Parameters optimization for cooperative sensing in multi‐channel cognitive radio networks

In this paper, we propose a relatively complete and robust optimization model under the scenario where multisecondary users cooperatively sense multi‐channels. The objective of this model is to maximize the system throughput, meanwhile aims to jointly optimize the parameters including the sensing time and the weight coefficients of the sampling results. Because this model is a nonlinear optimization model, we instead adopt a heuristic sequential parameters optimization method (SPO) to solve the model. The method begins with deriving the lower bound of the objective function of the optimization model. Then, it maximizes this lower bound by optimizing the weight coefficients through solving a series of suboptimal problems using Lagrange method. Given that the weight coefficients are found, it finally transforms the problem into another monotonic programming problem and exploits a fast‐convergent polyblock algorithm to find an optimized sensing time parameter. We finally conduct extensive experiments by simulations. The results demonstrate that, in terms of the throughput gained by the system, SPO can deliver a solution that is up to 99.3% of the optimal on average, which indicates that SPO can solve the proposed optimization model effectively. In addition, we also show the performance advantage of the proposed model on improving the system throughput by comparing with other state‐of‐the‐art optimization models. Wireless Communications and Mobile Computing. Copyright © 2012 John Wiley & Sons, Ltd.     

Centralized spectrum leasing via cooperative SU assignment in cognitive radio networks

As the increasing demand of the radio spectrum, the researchers pay more attention to the technology of cognitive radio networks to improve the use of the scarce spectrum resources. Recently, cooperative communications combining with cognitive radio have been proposed in many literatures to improve the channel capacity. The primary users with poor transmission environment transmit their packets with the assistance of the secondary users (SUs) by offering them spectrum resources. This paper first raises issues in existing works, such as non‐optimal selection, selection collision, and transmission interruption. Aiming at these issues, we design a centralized system model and a cooperative relaying protocol for multiple primary user pairs to dynamically lease spectrum in exchange for the transmission assistance of SUs. Then we define 2 problems of the cooperative SU assignment to maximize total rate and maximize number of assigned SUs. We prove they are NP‐hard and propose a local search algorithm for the objective of maximize total rate and a ‐approximation algorithm for another objective. Our simulation results show that our system and algorithms can effectively improve the performance of the wireless networks.     

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.     

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.     

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.     

New coalition formation game for spectrum sharing in cognitive radio networks

In cognitive radio networks, Secondary Users (SUs) can access the spectrum simultaneously with the Primary Users (PUs) in underlay mode. In this case, interference caused to the licensed users has to be effectively controlled. The SUs have to make spectrum access decisions in order to enhance their quality of service, but without causing harmful interference to the coexisting PUs. In this paper, we propose a cooperative spectrum decision, which enables the SUs to share the spectrum with the PUs more efficiently. Our approach is based on a new coalitional game in which the coalition value is a function of the SUs' spectral efficiencies, the inter‐SUs interference, and the interference caused to the PUs. By applying new Enter and Leave rules, we obtain a stable coalition structure. Simulation results show that the SUs' spectral efficiencies are considerably increased and that the interference caused to the coexisting PU is reduced by about 7.5% as compared to an opportunistic spectrum access scheme. Moreover, the proposed coalitional game results in a more balanced spectrum sharing in the network. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

基于信道统计特征的认知无线电协作频谱检测

针对认知无线电到融合中心间的控制信道为Nakagami-m衰落信道的情况,研究了认知无线电协作频谱检测问题,推导出融合中心利用衰落信道统计特征的似然比协作频谱检测公式.该方法不需要瞬时信道状态信息,简化了协作频谱检测过程,便于实际应用.通过仿真对融合中心的协作频谱检测性能进行了分析,结果表明:利用衰落信道统计特征的似然比协作频谱检测的性能较利用瞬时信道状态信息的似然比频谱检测性能略有下降,但是在高信噪比或衰落不严重的情况下,二者的性能非常接近,认知无线电节点个数对两种频谱检测方法间的性能差距几乎没有影响.     

Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

With the advent of various emerging wireless products, the usage of limited spectrum has grown exponentially in the recent years. In the next few years, that mobile data traffic globally is expected to grow up to 50 EB/month, which is nearly a five times increase over year 2018. Therefore, it will become extremely difficult to satisfy the ever increasing demand through the current fixed spectrum assignment policy in which spectrum band is exclusively used for the particular applications, and it has also led to underutilization of a significant portion of the spectrum (like TV bands). Cognitive radio networks has emerged as a possible solution for the problem which makes dynamic spectrum access possible for unlicensed user when licensed user is not active. Among various operations of cognitive radio, channel assignment to the unlicensed user is very important. Further, wireless regional area network is one of the most important application of cognitive radio, which provides wireless broadband to the rural area using vacant TV channels. This paper discusses channel assignment techniques considering various functionalities for cognitive radio networks in respect of wireless regional area network in the existing literature. Initially, a comprehensive introduction to both cognitive radio networks and wireless regional area networks is provided, and in the end, the paper summarizes the various issues and research challenges in the channel assignment for wireless regional area networks.     

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.     

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.     

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.     

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.     

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.     

认知自组网分布式频谱感知最优协作算法

认知无线电技术使得自组织网络节点能够充分利用空闲频谱资源,提高了传输性能。通过协作频谱感知,可有效解决由于无线信道存在阴影、噪声和衰落等情况导致的单节点感知准确性偏低。为了解决梯度算法随着协作节点数量增大后计算复杂度变高,文中提出部分梯度算法ψ-GBCS,该模型通过基于SNR的动态阈值保证了感知准确性,同时通过最佳协作节点数提高了感知效率。仿真结果表明,该模型下,综合评估系统效率和性能的J函数值提高37%,能耗降低50%,有效保证大规模认知自组网频谱感知的鲁棒性,降低了对主用户的干扰及设备功耗。     

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.     

认知无线网络按需协同感知和信道分配

结合路由发现和维护过程中控制消息的广播特性,提出将频谱协同感知和信道分配的交互信息部分融入路由控制消息的方法。认知用户的信息交互随按需路由发现过程而启动,并在路由沿线建立协同感知节点簇,利用路由维护消息对该节点簇进行维护。同时以认知网络容量最大化为目标,提出将频谱协同感知和信道分配联合设计。仿真分析表明,减少了认知用户的信息交互开销,缓解了认知无线网络中控制信道的瓶颈影响,对空闲频谱进行了高效再利用。     

Polyphase filter bank based multi‐band spectrum sensing in cognitive radio systems

Spectrum sensing has been identified as an essential enabling functionality for cognitive radio (CR) systems to guarantee that CR users could share the spectrum resource with licensed users on a non‐interfering basis. Recently, simultaneous sensing of multi‐band licensed user activity has been attracting more and more research interest. Generally, the multi‐band sensing is implemented through energy detection by estimating power spectral density. In this paper, we investigate a multi‐band energy detection architecture based on different polyphase filter banks (PFBs), which aim to reliably sense multiple active bands by exploiting the low power leakage property of PFB. We have theoretically derived the closed‐form expressions of detection probability and false alarm probability for PFBs and fast Fourier transform based detectors, respectively. Theoretical detection thresholds are therefore computed, which ensures a fair comparison for different detectors. Final experimental results are presented to verify our theoretical analysis and demonstrate that PFBs based sensing architecture exhibits better sensing performance than the conventional FFT.Copyright © 2014 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.