A FUSION BASED COOPERATIVE SPECTRUM SENSING DETECTION TECHNIQUES (original) (raw)

ABSTRACT: Recent advances in communication technologies and the proliferation of wireless computing and communication devices make the radio spectrum overcrowded. However, experiments from the Federal Communication Commission (FCC) reveals that the spectrum utilization varies from 15% − 85%. Consequently, Cognitive Radio Networks (CRNs) are proposed to utilize the radio spectrum opportunistically. Therefore, FCC is currently working on the concept of unlicensed users “borrowing” spectrum from incumbent license holders temporarily to improve the spectrum utilization. This concept is called dynamic spectrum access (DSA). Cognitive radios offer versatile, powerful, and portable wireless transceivers enabling DSA. For complex computer networks with many tunable parameters and network performance objectives, the task of selecting the ideal network operating state is difficult. To improve the performance of these kinds of networks, this research proposes the idea of the cognitive network. A cognitive network is a network composed of elements that, through learning and reasoning,dynamically adapt to varying network conditions in order to optimize end-to-end performance. Therefore, a new channel selection strategy is required which cause less harmful interference to PR nodes and try to maximize the chances that the message is delivered to the neighboring cognitive radio receivers, thus increasing the data dissemination reachability. Keywords: Cognitive radio networks, channel selection, dynamic spectrum access networks, spectrum sensing, cooperation, Receiver Detection, OR and AND rule

A Monthly Double-Blind Peer Reviewed Refereed Open Access International e-Journal -Included in the International Serial Directories A FUSION BASED COOPERATIVE SPECTRUM SENSING DETECTION TECHNIQUES

Recent advances in communication technologies and the proliferation of wireless computing and communication devices make the radio spectrum overcrowded. However, experiments from the Federal Communication Commission (FCC) reveals that the spectrum utilization varies from 15% − 85%. Consequently, Cognitive Radio Networks (CRNs) are proposed to utilize the radio spectrum opportunistically. Therefore, FCC is currently working on the concept of unlicensed users " borrowing " spectrum from incumbent license holders temporarily to improve the spectrum utilization. This concept is called dynamic spectrum access (DSA). Cognitive radios offer versatile, powerful, and portable wireless transceivers enabling DSA. For complex computer networks with many tunable parameters and network performance objectives, the task of selecting the ideal network operating state is difficult. To improve the performance of these kinds of networks, this research proposes the idea of the cognitive network. A cognitive network is a network composed of elements that, through learning and reasoning,

Collaborative Spectrum Sensing for Cognitive Radio

2009

Today's wireless communication systems follow fixed spectrum assignment policies which leads to overall inefficient spectrum use. Further, spectrum scarcity is an issue for operators with emerging mobile services and large number of users with even higher capacity requirements. This inefficiency and scarcity in spectrum usage necessitates a new paradigm for communications such as utilising available spectrum opportunistically. Cognitive radio (CR) is an enabling technology having potential to increase spectrum utilisation and provide desired interference protection to licenced users. This can be done by detection of spectrum opportunities by secondary users. Due to channel fading and shadowing a single user can not make a reliable decision and collaboration of and among users is required. In this paper, it has been demonstrated that for improved detection performance decision fusion algorithm for collaborative spectrum sensing must have information about channel and the mean SNR of all secondary users. Using Monte Carlo simulations it is concluded that for optimum performance it is not necessary that all users collaborate with each other.

A Novel Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

—The rapid growth in wireless communication technology has led to a scarcity of spectrum. But, studies are saying that licensed spectrum is underutilized. Cognitive Radio Networks (CRNs) seem to be a promising solution to this problem by allowing unlicensed users to access the unused spectrum opportunistically. In this paper we proposed a novel spectrum sensing algorithm to improve the probabilities of detection and false alarm in a CRN, using the traditional techniques of energy and first order correlation detection. Results show a significant improvement in performance in cooperative spectrum sensing. Keywords—cognitive radio networks, energy detection, correlation detection, cooperative spectrum sensing.

Enhancement of Spectrum Sensing Performance via Cooperative Cognitive Radio ‎Networks at Low SNR

Iraqi Journal of Science

The inefficient use of spectrum is the key subject to overcome the upcoming spectrum crunch issue. This paper presents a study of performance of cooperative cognitive network via hard combining of decision fusion schemes. Simulation results presented different cooperative hard decision fusion schemes for cognitive network. The hard-decision fusion schemes provided different discriminations for detection levels. They also produced small values of Miss-Detection Probability at different values of Probability of False Alarm and adaptive threshold levels. The sensing performance was investigated under the influence of channel condition for proper operating conditions. An increase in the detection performance was achieved for cognitive users (secondary users) of the authorized unused dynamic spectrum holes (primary users) while operating in a very low signal-to-noise ratio with the proper condition of minimum total error rate.

Cooperative Spectrum Sensing and Decision Making Rules for Cognitive Radio

2014

Cognitive radios are proposed to be the technology that will alleviate the problem of spectrum scarcity by using the underutilized radio frequency on non-interfering basis. So the cognitive radio user must be able detect the available spectrum opportunity reliably and efficiently. Spectrum sensing is an important functionality for cognitive users to look for spectrum holes before taking transmission in dynamic spectrum access model. In this paper we consider a realistic case where the SNR of the primary user's signal is unknown to both fusion center and cognitive radio terminals. Adaptive fuzzy system is designed to make the global spectrum sensing decision based on the observed energies from cognitive users. With the capacity of adapting system parameters, the fusion center can make a global sensing decision reliably without any requirement of channel state information, prior knowledge and prior probabilities of the primary user's signal. Simulation results prove that the s...

Spectrum Sensing Techniques Applied In Cognitive Radio Networks – A Comparison

2017

Cognitive Radio (CR), a radio with built-in intelligence, became a necessity to overcome the scarcity of available electromagnetic radio spectrum. It efficiently allocates the licensed bands to the unlicensed users when licensed bands are not in use, taking into concern the interference limit. In this radio network, the first and the most important task is the Spectrum Sensing. This is the technique of sensing or detecting the available licensed bands that can be made use of by the unlicensed users. As spectrum sensing is a major functional block of cognitive networks, it faces certain challenges also. This paper presents the concept of Cognitive radio networks and a literature survey of the two main techniques of spectrum sensing i.e. Cooperative and non – Cooperative spectrum sensing. It also highlights their respective advantages and disadvantages. Based on the study, some generic conclusions have been taken.

Loading...

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.