scholarly journals Spectrum Sensing for Cognitive Radio Using Genetic Algorithm

2018 ◽  
Vol 14 (09) ◽  
pp. 190 ◽  
Author(s):  
Shewangi Kochhar ◽  
Roopali Garg
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Optimization Technique ◽  
Primary User ◽  
Time Frame ◽  
Probability Of False Alarm ◽  
Sensing Time ◽  
Better Than

<p>Cognitive Radio has been skillful technology to improve the spectrum sensing as it enables Cognitive Radio to find Primary User (PU) and let secondary User (SU) to utilize the spectrum holes. However detection of PU leads to longer sensing time and interference. Spectrum sensing is done in specific “time frame” and it is further divided into Sensing time and transmission time. Higher the sensing time better will be detection and lesser will be the probability of false alarm. So optimization technique is highly required to address the issue of trade-off between sensing time and throughput. This paper proposed an application of Genetic Algorithm technique for spectrum sensing in cognitive radio. Here results shows that ROC curve of GA is better than PSO in terms of normalized throughput and sensing time. The parameters that are evaluated are throughput, probability of false alarm, sensing time, cost and iteration.</p>

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.

scholarly journals Kinerja Spectrum Sensing dengan Metode Matched Filter Detector pada Radio Kognitif

2013 ◽  
Vol 1 (1) ◽  
pp. 60
Author(s):  
BAYU ANGGA ◽  
DWI ARYANTA ◽  
NASRULLAH ARMI
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Matched Filter ◽  
Primary User ◽  
Energy Detector ◽  
New Paradigm ◽  
Major Step ◽  
Probability Of False Alarm ◽  
Radio Frequency Spectrum

ABSTRAKEvolusi sistem nirkabel dan teknologi saat ini telah membuat dampak besar pada masyarakat. Namun, disaat yang sama pengelolaan dan pemanfaatan kelangkaan spektrum tidak efisien. Radio kognitif adalah paradigma baru dalam merancang sistem komunikasi nirkabel yang bertujuan untuk meningkatkan pemanfaatan spektrum frekuensi radio (RF) dan mengurangi seminimal mungkin kelangkaan spektrum. Spectrum sensing adalah langkah utama yang akan memungkinkan jaringan radio kognitif, yaitu untuk menentukan status spektrum dan aktivitas pengguna utama secara berkala, dengan menggunakan metode matched filter detector dan energy detector sebagai pembandingnya. Hasil dari kinerja spectrum sensing berdasarkan simulasi, menunjukan kinerja matched filter detector membutuhkan SNR = 15 dB untuk mencapai probability detection (Pd) sebesar 100%, dengan probability false alarm sebesar 0,01, sedangkan energy detector hanya membutuhkan SNR = 14,2 dB. Secara keseluruhan untuk deteksi sinyal yang optimal kinerja matched filter detector tidak lebih baik dibanding kinerja energy detector.Kata kunci: spectrum sensing, radio kognitif, probability detection, matched filter detector, energy detector.ABSTRACTThe evolution of wireless systems and current technology has made a huge impact on society. However, at the same time the management and utilization of spectrum scarcity is not efficient. Cognitive Radio is a new paradigm in designing wireless communication system that aims to improve the utilization of the radio frequency spectrum (RF) and reduce to a minimum the scarcity of spectrum. Spectrum sensing is a major step that will allow the cognitive radio networks, namely to determine the status of the spectrum and activity of the primary user at regular intervals, using the method of matched filter detector and energy detector as a comparison. The results of the performance spectrum sensing based on simulations, indicates the performance matched filter detector requires SNR = 15 dB to achieve detection probability (Pd) of 100%, with a probability of false alarm of 0.01, whereas energy detector only requires SNR = 14.2 dB. As a whole for optimum signal detection performance of matched filter detector is not better than the performance of energy detector.Keywords: spectrum sensing, cognitive radio, probability detection, matched filter detector, energy detector.

