Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks

Recently, cognitive radio (CR) access has received much attention to overcome spectrum scarcity problem. Spectrum sensing methods are often used for finding free channels to be used by CR. In this paper, the problem of cooperative spectrum sensing will be investigated in CR networks over realistic channels. This problem is not clarified until now by taking into account the error effect on the decision reporting. The analytical expressions of the hard and softened one bit and two bits hard combination scheme for cooperative spectrum sensing will be derived. These expressions are investigated to compare with simulation results. The analysis and simulation results show that the performance of cooperative spectrum sensing is limited by the probability of reporting errors. Moreover, it is shown that there is a significant performance loss when a final decision regarding to primary user’s (PU) state made at the fusion depends on a set of local spectrum sensing information that are distorted by imperfect reporting channels during transmission. The probability of detection is degraded due to imperfect reporting channel by 16.5% and 12.2% with one bit hard combination and softened two bits hard combination, respectively. To reduce this performance loss, Amplify and Forward (AAF) relying mechanism will be proposed. The probability of detection is improved by 8% and 9.3% with one bit hard combination and softened two bits hard combination, respectively using AAF relaying mechanism.     

A novel cooperative spectrum sensing scheme based on virtual soft information fusion

In cognitive radio (CR), the performance of hard information fusion (HIF) strategy for cooperative sensing will deteriorate when cooperative CR user are not uniformly reliable. To deal with this problem, this paper proposed a novel virtual soft information fusion (VSIF) strategy which uses expectation for primary users (PU) presence probability to replace the local sensing decision of each user in the information fusion. Compared with the HIF-based scheme, VSIF-based sensing scheme keeps the advantages of low data transmission in HIF-based scheme, and modifies the way of information fusion at the fusion center to achieve better performance when the user sensing reliability is non-uniform. Simulation shows VSIF strategy has significant superiority on the missing detection probability over HIF in the scenarios of non-uniform user reliability.     

基于自适应决策融合的合作频谱感知方法

频谱感知是认知无线电(CR)的关键技术之一。在该机制中,对主用户(PU)信号的可靠检测是实现CR的前提。提出一种基于自适应决策融合的合作频谱感知算法用于频谱感知,该算法通过估计PU的先验概率与各个CR用户(SU)的漏检及虚警概率,然后运用Chair-Varshney准则对局部判决进行决策融合以得到全局判决。仿真结果表明,采用该方案的全局虚警和漏检概率明显低于单个SU,可有效提高CR系统频谱感知的可靠性。     

Fault-Tolerant Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks

In order to solve the uncertainty resulting from shadowing effect and resist the attack from malicious cognitive radio (CR) users, we propose a fault-tolerant cooperative spectrum sensing scheme for CR networks, where an energy detection-based local spectrum sensing is performed at each CR user, a coefficient is used to weight each CR user’s sensing result, a linear weighted fusion process is performed at the fusion center (FC) to combine received sensing results. For a fault-tolerant cooperative spectrum sensing scheme, the most important issue is to distinguish whether the CR user is reliable or not. In this paper, a reputation-based cooperative mechanism is presented to alleviate the influence of the unreliable sensing results from CR users suffering shadowing and the false sensing data from malicious CR users on the detection result at the FC. In proposed fault-tolerant cooperative scheme, each cooperative CR user has a reputation degree which is initialized and adjusted by the FC and used to weight the sensing result from the corresponding user in the fusion process at the FC. And then, two reputation degree adjusting methods are presented to manage the reputation degree of each CR user. Simulation results show that the proposed scheme can not only weaken the harmful influence caused by malicious CR users, but also alleviate the corrupted detection problem resulting from destructive channel condition between the primary transmitter and the CR user. Moreover, the detection performance of the fault-tolerant cooperative scheme, which has a feasible computational complexity and needs no instantaneous SNRs, is close to that of the optimal scheme.     

Performance Evaluation of Cooperative Spectrum Sensing Scheme with Censoring of Cognitive Radios in Rayleigh Fading Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users in Rayleigh fading channel is analyzed. More precisely, CR users which employ energy detectors are censored depending on the quality of radio channels between them and a fusion center (FC). Each CR makes a hard decision about primary user (PU) using energy detection and transmits the information to FC using BPSK signaling if that CR user is selected to transmit. A training based channel estimator is used at the FC to estimate the complex Gaussian fading coefficients characterizing the channels between the CR users and the FC. This channel state information on fading coefficients is used for censoring the CR users. Two fusion rules such as majority logic fusion and maximal ratio combining (MRC) fusion rules are applied at the FC for estimating the performance in terms of probability of missed detection (P_m). We develop a simulation test bed for evaluating the performance of CSS scheme. Probability of missed detection has been evaluated for both perfect and imperfect channel estimation for various probabilities of false alarm (P_f), reporting and sensing channel SNR values.     

