Secrecy outage analysis for underlay cognitive radio networks over correlated channels

This paper investigates the secrecy outage performance of underlay cognitive radio networks, in which a source in a secondary system transmits its confidential information to a legitimate destination in the presence of an eavesdropper. Specifically, the main (the source-to-destination) and eavesdropping (the sourceto- eavesdropper) channels are assumed to be correlated. Moreover, it is also assumed that the main channel and the channel from the source to the primary user’s receiver are correlated. Tight closed-form analytical expression for secrecy outage probability and the closed-form analytical expression for the probability of non-zero secrecy capacity are derived and validated by simulation results when the interference temperature limit is comparably large.     

认知无线电网络中的分布式协作感知算法*

针对认知无线电中频谱感知的问题,讨论了分布式协作感知场景下最优的感知算法。介绍了经典的基于放大前传（AF）、解码前传（DF）和选择中继（SR）的分布式协作方案,包括模型、检测概率和虚警概率。提出了一种新的分布式协作感知算法,该算法将原始统计量和信噪比发送给协作用户,减少信道噪声对最后决策结果的影响。运用似然比准则推导出了最优的加权系数,以及决策函数。对几种协作方案的中断概率进行理论推导,并用数值仿真的方法验证了算法在中断概率上的性能。仿真结果表明,提出的方法在检测概率和中断概率上远优于其他分布式协作方案,但该方法需要协作用户间无损耗的传输,这也给实际的应用提出了很大的挑战。     

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.     

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.     

A stackelberg game for spectrum leasing in cooperative cognitive radio networks

According to the property-rights model of cognitive radio, primary users (PUs) who own the spectrum resource have the right to lease part of spectrum to secondary users (SUs) in exchange for appropriate profit. In this paper, we propose a pricing-based spectrum leasing framework between one PU and multiple SUs. In this scenario, the PU attempts to maximize its utility by setting the price of spectrum. Then, the selected SUs have the right to decide their power levels to help PU’s transmission, aiming to obtain corresponding access time. The spectrum leasing problem can be cast into a stackelberg game, where the PU plays the seller-level game and the selected SUs play the buyer-level game. Through analysis based on the backward induction, we prove that there exists a unique equilibrium in the stackelberg game with certain constraints. Numerical results show that the proposed pricing-based spectrum leasing framework is effective, and the performance of both PU and SUs is improved, compared to the traditional mechanism without cooperation.     

Distributed power control in cooperative cognitive ad hoc networks

In this paper, a relay selection strategy and distributed power control algorithm are proposed for the underlay spectrum sharing mode based cooperative cognitive ad hoc network with energy-limited users. The study aims to minimize the total power consumption of cooperative cognitive ad hoc network while ensuring the quality of service (QoS) requirement of cognitive user and keeping the interference to primary user below interference tolerance. The power control problem is transformed into a convex optimization problem. Based on Lagrange dual decomposition theory, a gradient iterative algorithm is constructed to search for the optimal solution and complete distributed power optimization. Simulation results show that the algorithm converges fast and reduces transmit power of cognitive users effectively while guaranteeing the QoS requirement.     

衰落信道下提高协作频谱感知能力的方法

由于协作频谱感知能够更准确地确定主用户的存在与否,因此,它被认为是认知无线电技术中的一个重要研究分支.在协作频谱感知中,各认知用户需要通过报告信道发送其本地判决结果(0或1)到融合中心(FC).然而,在实际中,报告信道通常受衰落的影响,这将降低频谱感知的检测性能.针对这个问题,首先,文中提出一种基于认知用户选择的协作频谱感知算法.该算法通过减小由衰落信道引入的误码概率来提高协作频谱感知的检测性能.其基本思想为:只有具有较好瞬时信道增益报告信道的认知用户才将其本地二进制判决结果发送到FC,否则,该认知用户不发送其本地检测结果到FC.其次,提出一种基于空时编码的协作频谱感知方法.通过在CR网络中,利用空间分集增益来降低由衰落型报告信道引入的误码概率,从而提高检测性能.最后,对提出的这两种协作频谱感知方法的检测性能进行理论分析研究,并对其进行数值仿真.仿真结果表明:相比于传统的协作频谱感知,本文提出的这两种协作频谱感知算法都能提高对主用户的检测性能.     

Robust cooperative spectrum sensing schemes for fading channels in cognitive radio networks

In cognitive radio systems, cooperative spectrum sensing can detect the presence of the primary user accurately. In practice, however, since the sensing observations are forwarded to a data collector through fading channels, the sensing performance is severely degraded. To deal with this problem, in this paper, we first propose a secondary user selection based cooperative spectrum sensing method to improve sensing performance by decreasing the reporting errors introduced by the fading channels. Mo...     

Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks

In this paper, joint optimization of throughput and error rate via cooperative spectrum sensing in cognitive radio networks is investigated. An optimization problem is formulated, which aims to maximize the average achievable throughput of cooperating cognitive users while keeping the error rate at a lower level. This is a multi-variable nonconvex optimization problem. Instead of solving it directly, we propose an iterative algorithm which jointly optimizes the threshold and sensing time together to decrease the effect of the error and to increase the achievable throughput. We first prove that the local error rate of the cognitive user is a convex function of energy threshold and determine a closed-form for the optimal threshold which minimizes the error rate. Then we show that the AND rule is the optimal fusion rule to maximize the achievable throughput. Furthermore we determine the least number of cooperating cognitive users that can guarantee a minimum target error rate. This initial nonconvex problem is converted into a single variable convex optimization problem which can be successfully solved by common methods e.g. Newton’s method. Simulation results illustrate the fast convergence and effectiveness of the joint iterative algorithm.     

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.     

