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.     

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.     

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.     

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.     

The effect of Weibull fading channel on cooperative spectrum sensing network using an improved energy detector

This paper analyses the performance of proposed cooperative spectrum sensing (CSS) network in Weibull fading environment. First, we have derived the novel analytic expressions for probabilities of missed detection and false alarm in Weibull fading channel, assuming an improved energy detector (IED), selection combining diversity scheme and multiple antennas at each cognitive radio (CRs). Next, performance is analyzed using complementary receiver operating characteristics curves, total error rate, average channel throughput, and network utility function curves for the proposed CSS network. The optimal performance of CSS network is achieved by optimizing the CSS network parameters. The closed form of expressions for the optimum value of number of CRs, arbitrary power of received signal, and detection threshold at each CR are derived using OR-Rule and AND-Rule at fusion center (FC). The average channel throughput and network utility function analysis are evaluated using \(k=1+n\) and \(k=N-n\) fusion rules at FC. Finally, the impact of several network parameters such as, multiple antennas at each CR (M), number of CRs (N) in CSS network, Weibull fading parameter (V), arbitrary power of received signal (p), and sensing channel SNR (\({\bar{\gamma }})\) on the performance of proposed CSS network are investigated using the simulation results. The performance comparison between conventional energy detector and an IED has been highlighted with the simulations.     

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.

     

Cooperative Cognitive Radio Networks: New Approach for Detection Accuracy Analysis Under Impaired Channels

The quality of the reporting channel and the relaying mechanism play a significant role in cooperative spectrum sensing (CSS). However, these factors are frequently overlooked when it comes to discussing the performance of CSS in cognitive radio (CR) networks. In this work we investigate the performance of a relay-based CSS approach proposed for CR applications. Specifically, we analyze the detection accuracy of a CR network considering channel impairments, amplify-and-forward relying protocol, and a selection combining scheme. First, a closed form expression for the average false alarm probability is derived. Then, the probability density function (PDF) of the end-to-end signal-to-noise ratio (SNR) is obtained and a closed-form expression for the average detection probability at high SNR applications is derived. The sensing and the reporting channels are assumed to be subjected to independent and identically distributed Rayleigh fading. The PDF approach is used in our analysis. This approach is not easily tractable as it involves higher orders of Bessel functions. However, an approximated polynomial representation of a first-order modified Bessel function of the second kind makes this task possible. The results obtained validate the derived closed form expressions and show the importance of considering reporting channel statistics and relaying mechanism for accurate performance analysis of the CSS in CR networks.     

Cooperative Spectrum Sensing Scheme with Hard Decision Based on Location Information in Cognitive Radio Networks

Without an efficient way to achieve the reliability of the decision, the implementation of weighted data fusion is limited in the hard decision combination for cooperative spectrum sensing. To address this problem, a new cooperative spectrum sensing scheme based on the location information of the primary user (PU) and cognitive radio (CR) is proposed. In the new scheme, depending on the location information, the channel condition between the PU and each CR is obtained at the fusion center (FC), with which the local sensing reliability is first achieved. Then we calculate the transmission reliability between the CR and FC. Based on both the local sensing reliability and the transmission reliability, the combining weighting factor is determined for optimal data fusion. On the basis of this proposed scheme, we study the global sensing false alarm and detection probabilities, derive the expressions to obtain the optimal local sensing threshold, and perform an error analysis that demonstrates the impact of imperfect channel knowledge. Using both analytical and simulation methods, we find that the proposed scheme achieves better performance compared with the conventional logical fusion rules in the hard decision combination for cooperative spectrum sensing.     

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.     

Sensing throughput trade‐off for an energy efficient cognitive radio network under faded sensing and reporting channel

The trade‐off between sensing time and throughput is investigated in the context of an energy‐efficient cognitive radio network considering both the sensing and reporting channels are Rayleigh faded, while the existing literature considered the fading in sensing channel only. In this paper, such a trade‐off is re‐examined under Rayleigh faded sensing as well as reporting channel. Novel analytical expressions for overall detection probability and false alarm probability are developed under such scenario. The performance is investigated in terms of detection probability, false alarm probability, throughput and energy efficiency of the network for different sensing parameters such as sensing time, number of samples, sensing channel signal‐to‐noise ratio and reporting channel signal‐to‐noise ratio. Our analysis shows that the quality of the reporting channel significantly affects the trade‐off performance of the network. Copyright © 2015 John Wiley & Sons, Ltd.     