Multi slot-throughput tradeoff in an improved energy detector based faded cognitive radio network

In this paper, the impact of a multi slot based cooperative spectrum sensing (CSS) on the performance of a cognitive radio (CR) network has been investigated. Each CR user, equipped with an improved energy detector (IED), uses a number of mini slots of the sensing time to perform the spectrum sensing. Each CR uses OR logic to combine the sub local decisions generated in each mini slot to obtain a local decision at CR level. Local decisions are sent to fusion centre (FC) over reporting channel. The FC obtains a final decision about the presence of primary user (PU) by combining the local decisions using a fusion rule: Majority or Maximal Ratio Combining. The performance of the CSS is assessed in terms of detection probability and false alarm probability considering both the sensing and reporting channels are Rayleigh faded. Furthermore, the impact of a number of sensing slots and IED parameter on throughput of CR network is also evaluated under the proposed spectrum sensing scenario. Impacts of several sensing parameters such as sensing channel SNR and reporting channel SNR on the performance of CR network are also evaluated. Performances of two fusion rules under study are compared. Effect of sensing error and synchronisation error is indicated. Further the study is extended for independent but non identically distributed (i.n.i.d.) Rayleigh faded channels as well as for a multiple PU scenario also.     

A Distance Based Reliable Cooperative Spectrum Sensing Algorithm in Cognitive Radio

Spectrum sensing is the most critical task in cognitive radio (CR) which needs to be performed very precisely in order to efficiently utilize the underutilized spectrum and to provide sufficient protection to the primary users (PUs). To improve the sensing performance under fading, shadowing and hidden terminal problems more than one CR users collaboratively perform the spectrum sensing called as cooperative spectrum sensing (CSS). In conventional CSS the decision of each CR is fused at fusion center with equal weights. But due to variable distance of each CR from the PU all decisions are not equally reliable and therefore should be assigned different weights according to their reliability. In this paper we propose a new weighting scheme for CSS under Rayleigh faded channel. In proposed weighting scheme, based on the distance of each CR from the PU reliability of CR nodes is determined and correspondingly appropriate weights are assigned to different users. The CSS algorithm using new weighting scheme gives better performance than conventional CSS algorithm.     

An Innovative Cooperative Spectrum Sensing Algorithm with Non-ideal Feedback Channels and Delay Considerations

Cognitive radio (CR) is used to overcome the spectrum scarcity problem, which results from fixed allocation of wireless bands. CR allows the unlicensed secondary users to exploit the idle spectrum, which is not occupied by any licensed primary user (PU), thus increasing the overall spectrum utilization. In this paper, we first propose a simple cooperative sensing algorithm, which combines the local decision at each CR along with a group decision received from a fusion center to produce a collective decision on the existence of the PU. The performance of the algorithm is investigated over ideal and non-ideal reporting channels, from the fusion center to the CR devices, both analytically and via simulations. Furthermore, the effect of cooperation delay, which causes the decisions received by the CR device from the fusion center to be outdated, is extensively studied, both analytically and via simulations. To overcome the significant performance degradation due to the effect of delay, an extra local sensing cycle is performed at the CR side upon reception of the group decision. Results show that the proposed algorithm outperforms the conventional hard decisions technique and exhibits a comparable performance to the soft decisions approach at a considerably lower complexity. Moreover, the algorithm is shown to enjoy more robustness against reporting channel errors than the conventional hard decisions-based algorithm. Finally, the extra sensing cycle is shown to dramatically improve the performance for different delay scenarios.     

Scheme of Cooperative Spectrum Sensing Based on Adaptive Decision Fusion Algorithm

Spectrum sensing is one of the core technologies for cognitive radios(CR),where reliable detection of the signals of primary users(PUs) is precondition for implementing the CR systems.A cooperative spectrum sensing scheme based on an adaptive decision fusion algorithm for spectrum sensing in CR is proposed in this paper.This scheme can estimate the PU prior probability and the miss detection and false alarm probabilities of various secondary users(SU),and make the local decision with the Chair-Varshney rule so that the decisions fusion can be done for the global decision.Simulation results show that the false alarm and miss detection probabilities resulted from the proposed algorithm are significantly lower than those of the single SU,and the performance of the scheme outperforms that of the cooperative detection by using the conventional decision fusion algorithms.     

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

The proposed cooperative spectrum sensing (CSS) network is equipped with multiple antennas and an improved energy detector (IED) scheme at each cognitive radio (CR). Each CR in the network receives the information about the primary user (PU) in the form of binary decisions at multiple antennas. Diversity technique called selection combining (SC) scheme is used at multiple antennas to select the maximum value of sensing information present at multiple antennas. Finally, sensing information will be passed to the fusion center (FC) through reporting channel, and the final decision about PU is made at FC using fusion rules. Initially, we have derived the novel missed detection probability expressions for AWGN channel, Rayleigh, and Rician fading environments. Later, the closed form of optimized expressions for proposed CSS network parameters are derived to achieve an optimal performance. The closed form of optimized expressions such as number of CR users (N_opt ), normalize threshold value (λ_n,opt ), and an arbitrary power of the received signal (p_opt ) are derived under various fading environments. The performance is evaluated using complementary receiver operating characteristics (CROC) and total error rate curves. The MATLAB‐based simulations are evaluated with the strong support of theoretical expressions. Finally, various simulation parameters such as sensing channel SNR, the error rate in reporting channel, threshold value, and number of antennas at each CR are considered in the simulation to show the effect on the performance of proposed CSS network.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

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.     

