Cooperative Spectrum Sensing Network Research Articles

A novel relay‐aided centralized cooperative spectrum sensing scheme using radio frequency energy harvesting

SummaryIn a cooperative spectrum sensing (CSS) network, the primary signal can be used as a radio frequency (RF) source in order to power the energy‐constrained sensor nodes of the secondary network. This work presents a novel hybrid model combining an optimal relay selection scheme to incorporate RF energy harvesting in a centralized CSS network. The secondary users, which are equipped with RF energy harvesting capabilities, act as relays in order to forward the sensing information to a fusion center. Here, we have derived an enhanced multi‐relay selection strategy to maximize the end‐to‐end signal‐to‐noise ratio of the links. Furthermore, a new voting rule is proposed based on the generalized K‐out‐of‐M rule, such that it minimizes our objective error function. The performance analysis of our proposed model is presented with respect to the flexible relay positions. We have used complementary receiver operating characteristic curves for analyzing the detection performance of the CSS model with our derived voting rule. Simulation results using MATLAB show that the proposed model gives a better detection probability and a smaller error rate than some related existing works.

Fast and Accurate Detection of Malicious Users in Cooperative Spectrum Sensing Network

Cooperative spectrum sensing allows users to detect available spectrum and utilize it. However, it is known that a few users can easily affect the cooperative decision at the fusion center by reporting falsified sensing data. The problem of detecting malicious users in cooperative spectrum sensing has been studied by numerous researchers. The basic approach is to compute the credibility of the reported data of each user and declare those with low credibility (below some threshold) as malicious. The computation of credibility can be based on several things such as pattern of historic behavior, entropy of the reported data, signal-to-noise ratio, etc. The credibility of the reported data of some user node can be expressed as an attack probability of that node. A node with higher attack probability will have lower credibility while a node with lower attack probability a higher credibility. Then, the problem of computing credibility of a node becomes the problem of computing attack probability of a node given a set of reported data. We can enumerate a list of all possible attack probability vectors for a set of nodes and the list of all possible energy level vectors of the channel for the observed time period, and compute which combination of attack probability and channel energy level vector can have the maximum probability to produce the reported channel energy level. However, the search space is quite large and grows exponentially as the number of user nodes and the number of time slots to observe increase. In this paper, we suggest algorithms that reduce the search space considerably and detect malicious users in linear time instead of exponential time. The suggested algorithms have been implemented and show promising results.

Detection Strategy Against Restricted SSDF Attack With Potential Interaction Assistance

This paper investigates the malicious users (MUs) detection problem against restricted spectrum sensing data falsification (RSSDF) attack in cooperative spectrum sensing (CSS) network. We consider a CSS network with non-ideal reporting channels, in which there are two kinds of secondary users (SUs): interactive SUs (ISUs) and non-interactive SUs (NSUs). We simplify the interaction process among ISUs with proper assumptions and formulate the impact of non-ideal reporting channels on falsified data. Based on the traditional probability SSDF attack on M-ary quantized data, we generalize the attack model by considering the restriction on attack magnitude. To detect ISUs, we construct a detection architecture with ISUs partitioned into groups of two and perform distributed detection by proposed interaction-based detection algorithm. For the detection of NSUs and undetected ISUs, we further propose a semi-supervised fuzzy c-means-based (SSFCM-based) detection algorithm with potential interaction assistance. Simulation results demonstrate the validity of the proposed theorems. In addition, we illustrate the detection performance of the proposed strategy in different conditions and show the superiority of the proposed strategy over other detection algorithms.

Distributed average consensus optimization for cooperative spectrum sensing in cognitive radio ad hoc networks

SummaryIn this article, we develop a parameter and optimization analyses aiming at characterizing the performance of cooperative spectrum sensing (CSS) based on the distributed average consensus (DAC), taking into account the network topology effect, represented by adjacency matrices in cognitive radio ad hoc networks. The CSS performance is analyzed by the probability of detection, probability of false alarm, and probability of miss detection, besides the decision threshold and the number of collected samples. In this work, all secondary users are equipped with a simple energy detector. Despite the DAC technique has been successfully deployed in the distributed CSS context, however, a full analytical description taking into account the joint effects of the network topology and all the optimized system parameters remains unknown. Moreover, the CSS network decision threshold was optimized using the error probability minimization criterion. Numerical results deploying extensive Monte Carlo simulations have corroborated the proposed analytical expressions.

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

SummaryThe 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 (Nopt), normalize threshold value (λn,opt), and an arbitrary power of the received signal (popt) 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.

Correction to: Performance Analysis of Cooperative Spectrum Sensing Network Using Optimization Technique in Different Fading Channels

The last author’s affiliation was incorrect in the original publication. The correct affiliation is ECE Department, Marri Laxman Reddy Institute of Technology and Management, Dundigal, India.

