A weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks

Spectrum sensing plays a critical role in cognitive radio networks. A good sensing scheme can reduce the false alarm probability and the miss detection probability, and thus improves spectrum utilization. This paper presents a weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks, to increase the spectrum sensing accuracy. The framework contains two modules. In the first module, each cognitive radio performs local spectrum sensing and computes the total error probability, which combines the false alarm probability and the miss detection probability. The total error probability and the energy signal from the primary user are then sent to the base station. In the second module, the base station makes a final decision after combining the weighted energy signals from all cognitive radios. The final decision is then broadcasted back to all cognitive radios. To reduce the computation complexity and communication overhead, the base station also instructs the cognitive radios that have large total error probabilities not to report their local sensing results. We have developed a theoretical model for the proposed framework, and derived the optimal detection threshold, as well as the minimum number of cognitive radios required to participate in cooperative sensing, subject to a given total error probability. Numerical results verify that the proposed weighted cooperative spectrum sensing framework significantly improves the sensing accuracy.     

Distributed cooperative spectrum sensing in cognitive radio for ad hoc networks

Cognitive radio refers to an intelligent radio with the capability of sensing the radio environment and dynamically reconfiguring the operating parameters. Recent research has focused on using cognitive radios in ad hoc environments. Spectrum sensing is the most important aspect of successful cognitive radio ad hoc network deployment to overcome spectrum scarcity. Multiple cognitive radio users can cooperate to sense the primary user and improve sensing performance. Cognitive radio ad hoc networks are dynamic in nature and have no central point for data fusion. In this paper, gradient-based fully distributed cooperative spectrum sensing in cognitive radio is proposed for ad hoc networks. The licensed band used for TV transmission is considered the primary user. The gradient field changes with the energy sensed by cognitive radios, and the gradient is calculated based on the components, which include energy sensed by secondary users and received from neighbors. The proposed scheme was evaluated from the perspective of reliable sensing, convergence time, and energy consumption. Simulation results demonstrated the effectiveness of the proposed scheme.     

遗传算法在认知无线电频谱感知中的应用

针对基于OFDM系统的多带联合检测方法中门限向量选取问题,在一定的主用户干扰限制下,充分考虑各子信道特征,建立了门限向量优化模型。将遗传算法应用其中求解最优门限向量,使认知系统吞吐量得到了优化。仿真结果表明,这种方法比传统未使用优化而取一致门限的频谱感知方法对吞吐量的提高更有效。     

Spectrum sensing algorithms for primary detection based on reliability in cognitive radio systems

One of the main requirements of cognitive radio systems is the ability to detect the presence of the primary user with fast speed and high accuracy. To achieve that, in this paper, we propose a spectrum sensing scheme by considering the reliability of spectrum sensing. Only the user with no reliable information will perform spectrum sensing again using one-order feature detection. Otherwise, the user directly transmits its binary decision (0 or 1) to the MAC layer. The performance of the one-order feature detection is studied and numerical results are presented to show that the one-order feature detector can perform better than the energy detector due to its robustness to the noise uncertainty. Since the feature detection is performed in time domain, the real-time operation and low-power consumption can be achieved. Furthermore, the performance of proposed spectrum sensing scheme based on reliability is also deduced and the analysis of the performance results indicate that the sensing performance is greatly improved as opposed to energy detector. However, due to the effects of channel fading/shadowing, individual cognitive radios may be not able to reliably detect the existence of a primary user. To solve this problem, cooperative sensing among secondary users are studied using the methodology proposed in this paper. The performance of cooperative spectrum sensing is investigated when various decision fusion rules are applied. We find that, regardless of the decision fusion rule used, the sensing performance can be significantly improved compared to conventional cooperative methods.     

