Adaptive Two-Stage Sensing Based on Energy Detection and Cyclostationary Feature Detection for Cognitive Radio Systems

2013 ◽  
Vol 411-414 ◽  
pp. 1521-1528 ◽  
Author(s):  
Yu Yang ◽  
Yan Li Ji ◽  
Han Hui Li ◽  
Du Lei ◽  
Meng Rui
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Two Stage ◽  
Probability Of False Alarm ◽  
Detection Model ◽  
Radio Systems ◽  
Cyclostationary Feature Detection

In this paper, we investigate the features of energy detection and cyclostationary feature detection for spectrum sensing. In order to combine their advantages, we propose an adaptive two-stage sensing scheme which performs spectrum sensing using an energy detector first in cognitive radio networks. Then in the second stage, this scheme decides whether or not to implement cyclostationary feature detection based on the sensing results of the first stage. On the premise of meeting a given constraint on the probability of false alarm, the goal of our proposed scheme is to optimize the probability of detection and sensing speed at the same time. In order to obtain the optimal detection thresholds, we can formulate the detection model as a nonlinear optimization problem. Furthermore, the simulation results show that the proposed scheme improves the performance of spectrum sensing compared with the ones where only energy detection or cyclostationary feature detection is performed.

Improved Two-Stage Spectrum Sensing for Cognitive Radio Networks

2019 ◽  
Vol 23 (6) ◽  
pp. 1052-1062
Author(s):  
Fidel Wasonga ◽  
Thomas O. Olwal ◽  
Adnan Abu-Mahfouz ◽  
◽  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Detection Accuracy ◽  
Two Stage ◽  
Probability Of Error ◽  
Average Spectrum ◽  
Sensing Time

Cognitive radio employs an opportunistic spectrum access approach to ensure efficient utilization of the available spectrum by secondary users (SUs). To allow SUs to access the spectrum opportunistically, the spectrum sensing process must be fast and accurate to avoid possible interference with the primary users. Previously, two-stage spectrum sensing methods were proposed that consider the sensing time and sensing accuracy parameters independently at the cost of a non-optimal spectrum sensing performance. To resolve this non-optimality issue, we consider both parameters in the design of our spectrum sensing scheme. In our scheme, we first derive optimal thresholds using an optimization equation with an objective function of maximizing the probability of detection, subject to the minimal probability of error. We then minimize the average spectrum sensing time using signal-to-noise ratio estimation. Our simulation results show that the proposed improved two-stage spectrum sensing (ITSS) scheme provides a 4%, 7%, and 6% better probability of detection accuracy rate than two-stage combinations of energy detection (ED) and maximum eigenvalue detection, energy detection and cyclostationary feature detection (CFD), and ED and combination of maximum-minimum eigenvalue (CMME) detection, respectively. The ITSS is superior also to single-stage ED by 19% and shows an improved average spectrum sensing time.

An Algorithm Based on Double-Threshold Energy Detection in Cognitive Radio

2014 ◽  
Vol 643 ◽  
pp. 105-110
Author(s):  
Yuan Li ◽  
Jia Yin Chen ◽  
Xiao Feng Liu ◽  
Ming Chuan Yang
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Mathematical Proof ◽  
Threshold Energy ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Double Threshold

Aiming at the situation where the double-threshold detection has been widely used without complete mathematical proof and condition of application, this paper proves its correctness under the circumstance of spectrum sensing, and circulates the condition where this method can work. The proof and simulation show that, comparing with traditional energy detection, this method can increase the probability of detection by 27% to 42% at most when the SNR is between-15dB and-2dB, while the probability of false alarm is increased by less than 2%.

scholarly journals Analysis of Cognitive Radio Spectrum Sensing Techniques over Nakagami-m Fading Channel

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Fading Channel ◽  
Feature Detection ◽  
Energy Detection ◽  
Radio Spectrum ◽  
Awgn Channel ◽  
Novel Approach ◽  
Spectrum Scarcity ◽  
Cyclostationary Feature Detection

As the demand of wireless communication increases exponentially, with the same ratio scarcity of spectrum also originates. To overcome this spectrum scarcity a novel approach, Cognitive Radio (CR) shows development of an opportunistic and promising technology. This paper explores implementation and analysis of the CR spectrum sensing techniques such as Matched filtering, Energy detection and Cyclostationary feature detection on MATLAB platform by simulation. We analyze performance of these techniques over, Nakagami-m fading channel with AWGN channel for both the BPSK and QPSK modulation.