认知无线电网络中安全的协作频谱检测算法

在认知无线电网络中,当认知用户存在虚假感知信息SSDF时,协作频谱感知的性能会受到巨大影响。为了确保频谱感知的鲁棒性,提出了一种基于信誉度加权序贯频谱检测算法来识别恶意用户并减轻他们造成的影响。该算法通过使用认知用户的近期感知信息计算本地信誉度函数,再综合考虑其信誉值与感知过程中表现的稳定程度以消除恶意用户对主用户的传输效率带来的影响。仿真结果表明,在恶意攻击环境下,新算法优于现有典型协作频谱感知算法。     

Matching game-based hierarchical spectrum sharing in cooperative cognitive radio networks

The Journal of Supercomputing - In a cooperative cognitive radio network (CCRN), primary users (PUs) select secondary users (SUs) as cooperative relays for increasing their transmission rates,...     

潜铺型卫星认知通信中上行链路功率控制

针对卫星通信中存在有效信道远小于注册频率的情况,提出了以潜铺型认知无线电为技术依靠的卫星上行链路功率控制算法。该算法以次要用户所获吞吐量与付出代价之差为效用函数,通过次要用户作为参与者建立的博弈模型进行纳什均衡求解,得到最优功率分配策略。该策略可满足次要用户自身需求,亦不影响主要用户系统正常通信,能有效提高频带使用率。在性能方面,指出了次要用户系统容量和预留信噪比的关系。仿真结果表明,在主要用户系统容许范围内次要用户数量越多则其系统吞吐量和系统收益越大,最后讨论了算法的实现复杂度。     

Optimization of resource allocation for underlay device-to-device communications in cellular networks

Underlay device-to-device (D2D) communication in cellular networks has been considered as a promising technique that can improve the spectral efficiency of cellular systems and meet the growing demand for wireless local services. In underlay D2D, it is of primary importance to manage the mutual interference between cellular links and D2D links through effective resource allocation. While most of previous works on D2D resource allocation are developed based on the knowledge of the channel state information (CSI) on the interference channels as well as the desired channels, it is hard to obtain full CSI in practice. Accordingly, we consider D2D resource allocation schemes based on distance between nodes. In particular, we formulate two optimization problems for D2D resource allocation using the outage probability computed based on the distance information as cost functions. One is a linear sum assignment problem (LSAP) and the other is a linear bottleneck assignment problem (LBAP). By applying the graph theory, we provide efficient algorithms for solving the optimization problems. Numerical results are provided to show the effectiveness of the proposed optimization as compared to previously proposed distance-based resource allocation algorithms.     

Detection time analysis for the multiple-user cooperative spectrum sensing scheme in cognitive radio networks

In this paper, a novel multiple-user cooperative spectrum sensing (MCSS) scheme is proposed to achieve the spatial diversity gains for cognitive radio (CR) networks, where only the best relay, selected among all the candidate relays in accordance with the quality of channel conditions, is utilized to cooperatively detect the primary user. Closed-form expressions of detection time for the traditional non-cooperative and the proposed MCSS schemes are derived over Rayleigh fading channels. In addition, numeric...     

基于能量获取下协作认知网的资源联合分配

频谱共享和能量获取是提高带宽和能量效率的前沿技术,满足了无线传输数据的不断增长的要求。在协作认知无线网络中,由混合接入点提供无线能量的次用户系统帮助主用户传输数据。作为回报,次用户以时分多址的方式获得频谱接入的机会来传输自己的数据。为了最大限度地提高次用户系统的吞吐量,提出了一个次系统吞吐量最优的资源分配方案。在满足主系统基本性能的约束下,根据次用户参与度来选择最佳次用户集合,联合对SUS进行时隙和能量的分配。     

On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks

This work explores the scope of Fuzzy C-Means (FCM) clustering on energy detection based cooperative spectrum sensing (CSS) in single primary user (PU) cognitive radio network (CRN). PU signal energy sensed at secondary users (SUs) is forwarded to the fusion center (FC). Two different combining schemes, namely selection combining (SC) and optimal gain combining are performed at FC to address the sensing reliability problem on two different optimization frameworks. In the first work, optimal cluster center points are searched for using differential evolution (DE) algorithm to maximize the probability of detection under the constraint of meeting the probability of false alarm below a predefined threshold. Simulation results highlight the improved sensing reliability compared to the existing works. In the second one, the problem is extended to the energy efficient design of CRN. The SUs act here as amplify-and-forward (AF) relays and PU energy content is measured at the FC over the combined signal from all the SUs. The objective is to minimize the average energy consumption of all SUs while maintaining the predefined sensing constraints. Optimal FCM clustering using DE determines the optimal SU amplifying gain and the optimal number of PU samples. Simulation results shed a light on the performance gain of the proposed approach compared to the existing energy efficient CSS schemes.     

Resource allocation in cooperative cognitive radio networks towards secure communications for maritime big data systems

In this paper, an innovative framework labeled as cooperative cognitive maritime big data systems (CCMBDSs) on the sea is developed to provide opportunistic channel access and secure communication. A two-phase frame structure is applied to let Secondary users (SUs) entirely utilize the transmission opportunities for a portion of time as the reward by cooperation with Primary users (PUs). Amplify-and-forward (AF) relaying mode is exploited in SU nodes, and Backward induction method based Stackelberg game is employed to achieve optimal determination of SU, power consumption and time portion of cooperation both for non-secure communication scenario and secure communication. Specifically, a jammer-based secure communications scheme is developed to maximize the secure utility of PU, to confront of the situation that the eavesdropper could overheard the signals from SU _i and the jammer. Close-form solutions for the best access time portion as well as the power for SU _i and jammer are derived to realize the Nash Equilibrium. Simulation results validate the effectiveness of our proposed strategy.