一种新型的认知无线电合作频谱感知算法*

为了提高认知无线电频谱感知性能,同时考虑到不同认知用户SU(Secondary User)具有不同的感知贡献和谈判力量,该文利用合作博弈理论提出了一种新的基于认知无线电的合作频谱感知非对称纳什谈判算法ANBS(Asymmetric Nash Bargaining Solution),该算法充分考虑到了每一个认知用户的感知可信度不尽相同的情况。仿真结果表明,与NBS(Nash Bargaining Solution)等算法相比,该算法不仅具有更强的合理性和可靠性,而且使系统整体感知性能得到了较大提高。     

一种认知无线电的联合频谱检测算法

为了改善信噪比不同的认知无线电(cognitive radio)用户的联合频谱检测性能,提出了一种基于能量检测的两个用户合作频谱检测算法。在联合虚警概率一定的条件下,根据接收信号能量对各个用户的判决门限进行调整,增大高信噪比用户对联合检测的影响,同时减小低信噪比用户的影响,来提高联合检测概率;判决结果只占用少量比特的信息,减少了通信开销。实验结果表明,所提算法很好地逼近了搜索解,提高了联合检测性能。     

一种时域—码域联合的认知无线电频谱感知算法

为了提高认知无线电系统中频谱感知的性能,对多维联合的频谱感知进行了研究,提出一种时域—码域联合的频谱感知算法。该算法主要利用了直接序列扩频主用户信号频谱空间中时域与码域的特性,分别从时域与码域的角度对信道的状态进行检测,其中时域采用能量感知,码域分析扩频主用户信号的二次功率谱,最终共同确认信道状态。仿真结果表明,联合感知算法对应的检测性能优于单纯时域或码域感知,能够直接应用于直接序列扩频主用户的频谱感知。     

利用在线异常感知的无线电网络抗SSDF攻击协作频谱感知方案

该文提出了一种时空频率CSS框架,用于检测和跟踪CR网络中的恶意用户和异常测量。联合频谱感知和恶意用户识别问题构成优化问题,且利用固有稀疏到频谱占用和恶意用户发生。提出的方案利用在线异常感进行实时识别和跟踪,通过节点位置信息获得了改进的性能,可有效处理错过或不正确的位置信息,以及PU功率级噪声SU测量。实验结果表明,提出的方案在协作感知中能够有效克服感知数据错误化(SSDF)攻击。此外,提出的方案优于现有的较为先进的基于PCA方法,具有足够的灵活性来抵御SU网络中的各种攻击。     

Volume-based method for spectrum sensing

It is recently shown that algorithms derived from random matrix theory (RMT) can provide superior performance for spectrum sensing, which corresponds to the task of detecting the presence of primary users in cognitive radio. The essence of the RMT-based methods is to utilize the distribution of extremal eigenvalues of the received signal sample covariance matrix (SCM), namely, the Tracy–Widom (TW) distribution. Although the TW distribution is quite useful in spectrum sensing, computationally demanding numerical evaluation is required because it does not have an explicit closed-form expression. In this paper, we devise two novel volume-based detectors by exploiting the determinant of the SCM or volume to distinguish between the signal-presence and signal-absence cases. With the use of RMT, we accurately produce the theoretical decision threshold for one of the detectors under the Gaussian noise assumption. Simulation results are included to illustrate the effectiveness of the volume-based detectors.     

A cognitive management framework for spectrum selection

To increase cognitive radio (CR) operation efficiency, there has been an interest in enhancing the awareness level of spectrum utilization. In this context, this paper builds a new cognitive management functional architecture for spectrum selection (SS). It relies on a knowledge manager (KM) retaining a set of advanced statistics that track the suitability of spectral resources to support a set of heterogeneous applications under varying interference conditions. Based on this architecture, a novel proactive strategy is proposed for both SS and spectrum mobility (SM) functionalities. The required interactions between the proposed decision-making processes are described, and their capability to exhibit robustness to unexpected changes in the radio environment is highlighted. The results show that the proposed strategy efficiently exploits the KM support for low loads, while the SM functionality introduces significant gains for high loads with respect to other strategies. Finally, to assess the practicality of the proposed approach, the signaling requirements in the radio interface are evaluated.     