Review of Spectrum Sensing Techniques in Cognitive Radio Networks

2019 ◽  
pp. 85-107
Author(s):  
Ala Eldin Omer
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Matched Filter ◽  
Internal State ◽  
Energy Detection ◽  
Detection Sensitivity ◽  
Detection Techniques ◽  
Radio Technology ◽  
Cyclostationary Feature Detection

Most frequency spectrum bands are licensed to certain services to avoid the interference between various networks, but the spectrum occupancy measurements show that few portions of this spectrum are fully efficiently used. Cognitive radio is a future radio technology that is aware of its environment, internal state, and can change its operating behavior (transmitter parameters) accordingly. Through this technology the unlicensed users can use the underutilized spectrum without causing any harmful interference to the licensed users. Its key domains are sensing, cognition, and adaptation. The spectrum sensing problem is one of the most challenging issues in cognitive radio systems to detect the available frequency bands. This chapter introduces the concepts of various transmitter detection techniques, namely energy detection, matched filter detection, and cyclostationary feature detection. The chapter also discusses other sensing techniques that are introduced to enhance the detection performance of the conventional energy detector. Additionally, the introduced sensing techniques are implemented using extensive MATLAB simulations and their performances are evaluated and compared in terms of sensing time, detection sensitivity, and ease of implementation. The implementation is based on BPSK and QPSK modulation schemes under various SNR values for AWGN noisy channel with Rayleigh fading.

scholarly journals Kinerja Spectrum Sensing Dengan Metode Cyclostationary Feature Detector Pada Radio Kognitif

2013 ◽  
Vol 1 (1) ◽  
pp. 26
Author(s):  
HENDRY CAHYO ◽  
DWI ARYANTA ◽  
NASRULLAH ARMI
Keyword(s):  
False Alarm ◽  
Frequency Spectrum ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Feature Detection ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Probability Of False Alarm ◽  
Detection Energy ◽  
Cyclostationary Feature Detection

ABSTRAKPerkembangan dalam dunia telekomunikasi nirkabel terutama spektrum frekuensi adalah hal yang perlu mendapatkan perhatian penting. Spektrum frekuensi merupakan sumber daya yang terbatas, penggunaannya harus dilakukan secara efisien dan se-maksimal mungkin. Penelitian ini membahas teknik spectrum sensing pada radio kognitif untuk menghadapi masalah keterbatasan penggunaan spektrum frekuensi. Radio kognitif merupakan sistem radio cerdas yang bisa mengatur parameternya seperti frekuensi kerja, daya pancar, dan skema modulasi secara optimal dalam melakukan proses komunikasi. Spectrum sensing merupakan teknik untuk memaksimalkan penggunaan spektrum frekuensi. Penelitian ini membandingkan kinerja metode cyclostationary feature detection dan metode energy detection pada teknik spectrum sensing menggunakan software matlab sehingga dapat diketahui bahwa kinerja cyclostationary feature detection untuk nilai Pd = 0,85 lebih handal sebesar 0,2 untuk fungsi probability of false dan lebih handal sebesar 2 dB untuk fungsi signal to noise ratio daripada energy detection.Kata kunci: radio kognitif, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm. ABSTRACTDevelopments in the world of wireless telecommunications specially frequency spectrum is an important thing to get attention. Frequency spectrum is afinite resource, its use must be efficiently and as maximum as possible. This study discuss the technique of spectrum sensing in cognitive radio to faces the problem using restrictiveness of frequency spectrum. Cognitive radio is a smart radio system that can adjust its parameters like work frequency, emission power, and modulation scheme are optimal in the communication process. Spectrum sensing is a technique to maximize the use of the frequency spectrum. This study compared performance of cyclostationary feature detection methodh with energy detection methodh in spectrum sensing technique using matlab software so ascertainable that cyclostationary feature detection performance for Pd value 0,85 better about 0,2 for probability of false alarm function and better about 2 dB for signal to noise ratio function than energy detection.Keywords:  cognitif radio, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm.

scholarly journals Optimization of spectrum sensing in cognitive radio using genetic algorithm

2012 ◽  
Vol 25 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Rashmi Deka ◽  
Soma Chakraborty ◽  
Sekhar Roy
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Rapid Development ◽  
Probability Of Detection ◽  
Radio System ◽  
Probability Of False Alarm ◽  
Space Allocation ◽  
Wireless Environment ◽  
Better Than

Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the help of genetic algorithm the optimized result is better than without using genetic algorithm. It is necessary that the secondary user should vacate the spectrum in use when licensed users are demanding and detecting the primary users accurately by the cognitive radio. Here, bit error rate (BER) is minimized for better spectrum sensing purpose using GA.

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