The effects of channel knowledge on cooperative spectrum sensing in Nakagami-n/q fading channels

Cooperative spectrum sensing (CSS) is an efficient method to detect vacant spectrum of a primary user (PU) by combining sensing information of multiple cognitive radios (CRs) in presence of fading. In this paper, effects of perfect and imperfect channel state information (CSI) on CSS network is evaluated. The proposed network is operated over Nakagami-q (Hoyt) and Nakagami-n (Rician) fading affecting both reporting (R) and sensing (S) channels. The CRs which employ energy detectors (EDs) are selected on the basis of CSI between them and a fusion center (FC). The knowledge on the quality of R-channels is estimated at FC using a channel estimator. The estimated CSI is either perfect when there is no error in the estimator, or imperfect when errors are present. Accordingly, CRs are selected under both perfect CSI and imperfect CSI cases. All CRs use the decision statistics obtained by EDs and make one-bit binary decisions about the availability of a PU. Selected CRs only transmit decision information to the FC. The miss detection probability and error rate of network under two cases of selection are evaluated by operating majority and maximal ratio combining rules at the FC. Performance is analyzed for different channel and network parameters and comparison between fusion rules for different fading channels is also highlighted.

Malicious User Detection Based on Low-Rank Matrix Completion in Wideband Spectrum Sensing

In cognitive radio networks, cooperative spectrum sensing (CSS) has been a promising approach to improve sensing performance by utilizing spatial diversity of participating secondary users (SUs). In current CSS networks, all cooperative SUs are assumed to be honest and genuine. However, the presence of malicious users sending out dishonest data can severely degrade the performance of CSS networks. In this paper, a framework with high detection accuracy and low costs of data acquisition at SUs is developed, with the purpose of mitigating the influences of malicious users. More specifically, a low-rank matrix completion based malicious user detection framework is proposed. In the proposed framework, in order to avoid requiring any prior information about the CSS network, a rank estimation algorithm and an estimation strategy for the number of corrupted channels are proposed. Numerical results show that the proposed malicious user detection framework achieves high detection accuracy with lower data acquisition costs in comparison with the conventional approach. After being validated by simulations, the proposed malicious user detection framework is tested on the real-world signals over TV white space spectrum.

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.

Performance Analysis of Cooperative Spectrum Sensing Network Using Optimization Technique in Different Fading Channels

Spectrum sensing is an important task to find out the spectrum holes in a given radio spectrum. Spectrum sensing performance is improved with the aid of multiple cognitive radios (CRs) in the network and each CR having multiple antennas in different fading channels (Rayleigh, Hoyt and Weibull fading channel). In this paper, we have considered that each CR having multiple antennas and improved energy detector (IED) scheme is used for detection of primary user. Imperfect channel is considered between CRs and fusion center (i.e. in reporting channel) with an error probability rate (r). We have derived the novel expression for missed detection probability (P m ), closed form of expression to find out optimal value of number of CR users (N opt ), closed form of expression and procedure to find an optimal value of normalized threshold value (λ n,opt ), expression for optimal value of arbitrary power of received signal (P opt ) and calculation of minimum value of total error in different fading channels are provided. Performance is evaluated to find out (N opt ), (λ n,opt ), (P opt ) and to calculate minimum error value for various network parameters like SNR, r, λ n and multiple number of antennas (M). It is observed that detection performance is improved by using multiple antennas at each CR. Comparison between conventional energy detector and IED, comparison among Rayleigh, Hoyt and Weibull fading channels also provided for different cases of network parameters.

Optimization Analysis of Improved Energy Detection based Cooperative Spectrum Sensing Network in Nakagami-m and Weibull Fading Channels

Optimization Analysis of Improved Energy Detection based Cooperative Spectrum Sensing Network in Nakagami-m and Weibull Fading Channels

Maximization of Network Utility Function in Co- Operative Spectrum Sensing using Energy Detection Scheme

Spectrum Sensing (SS) is the best technique to identify the vacant bands present in the radio spectrum. Co-operative Spectrum Sensing (CSS) concept is introduced to overcome the drawbacks present in the SS network and CSS improves the detection probability though the fading and shadowing effects are present in the environment. It is necessary to maximize the network utility function and minimize the total error probability rate for the better usage of the CSS network. In this paper, performance is evaluated by maximizing network utility function and minimizing the total error probability rate with the Conventional Energy Detection (CED) scheme in AWGN channel. An imperfect Binary Symmetric Channel (BSC) having an error probability rate (r) is considered in the CSS network reporting channel. Finally, comparison between perfect and imperfect reporting channel, effect of error rate on utility function and total error are described.