Optimal MAC based cooperative spectrum sensing in cognitive radio networks

This paper considers a cognitive radio (CR) system in non-ideal fading wireless channels and pro-poses cooperative spectrum sensing schemes based on coherent multiple access channels (MAC),serving as an alternative way to improve the cooperative spectrum sensing performance and provide space diversity for spec-trum sensing.Sufficient statistics are transmitted using a common channel from the secondary users (SUs) to a fusion center (FC) where the global decision is obtained.The optimal scaling factors of the proposed schemes are obtained by maximizing the detection probability under a target false alarm probability and a transmit power constraint.Because the proposed optimal MAC scheme has high computational complexity,a sub-optimal solu-tion based on maximization of the deflection coefficient (DC) is also proposed.Simulation results show that the proposed algorithms can significantly improve the spectrum sensing performance and approach the detection baseline.     

认知OFDM系统中基于能耗受限的频谱感知方法

针对传统频谱感知方法没有考虑能耗受限对认知系统的影响,以认知正交频分复用(OFDM)系统为背景,提出一种基于能耗受限的联合优化频谱感知方法。该方法基于传统能量检测方法,以最大化吞吐量性能为目标,将频谱感知问题建模为一个优化问题,联合多个频带选取最优感知时间和判决门限参数,使其在能耗受限的情况下,总吞吐量达到最大。仿真结果表明,与传统使用能耗均分的检测方法相比,该方法具有更大的吞吐量,能够更好地节约能耗。     

基于可信度的认知无线电协同频谱检测

认知无线电中随着参与协同检测的认知用户数目的增大,频谱检测性能逐渐增强。但是过多的认知用户参与协同检测,会使整个认知无线电网络的灵敏度降低,同时也会造成巨大的系统开销。针对上述问题,提出了一种新的基于可信度的协同频谱检测方法。在满足目标错误概率的条件下,该算法只选择可信度较高的一些认知用户参与协同频谱检测。仿真结果表明当认知用户中存在恶意节点或者故障节点时,该算法同传统算法相比较,频谱检测性能更好,具有更强的健壮性。     

基于高效协作感知算法的认知无线电研究*

针对协作频谱感知中感知开销过高问题,提出了一种联合考虑选择最佳的感知节点数以及感知的信道数来降低协作感知开销的方法。该算法分析了协作感知算法中感知节点数、感知的授权信道数与协作感知精度以及感知开销之间的关系。仿真结果表明,与其他算法相比,该算法能够有效地降低感知开销并提高系统的感知性能,验证了该算法的有效性。     

认知无线电网络中宽频谱的信号分离算法

在认知无线电网络中,认知用户随机接入宽带频谱进行数据传输,但是这样很容易受到恶意用户的干扰,这些恶意用户随意地接入共享频带进行信号传输,这些信号会干扰主用户和认知用户。为此,提出了一种基于压缩感知的信号分离方法。该方法可以很好地从宽带信号中分离出恶意用户信号。算法主要采用以下三个步骤：（1）所有认知用户采用压缩感知技术从宽带频谱中恢复各信号;（2）认知用户将分离的信号发送到融合中心,融合中心通过小波边缘检测的方法确定频谱边缘,并按照边缘特性将频谱分成若干频段;（3）融合中心根据具体特征对每个子频段进行信号分离。分析和仿真结果表明,这种新的基于压缩感知的宽频带信号分离方法能很好地从宽带信号中将含有恶意用户干扰的混合信号分离出来。     