集中式双非参量累积和的合作频谱感知技术

针对认知无线电网络频谱感知的检测时延降低问题，提出了一种采用双非参量累积和的合作频谱感知方法。在单主用户认知网络中，本地认知用户执行非参量累积和算法，处理能量观测数据，以缩短检测时延，减少对主用户先验信息的需求，同时为了降低带宽开销，只向融合中心传输1比特的预判决结果。融合中心在噪声干扰下接收融合预判决结果，执行非参量累积和算法，累加判决统计量，对主用户信号是否存在进行最终判决。仿真结果表明，在10%的虚警概率下，相比于传统的非参量合作频谱感知算法，双非参量累积和算法具有较低的检测延迟。      

Cyclostationarity-based cooperative spectrum sensing over imperfect reporting channels

Reliable detection of weak primary user signals is a crucial problem for cognitive radio networks. To address the above issue, cooperative spectrum sensing (CSS) methods based on cyclostationary detection (CD) have been introduced in the literature. In this paper, a soft decision-based CSS method based on the second-order CD at secondary users (SUs) is proposed. The proposed scheme aims to maximize the deflection criterion at the fusion center (FC), while the reporting channels are characterized by Rayleigh fading. To this end, a fusion rule which does not require to know the noise variances of sensing channels is developed. Since the fusion rule assumes the perfect knowledge of channel state information (CSI) of reporting links, it has theoretical significance and provides an upper bound for the performance of cyclostationarity-based CSS. We have also proposed a more practical suboptimum fusion rule and studied its detection performance in the presence of uncertainties in noise variance and channel power gain estimations. Furthermore, in order to be able to evaluate the performance of the CSS, an analytic threshold estimation method has been proposed. Extensive simulation results have been illustrated the robustness of the proposed method compared to the existing cyclostationary detectors.     

Adaptive Decode-and-Forward Protocol Based Cooperative Spectrum Sensing in Cognitive Radio with Interference at the Secondary Users

In this paper a novel multiple-user cooperative spectrum sensing scheme (MCSS) based on hybrid relay is proposed to achieve the spatial diversity gain in detection of the primary user (PU) in a cognitive radio (CR) network. A practically important case where co-channel interference signals are present at the network is considered for the analysis. Closed-form expressions of detection probability \((\hbox {P}_{\mathrm{d}})\) and false alarm probability \((\alpha )\) for the proposed adaptive decode-and-forward based multiple-user cooperative spectrum sensing scheme (ADF-MCSS) using energy detector over Rayleigh fading sensing channels is derived in presence of co-channel interference at the secondary user which is far away from the PU. Further we extend the concept of two user amplify-and-forward (AF) and decode-and-forward (DF) cooperative spectrum sensing schemes in multiple-user scenario (i.e. AF-MCSS and DF-MCSS) over Rayleigh fading channels when the secondary user (which is far away from PU) is affected by interference. Closed-form expressions of AF-MCSS and DF-MCSS schemes over a Rayleigh fading channels are also evaluated and compared with that of proposed ADF-MCSS in presence of interference signals at the secondary user. Further the performance analysis of AF-MCSS, DF-MCSS and ADF-MCSS schemes are compared with the existing non-cooperative spectrum sensing schemes in presence of interference at the secondary user. Our analysis is validated by numerical and simulation results for multiple-user CR network. The impact of number of cooperative relays, SNR in sensing channel, energy of interference signal, false alarm on detection probability in proposed ADF, AF and DF schemes is shown.     

Cooperative Spectrum Sensing with Adaptive Double-Threshold Based Energy Detector in Cognitive Radio Networks

Spectrum sensing is one of the key functionalities in the implementation of cognitive radio. It is used to sense the unused spectrum in an opportunistic manner. In this paper, we propose an energy detector with adaptive double-threshold for spectrum sensing, to optimize the detection performance at a fixed probability of false alarm $(\text{ P }_\mathrm{f})$ i.e. 0.1, which also overcomes sensing failure problem. In the present work, the detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of cognitive radio (CR) user. Simulation results show that proposed scheme optimizes better detection performance and outperforms both conventional energy detector and cooperative spectrum sensing (CSS) method by 12.8 and 3.3 % at $-$ 8 dB signal to noise ratio (SNR), respectively. While utilizing CSS with proposed adaptive double-threshold scheme, where each CR user use a double threshold detectors for local detection and send detection decisions to fusion center (FC) to give the final decision based on hard decision rule. It is further found that CSS with adaptive double-threshold improves detection performance around 26.8 and 7.6 % as compare to CSS with single threshold and Hierarchical with quantization method at $-$ 10 dB SNR, respectively, under the case when a small number of sensing nodes are used in spectrum sensing.     

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.     

Efficient error detection in soft data fusion for cooperative spectrum sensing

The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.     

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。     

基于信任度与信噪比的认知无线电协同频谱检测

无线网络中存在信噪比较高的恶意认知用户的情况,为了有效利用可靠的认知无线电(CR)技术用户的本地感知结果,提出了一种基于信任度的信噪比比较协同频谱感知算法,可有效剔除认知网络中存在的信噪比较高的恶意认知用户。仿真实验表明,在存在恶意认知用户的认知无线电网络中,该算法检测性能优于传统的或准则(OR)数据融合的协同频谱感知算法以及基于信噪比比较协同频谱感知算法。     

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.     

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.