认知无线电网络中基于最大似然准则的协同频谱检测算法研究

提出一种集中式频谱协同检测算法。各认知节点采用能量检测算法,然后使用最大似然准则进行本地判决,且把似然比作为本地判决可靠性的度量;中心节点基于可信度对接收到的认知节点本地检测数据进行数据融合。仿真结果显示,文中提出的认知节点协同频谱检测方案能够减少误检概率。特别是当信道处于深衰落时,少量节点参与协同就能获得较好的检测性能。     

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.     

A reliable cooperative spectrum detection scheme in cognitive radio networks

Reliable spectrum detection of the primary user (PU) performs an important role in the cognitive radio network since it’s the foundation of other operations. Spectrum sensing and cognitive signal recognition are two key tasks in the development of cognitive radio (CR) technology in both commercial and military applications. However, when the CR terminals receiving signals have little knowledge about the channel or signal types, these two tasks will become much more difficult. In this paper, we propose a reliable cooperative spectrum detection scheme, which combines the cooperative spectrum sensing with distributed cognitive signal recognition. A novel improved cooperative sensing algorithm is achieved by using a credibility weight factor and the “tug-of-war” rule, which is based on the double threshold detection and Dempster–Shafer theory, to determine whether the PU signals exist. In this scheme, cognitive signal recognition can be used to identify the signal type when the PU signal is present. During the cognitive signal recognition processing, the CR terminals make local classification of the received signals by using Daubechies5 wavelet transform and Fractional Fourier Transform, and send their recognition results to the globe decision making center. A distributed processing uses these cognitive terminals’ local results to make final decisions under the Maximum Likelihood estimation algorithm. Simulation results show that the proposed method can achieve good sensing probability and recognition accuracy under the Additive White Gaussian Noise channel.     

Cooperative Spectrum Sensing with Censoring of Improved Energy Detector Based Cognitive Radios in Rayleigh Faded Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users under several schemes of fusions at fusion center (FC) has been assessed in the presence of Rayleigh fading. Improved energy detector (IED) with multiple antennas has been used at each CR user. The CR users utilize selection combining (SC) of the decision statistics obtained by IEDs with multiple antennas for making hard decisions about PU and transmit the decisions to the FC using BPSK if the CR user is selected to transmit. Censoring of CR users has been considered based on quality of the reporting channels between CRs and a fusion center (FC). A training based channel estimator is used at FC to estimate the fading coefficients characterizing the channels between the CR users and The FC. Several types of fusion rules such as OR-logic, AND-logic, majority-logic and maximal ratio combining (MRC) fusion rules are considered at the FC for estimating the performance in terms of missed detection (Q _m ), total error (Q _m  + Q _f ) and proposed weighted total error probabilities. Performance of CSS in terms of missed detection is evaluated for various values of IED parameter (p) and number of antennas (M) at each CR. The performance in terms of total error probability has also been estimated for several values of normalized detection thresholds, sensing and reporting channel SNRs under both perfect and imperfect channel estimation. Performance comparison amongst the fusion rules have also been presented under both perfect and imperfect channel estimation under different channel and network conditions.     

授权用户信号随机到达时基于双门限的多用户合作频谱感知方法

针对认知无线电系统中可能出现的授权用户信号随机到达时的频谱感知问题,提出了一种基于双门限的多用户合作频谱感知方法.首先在本地判决时采用高低双门限的方式,如果判决量大于高门限就判1,小于低门限判0,在两个门限之间就把判决量直接发送给融合中心,融合中心将直接收到的判决量进行软判决合并,软判决的结果再与其他硬判决的结果进行"OR原则"的硬判决合并,从而得到最终的判决结果.仿真表明所提方法的性能比传统"OR原则"硬判决合并方案要好,仅仅略逊于传统等增益软判决合并方案,但是能大量节省认知网络中的传输比特数.     

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.     

Efficient Spectrum Sensing with Minimum Transmission Delay in Cognitive Radio Networks

In cognitive radio (CR) networks, the secondary users (SUs) need to find idle channels via spectrum sensing for their transmission. In this paper, we study the problem of designing the sensing time to minimize the SU transmission delay under the condition of sufficient protection to primary users (PUs). Energy detection sensing scheme is used to prove that the formulated problem indeed has one optimal sensing time which yields the minimum SU transmission delay. Then, we propose a novel cooperative spectrum sensing (CSS) framework, in which one SU’s reporting time can be used for other SUs’ sensing. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, it is proved that there exists one optimal sensing time that minimizes the SU transmission delay. Under hard information fusion, for time varying channels, the novel multi-slot CSS is derived. The performance of SU transmission delay is studied in both perfect and imperfect reporting channels. Some simple algorithms are derived to calculate the optimal sensing settings that minimize the SU transmission delay. Computer simulations show that fundamental improvement of delay performance can be obtained by the optimal sensing settings. In addition, the novel multi-slot CSS scheme shows a much lower transmission delay than CSS based on general frame structure.     

Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.