Instant overbooking framework for cognitive radio networks

In recent years, new emerging wireless technologies necessitate more spectrum resources compared to before. Related to this fact, cognitive radio and its capabilities provide promising functionalities in efficient management of the spectrum. In this paper, to maximize both spectrum utilization and revenue of network operators, we propose an Instant Overbooking Framework for Cognitive Radio networks (IOFCR) where different overbooking policies can be employed. Besides, the framework includes policies in order to decide which requesting secondary users (SUs) can be denied and which Active SUs can be ejected when a primary user (PU) activity is sensed. The effects of different pricing strategies used in a booking interval are also analyzed. To evaluate IOFCR, we use performance measures such as total net revenue, spectrum utilization, overbooking limit, number of free blocks, average service period, percentage of denied SUs forwarding their booking request and percentage of ejected Active SUs. In addition to being a first overbooking framework for Cognitive Radio Networks that takes several system parameters like PU on-rate, Active SU on-rate and Requesting SU show-rate into the account, to the best of our knowledge, this paper makes key contributions concerning the pricing policies, denial of requesting SUs, ejection and priority levels of active SUs. Finally, we numerically analyze the IOFCR performance by conducting numerous simulations and show the efficiency and validity in accordance with comprehensive measures mentioned above.     

Analytical modeling for spectrum handoff decision in cognitive radio networks

Cognitive Radio (CR) is an emerging technology used to significantly improve the efficiency of spectrum utilization. Although some spectrum bands in the primary user’s licensed spectrum are intensively used, most of the spectrum bands remain underutilized. The introduction of open spectrum and dynamic spectrum access lets the secondary (unlicensed) users, supported by cognitive radios; opportunistically utilize the unused spectrum bands. However, if a primary user returns to a band occupied by a secondary user, the occupied spectrum band is vacated immediately by handing off the secondary user’s call to another idle spectrum band. Multiple spectrum handoffs can severely degrade quality of service (QoS) for the interrupted users. To avoid multiple handoffs, when a licensed primary user appears at the engaged licensed band utilized by a secondary user, an effective spectrum handoff procedure should be initiated to maintain a required level of QoS for secondary users. In other words, it enables the channel clearing while searching for target vacant channel(s) for completing unfinished transmission. This paper proposes prioritized proactive spectrum handoff decision schemes to reduce the handoff delay and the total service time. The proposed schemes have been modeled using a preemptive resume priority (PRP) M/G/1 queue to give a high priority to interrupted users to resume their transmission ahead of any other uninterrupted secondary user. The performance of proposed handoff schemes has been evaluated and compared against the existing spectrum handoff schemes. Experimental results show that the schemes developed here outperform the existing schemes in terms of average handoff delay and total service time under various traffic arrival rates as well as service rates.     

Cooperative spectrum sensing based on stochastic resonance in cognitive radio networks

A new censoring cooperative spectrum sensing scheme based on stochastic resonance(SR)technique in cognitive radio(CR)network is proposed in this paper.The observations of the cooperative secondary users(SUs)whose statistics fall into the censoring interval are processed by SR system in the proposed scheme.The hard fusion and the soft fusion for the censoring cooperative spectrum sensing scheme are analyzed respectively.Theoretical analyses and simulation results show that the proposed censoring cooperative spectrum sensing scheme has the same detection performance as and lower computational complexity than the method that each cooperative SU performs spectrum sensing using SR-based energy detection,and its detection performance is superior to that of the conventional method that all the cooperative SUs perform spectrum sensing using energy detection in hard fusion.In soft fusion,the proposed censoring cooperative spectrum sensing based on equal gain combination can achieve the optimal sensing performance approximately.     

认知无线电网络中多目标频谱分配与功率控制

针对Underlay接入方式的认知无线电网络中的功率控制问题进行了研究,提出同时考虑频谱分配和功率控制两个因素。并且为了同时满足用户的多种需求,将网络容量和功耗效率构建成一个多目标优化问题,然后提出了一种基于NSGA-Ⅱ的改进多目标优化算法对该问题进行建模求解,得到了适合用户不同需求的Pareto最优解集。最后将所提方法与SPEA-Ⅱ算法进行了实验对比,仿真结果表明,所提方法能够有效地搜索到优化解,并且能够满足不同情况下的频谱和功率分配要求。