Adaptive Spectrum Sensing Research Articles

AdS: An adaptive spectrum sensing technique for survivability under jamming attack in Cognitive Radio Networks

IEEE 802.22 Cognitive Radio Network (CRN) allows sharing of geographically unused spectrum allocated to the television broadcast service, on a non-interfering basis. CRNs make use of Dynamic Spectrum Access (DSA) which is a two-stage mechanism comprising fast sensing, which is mandatory and fine sensing which is optional. However, the two-stage spectrum sensing mechanism suits malicious nodes in the CRN which intend to deny the use of vacant spectrum to the CRN by jamming its communication while at the same time, minimizing the amount of power expended on jamming. Such Minimal Denial of Service (MDoS) jamming attack can be launched by the malicious nodes by transmitting a very short jamming signal during the mandatory fast sensing stage which will in turn force the CRN to carry out the otherwise optional, fine sensing. MDoS jamming attack results in wastage of spectrum opportunities for the rest of the CRN to the extent which can jeopardize its survivability. In this paper we present AdS: an Intelligent Adaptive spectrum Sensing technique which, not only minimizes the effects of MDoS jamming attack but can also reduce the effects of noise during the spectrum sensing stages of DSA. The adaptive nature of AdS improves spectrum utilization by CRNs by up to 90% through adaptive tuning of the fine sensing threshold which is based on an estimate of PU’s activity and the severity of MDoS jamming attack.

Simulation of a Smart Sensor Detection Scheme for Wireless Communication Based on Modeling

The principle of sensing and sending information applies to all kinds of communications in different media like air, water, etc. During data transmission through sensors, the most important issue is sensing failure problems. In communication systems, sensing failure problems generally occur and affect sensor system performance. In this study, sensing failure issues are discussed, and a smart sensor is introduced that detects the communication signals. The characteristics of these sensors are identified with signal-to-noise ratio (SNR) readings. The proposed sensor system has high performance and it is better than many systems in the literature. Graphical findings show that the suggested scheme increases device efficiency and has more performance than the energy detector (ED) and ED-ADT-2013 by 33.5%, adaptive spectrum sensing (ASS)-2012 by 41.5%, energy detecting technique for adaptive spectrum sensing (EDT-ASS)-2015 by 28.2%, energy detector, and cyclo-2010 by 57.0%, and energy-SNR adaptive threshold (ADT) detector-2016 by 52.8% at −12 dB SNR, respectively. The proposed sensor detection scheme performs well compared to other existing sensors regarding sensing time. It was found that cooperative spectrum sensing (CSS) with the proposed method outperforms HwQ-2012 and CSS-EDT-ASS-2015 by 22.70% and 16.10% in terms of probability at −12 dB SNR, respectively, and detects the signal at −19.70 dB SNR.

Two Stage Detector Comprising of Weighted-ED and Correlated-GLRT for Cognitive Radio Networks

Cognitive radio network is one of the prime solutions of band width crises problem. To resolve band width crises firstly we have to sense primary user (PU) licensed signal. To sense PU signal there are various sensing techniques which have been proposed by researchers, but each of them are having some limitations. In this paper we present a two stage detector for spectrum sensing (SS) in cognitive radio (CR). It comprises of a weighted-energy detector (W-ED) and a correlated-generalized likelihood ratio test (CGLRT). The first stage detects the energy and then if required, the C-GLRT makes the final decision in second stage. Performance of the proposed two stage detector is compared with the existing energy detector (ED), generalized likelihood ratio test (GLRT), and adaptive spectrum Sensing (ASS) detectors. The numerical results show that proposed sensing technique has better detection performance and require less sensing time.

Spectrum Occupancy Information in Support of Adaptive Spectrum Sensing for Cognitive Radio

Cognitive radio (CR) is an emerging solution to spectrum scarcity currently faced worldwide as CR can change its operating parameters like frequency and bandwidth according to the radio environment and provides efficient spectrum utilisation. Many measurement campaigns conducted around the world showed that the licensed spectrum is not efficiently utilized which led to the need of implementation of dynamic spectrum access (DSA). Statistical information about current frequency usage and its use for developing new algorithms and protocols for CR network is the research area that still requires much more effort. In this paper we discuss the comparison of measurement results obtained from two measurement campaigns conducted in Pune at same location but with different total bandwidths considered. Further to implement CR the best suited channels are obtained from the data collected by using adaptive sensing methods, reference, duty cycle, periodicity and Markov method. The results of spectrum sensing methods show that spectrum occupancy information play a vital role in sensing best suited channels for cognitive radio.

A Robust Detector Using SNR with Adaptive Threshold Scheme in Cognitive Radio Networks

Spectrum sensing is a key functionalities of Cognitive radio networks (CRN). There are several methods to improve sensing techniques. In this paper, we present a robust detector using signal to noise ratio (SNR) with adaptive threshold (ADT) scheme in Cognitive Radio Networks (CRN). This technique has two detectors, energy detector (ED)&EDwithADT detector, out of these two detectors only one will perform sensing operation at a time. Selection of detector depends on condition between estimated SNR value (Se) and threshold (γ). Numerical results show that proposed ESNR_ADT scheme optimizes detection performance and outperforms the cyclostationary based sensing method and adaptive spectrum sensing (SS) by 30.5 % and 30 % at – 10 dB signal to noise ratio (SNR) respectively. It is also shown that the proposed scheme yields lesser sensing time than cyclostationary detection and adaptive SS scheme in the order of 5.2 ms and 1.0 ms at - 20 dB SNR respectively.

Adaptive Spectrum Sensing for Time-Varying Channels in Cognitive Radios

In this article, we develop a novel adaptive spectrum sensing scheme to improve the throughput of cognitive radio (CR) users. The new scheme takes the variation of wireless channels into consideration and requires no priori knowledge of primary user activity statistics. At the beginning of each time frame, this adaptive sensing scheme adjusts the spectrum sensing parameters according to the latest sensing results and channel state information (CSI) of the time-varying channels. Numerical results show that the proposed adaptive spectrum sensing scheme can significantly outperform the traditional spectrum sensing scheme.

Dynamic Spectrum Sensing By Channel Information Table in Cognitive Radios

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In cognitive radio networks, the secondary (unlicensed) users need to find idle channels via spectrum sensing for their transmission. Adaptive spectrum sensing (ASS) is a promising technology in spectrum sensing with an admirable performance. In ASS, multiple secondary users individually sense the idle channels and send their decisions to the network center, and then the center will do a final decision. Spectrum sensing, which aims at detecting spectrum holes, is the precondition for the implementation of cognitive radio (CR). In this work we formed an information table at MSC (main switching center) which consists of channel information and according to the requirement any primary or secondary user can fetch that channel and utilize without any interference. The experiment is conducted on static as well as adaptive environment to check the throughput, route delay of the conventional as well as proposed method.

Adaptive Spectrum Sensing for Throughput Maximization of Cognitive Radio Networks in Fading Channels

In this paper, we investigate an adaptive cognitive radio (CR) scheme where a sensing duration and a detection threshold for spectrum sensing are adaptively determined according to the channel condition in a fading channel. We optimize the sensing duration and detection threshold of a secondary user to maximize the performance of the secondary user guaranteeing a primary user's secure communication. In addition, we analyze the effect of channel fading on the optimization of the sensing duration and detection threshold. Our numerical results show that the performance of the adaptive CR scheme can be drastically improved if a secondary user can take the advantage of channel information between primary and secondary users.