial Vehicle,UAV）认知通信网络中,其能量受限和通信高吞吐量问题备受关注。然而,能量效率（Energy Efficiency,EE）的提升可能会导致频谱效率（Spectrum Efficiency,SE）的下降。针对此问题,对UAV协作认知通信网络中EE和SE的折中优化进行了研究。首先,进行了感知时间、UAV通信的发射功率和判决门限各自对SE与EE两者的优化;其次,通过二分法求解使得EE和SE最大化的感知时间值,并通过穷尽搜索法分别求解感知时间、UAV通信的发射功率和判决门限对EE和SE折中优化问题的最优参数值。在此基础上,提出一种联合参数迭代优化算法,求解EE和SE的折中优化问题。仿真实验表明,SE和EE之间存在折中的权衡,并验证了所提优化方案的有效性。     

A selective decision–fusion rule for cooperative spectrum sensing using energy detection

Increasing the number of terminals in a cognitive radio network is known to improve the accuracy of cooperative spectrum sensing at the cost of reducing the useful communication time. This downside can be partially mitigated using decision‐based fusion and/or sequential reporting. This paper proposes a novel selective decision‐based cooperative spectrum sensing strategy that limits the reporting time to a single reporting slot with a possibility for retransmissions using automatic repeat request. The terminal with the highest energy estimate sends its local decision to the fusion center to make a final decision. Potential decoding errors are mitigated using threshold‐based automatic repeat request. The performance of the proposed strategy is studied using rigorous mathematical analysis and intensive computer simulations. Results show observable performance enhancements compared with some benchmark strategies in terms of detection accuracy and agility. Copyright © 2015 John Wiley & Sons, Ltd.