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.     

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.     

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.     

Effective autocorrelation-based spectrum sensing technique for cognitive radio network applications

Spectrum sensing based on detection techniques enables cognitive radio networks to detect vacant frequency bands. The spectrum sensing gives the opportunity to increase the radio spectrum channels re-utilization. However, the main challenge in spectrum sensing is the simplicity of the considered detection approach and the amount of prior information needed to make an accurate decision. This paper proposes a novel sensing technique based on the autocorrelation function. This novel approach is based on the speed of convergence to zero of all autocorrelation coefficients. This technique shows the highest probability of detection for the same probability of false alarm target at low signal-to-noise ratio (SNR) compared with many standard detection techniques. The proposed method has been implemented using GNU Radio software and SDR (software-defined radio) platforms. The experimental results show the effectiveness of the proposed method under real scenarios.     

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.     

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.     

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.     

认知网络中的多用户MIMO线性协作频谱感知问题研究

研究了多用户MIMO的线性协作频谱感知问题以提高频谱检测的可靠性,推导了多用户MIMO线性协作感知系统的局部检测和全局检测策略,建立了在给定误警概率的情况下控制中心通过优化给各个用户的信号所分配的权值来最大化全局检测概率的优化模型。进一步,引入了遗传算法来求解上述全局检测优化问题的最优权值,期望能够有效降低算法在频谱感知过程中检测时间。仿真结果表明,多入多出能够明显提高协作频谱感知系统频谱检测可靠性,而遗传算法高效且稳定,相比较其他算法能够有效改善系统的检测性能。     

Energy-efficient cooperative sensing and transmission in relay-assisted cognitive radio network

An innovative EE-oriented cooperative sensing and transmission scheme in relay-assisted cognitive radio networks,called energy-efficient best-relay cooperative transmission (BCT) was proposed.Based on the BCT scheme,mean energy efficiency (MEE) maximization problem with sensing duration and transmitting power as optimization variables was modeled for fading channels under constraint of minimal secondary outage probability.By virtue of Jensen’s inequality,the original optimization problem was decomposed into two relatively independent subproblems which solved sensing duration and power allocation respectively.And for the two subproblems,an efficient cross iteration based algorithm was proposed to obtain the suboptimal solutions.Both analytical and simulation results demonstrate that the proposals can achieve significantly higher EE while enhancing reliability of secondary transmission remarkably compared to non-cooperation single cognitive transmission schemesin high QoS requirement.     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

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.     

SNR-based weighted cooperative spectrum sensing in cognitive radio networks

Cooperative spectrum sensing (CSS) is an approach to confront fading environment. However, in conventional cooperative spectrum sensing (CCSS), the difference among the secondary users (SUS) is ignored when SUS suffer from different fading. In this article, a signal-to-noise ratio (SNR)-based weighted spectrum sensing scheme is proposed to improve the sensing performance. The sensing performance of the weighted spectrum sensing scheme is then derived. Considering the minor contribution of the SUS with small weighted factor, a selective CSS scheme is proposed, where SUS with low SNR are not selected into cooperative spectrum sensing. The simulation results confirm the analytical results. And the performance of weighted scheme is better than that of conventional schemes. In the case where the SNR of SUS are randomly distributed, the performance of selective scheme is almost the same as the weighted scheme while the number of cooperative SUS is reduced to save the consumption of system resource in cooperation with little additional complexity.     

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。     

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.     

多输入多输出系统基于特征函数频谱盲检测

提出多输入多输出（Multiple-Input Multiple-Output,MIMO）认知无线电系统中基于多元特征函数的频谱盲检测方法.所提方法不需要知道授权用户传输信号的先验知识,也不需要知道信道噪声的方差.通过计算次用户多天线系统接收到的信号样本向量的经验特征函数,MIMO系统中的频谱检测就转换为多元特征函数检验问题.通过度量经验特征函数与已知特征函数的距离, 实现频谱检测.在MIMO系统中,基于特征函数的频谱检测算法比现存的频谱检测方法,具有更好的性能,特别是在低信噪比、小样本条件下.     

利用秩和检验的多天线协作频谱感知

高效稳定的频谱感知是认知无线电系统的关键环节.传统的能量检测算法受噪声不确定性影响,而协方差矩阵类算法在天线相关性低时性能较差.针对上述缺陷,利用秩来衡量由信道衰落导致的同一感知时刻不同天线上的信号功率差异,提出通过构建秩和统计量来实现频谱感知的算法.另外,推导了所提算法判决门限的理论表达式,结果显示其不受采样点数影响,因此当采样点数变化时无需重新设置门限.理论分析和仿真表明所提算法不受噪声不确定度的影响,并且在低天线相关性时可以保持良好的性能.     

基于压缩感知和最小二乘的分布式协作频谱感知

针对认知无线电(CR)集中式频谱感知算法对融合中心要求高,而且对节点失效的容忍性也不高等缺点,提出了一种基于压缩感知的分布式多节点协作算法.认知无线电网络中每个CR节点在接收信号频谱后,首先根据压缩采样理论在本地获取压缩采样测量值,然后利用l1范数约束的最小二乘算法在本节点估计频谱,把在此节点估计的频谱传给下一相邻节点,以此进行迭代优化直到算法收敛.理论分析和仿真结果表明,所提算法不仅计算复杂度低,收敛速度快,而且精确重构性能好,可靠性较高.     

基于人工神经网络的认知无线电频谱感知研究

认知无线电是一种新的智能无线通信技术,通过感知周围环境特征,并采用构建理解的方法进行学习。频谱感知技术是认知无线电系统设计的重要组成部分,本文提出了基于人工神经网络（ANN）算法的认知无线电感知技术。由于单用户检测存在检测精度不高的问题,本文通过采用ANN的自主学习能力设计频谱检测分类器,对以往分类器所收集的环境信息进行学习和储存,从而对以后感知新的环境时起到先验信息的作用,能快速准确地判决出主用户的存在与否。通过与能量检测和循环平稳检测对不同调制方式信号进行信号识别仿真实验可以看出,相比原有的单用户频谱检测技术,ANN具有更高的有效性和可靠性。