• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.10A
• /
• pp.984-991
• /
• 2007

Cognitive Radio is an advanced enabling techlology for efficient utilization of under-utilized spectrum since it is able to sense the temporally available spectrum and adapt its parameters to fully utilize the frequency band. Recent investigation suggests that spectrum sensing is compromised when a cognitive radio user suffers from the environment with fading or shadowing. In order to combat the effect, collaborative sensing is considered to be a promising way, which combines the sensing result of each user to achieve good performance. However, the conventional collaborative sensing is not efficient when users suffer different fading environments. In this paper, we propose a weighted-collaborative scheme that considers using the weights of each collaborative CR user, which can achieve better sensing performance under both fast and slow fading environments. The analysis of the simulation resultsproves that the weighted-collaborative scheme improves sensing performance obviously and outperforms the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.8C
• /
• pp.713-719
• /
• 2010

Collaborative spectrum sensing has been found to be an effective means for detecting the activity of primary users in a fading environment. Most previous works on collaborative spectrum sensing are based on the assumption that the local spectrum sensing decisions of secondary users are statistically independent. However, it may not hold in some practical situations. In this paper, we consider a cognitive radio network where the local spectrum sensing decisions of secondary users are statistically correlated with the same level of correlation if they are next to each other in location and statistically independent, otherwise. Then, for the system, we analyzed the performance of the collaborative spectrum sensing with the AND and the OR fusion rules and found that the scheme with the AND fusion rule performs better than the one with OR fusion rule when the degree of correlation is significant.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.7C
• /
• pp.642-650
• /
• 2010

Collaborative spectrum sensing allows secondary users scattered in location to work together to detect the activity of primary users and has been shown to significantly reduce the performance degradation due to fading phenomenon. Most previous works on collaborative spectrum sensing are based on the assumption that local spectrum sensing decisions of secondary users are statistically independent. However, it may not hold in some practical situations with shadowing effect. In this paper, we consider the case that the secondary users are evenly spaced in the form of a linear array and only adjacent secondary users are statistically correlated, and analyze the effect of the statistical correlation on the performance of collaborative spectrum sensing and the throughput of a cognitive radio network. Here we assumed the AND and OR fusion rules for combining the local decisions of secondary users. The analysis showed that the AND fusion rule achieves higher throughput than the OR fusion rule.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.3
• /
• pp.564-571
• /
• 2009

In this paper, we propose out-of -band collaborative spectrum sensing scheme in the cognitive radio (CR) base station operated by the multiple frequency channels. Also this paper presents the signal detection results for ATSC digital TV signal as an incumbent signal and derives signal detection probability and false alarm probability for the out-of-band collaborative spectrum sensing scheme in frequency selective Rayleigh fading channel. Numerical results demonstrate that the sensing performance is improved by the out-of-band collaborative spectrum sensing in the case that the incumbent signal powers measured by the CR terminals of the multiple frequency channels are almost similar.

• Journal of Internet Computing and Services
• /
• v.12 no.4
• /
• pp.35-43
• /
• 2011

Cognitive Radio (CR) ad hoc network is highly considered as one of promising future ad hoc networks, which enables opportunistic access to under-utilized licensed spectrum. Similarly to other CR networks, the spectrum sensing is a prerequisite in CR ad hoc network. Collaborative spectrum sensing can help increasing sensing performance. For such an infrastructureless network, however the coordination for the sensing collaboration is really complicated due to the lack of a central controller. In this paper, we propose a novel collaborative spectrum sensing scheme in which the final decision is made by the node with the highest data reliability based on a sequential Dempster Shafer theory. The collaboration of sensing data is also executed by the proposed contention-aware reporting mechanism which utilizes the sensing data reliability order for broadcasting spectrum sensing result. The proposed method reduces the collecting time and the overhead of the control channel due to the efficiency of the ordered sequential combination while keeping the same sensing performance in comparison with the conventional cooperative centralized spectrum sensing scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.6
• /
• pp.101-109
• /
• 2008

In this paper, we introduce clustering scheme to calculate probability of detection which is practically required for conventional weighted-collaborative sensing technique. We also propose an improved weighted-collaborative spectrum sensing scheme using new weight generation algorithm to achieve better performance in Cognitive Radio systems. We calculate Pd in each cluster which is a CR users group with similar channel situation. New weight factor is generated using square sum of all cluster's Pds. Simulations under slow fading show that we can get better total detection probability and lower false alarm rate when PU (Primary User) suddenly terminates their transmission.

• Journal of Satellite, Information and Communications
• /
• v.6 no.2
• /
• pp.72-77
• /
• 2011

Spectrum sensing is a critical functionality of CR network; it allow secondary user to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to primary use. Recently, wideband service has been increase for processing abundance of data traffic. So CR network needs a realizable implementation design of spectrum sensing for wideband. To get high resolution performance of wideband sensing must precede algorithm processing for reliability signal detection. By the way, the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome this problem, we propose system model of wideband sensing scheme on energy detected collaborative technique. we divide wideband into narrowbands and use narrowbands to detect signal excepting some narrowbands including bad channel through the CSI. And we simulate and analyze in terms of detection probability with various SNR.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.7
• /
• pp.1951-1975
• /
• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.37-43
• /
• 2012

In this paper, we analysis wideband spectrum sensing with distance based weight combining for Cognitive Radio (CR) systems. CR systems is implemented the spectrum of the Primary User(PU) by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of PU is BPSK signal and the wireless channel between a PU and CR systems is modeled as Gaussian channel. From the simulation results, the wideband sensing with distance based and Distance based weight Combing (DWC) methods shows higher spectrum sensing performance than single CR user spectrum sensing.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8A
• /
• pp.633-639
• /
• 2009

For operation of IEEE 802.22 WRAN system, spectrum sensing is a essential function. However, due to strict sensing requirement of WRAN system, spectrum sensing process of CR nodes require long quiet period. In addition, CR nodes sometimes fail to detect licensed users due to shadowing effect of wireless communication environment. To overcome this problem, CR nodes collaborate with each other for increasing the sensing reliability or mitigating the sensitivity requirement. A general approach for decision fusion, the "k out of N" rule is often taken as the decision fusion rule for its simplicity. However, since k out of N rules can not achieve better performance than the highest SNR node when SNR is largely different among CR nodes, the local SNR of each node should be considered to achieve better performance. In this paper, we propose two novel data fusion methods by utilizing confidence vector which represents the confidence level of individual sensing result. The simulation results show that the proposed schemes improve the signal detection performance than the conventional data fusion algorithms.