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 DOUBLE THRESHOLD SPECTRUM SENSING WITH OPTIMIZATION OF SAMPLES IN COGNITIVE RADIO NETWORKS

2021 ◽  
Vol 22 (2) ◽  
pp. 161-167
Author(s):  
Chilakala Sudhamani
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Primary User ◽  
Radio Networks ◽  
Probability Of Detection ◽  
Secondary User ◽  
Correct Detection ◽  
Propagation Time

In cognitive radio networks spectrum sensing plays a vital role to identify the presence or absence of the primary user. In conventional spectrum sensing one secondary user will make a final decision regarding the availability of licensed spectrum. But Secondary user fail to make a correct detection about the presence of the primary user if he is in fading environment and it causes interference to the licensed users. Therefore to avoid interference to the licensed users and to make correct detection, number of samples is increased, Which increases the probability of detection. In this paper the optimization of samples is proposed to reduce the system overhead and also to increase the propagation time. Simulation results show the optimized value of samples for a given probability of false alarm and also the variation of probability of detection with optimized samples and false alarm is shown in the results. ABSTRAK: Dalam rangkaian radio kognitif, penginderaan spektrum memainkan peranan penting untuk mengenal pasti kehadiran atau ketiadaan pengguna utama. Dalam penginderaan spektrum konvensional, seorang pengguna sekunder akan membuat keputusan akhir mengenai ketersediaan spektrum berlesen. Tetapi pengguna Sekunder gagal membuat pengesanan yang betul mengenai kehadiran pengguna utama jika dia berada dalam persekitaran yang pudar dan menyebabkan gangguan kepada pengguna yang berlesen. Oleh itu untuk mengelakkan gangguan kepada pengguna berlesen dan membuat pengesanan yang betul, jumlah sampel meningkat, yang meningkatkan kemungkinan pengesanan. Dalam makalah ini pengoptimuman sampel dicadangkan untuk mengurangi overhead sistem dan juga untuk meningkatkan waktu penyebaran. Hasil simulasi menunjukkan nilai sampel yang dioptimumkan untuk kebarangkalian penggera palsu dan juga variasi kebarangkalian pengesanan dengan sampel yang dioptimumkan dan penggera palsu ditunjukkan dalam hasil.

scholarly journals Optimal Joint Allocation of MultiSlot Spectrum Sensing and Transfer Power in MultiChannel Cognitive Radio

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xin Liu ◽  
Min Jia ◽  
Xuemai Gu ◽  
Fanqiang Kong ◽  
Qingfeng Jing
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Optimization Problem ◽  
Primary User ◽  
Optimal Number ◽  
Spectrum Access ◽  
Transfer Scheme ◽  
Simulation Results ◽  
Sensing Time ◽  
Sensing Performance

In multichannel, cognitive radio (CR), the secondary user (SU) is allowed to utilize multiple subaltern frequency bands of the primary user (PU), when these bands, namely, subchannels are not currently being used. To support this spectrum reuse functionality, the SU is required to sense each subchannel, and only the subchannels wherein the PU is inactive are available for the spectrum access of the SU. In this paper, a multislot spectrum sensing and transfer scheme for multichannel CR is proposed, whose sensing stage is divided into several time slots allocated to the subchannels for spectrum sensing. While guaranteeing the spectrum sensing performance on each subchannel and limiting the interference to the PU, we formulate an optimization problem that maximizes the SU’s aggregate throughput by jointly allocating the optimal number of sensing time slots and the optimal transfer power to each subchannel. Theoretical analysis is given to prove the feasibility of the proposed optimization problem and simulation results are presented to show the notable improvement on the SU’s throughput when the sensing time slots and the transfer power are both optimized by the proposed scheme.

scholarly journals DWT Based Energy Detection Spectrum Sensing Method for Cognitive Radio System

2020 ◽  
Vol 3 (3) ◽  
pp. 1-11
Author(s):  
Muntaser S. Falih ◽  
Hikmat N. Abdullah
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Primary User ◽  
Radio System ◽  
Processed Sample ◽  
Simulation Results ◽  
Sensing Time

In this paper a new blind energy detection spectrum-sensing method based on Discreet Wavelet Transform (DWT) is proposed. The method utilizes the DWT sub-band to collects the received energy. The proposed method recognizes the Primary User (PU) signal from noise only signal using the differences in the collected energy in first and last sub-bands of one level DWT. The simulation results show that the proposed method achieves improved detection probability especially at low Signal to Noise Ratio (SNR) compared to Conventional Energy Detector (CED). The results also show that the proposed method has shorter sensing time and less Energy Consumption (EC) compared to CED due to using small number of processed sample. Therefore, this method is suitable for Cognitive Radio (CR) applications where only limited energy like device battery is available.

A hybrid model for energy efficient spectrum sensing in cognitive radio

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahua Bhowmik ◽  
P. Malathi P. Malathi
Keyword(s):  
Cognitive Radio ◽  
Prediction Model ◽  
Spectrum Sensing ◽  
Hybrid Model ◽  
Energy Efficient ◽  
Probability Of Detection ◽  
Content Type ◽  
Hybrid Prediction ◽  
Probability Of False Alarm ◽  
Sensing Time

Purpose Cognitive radio (CR) plays a very important role in enabling spectral efficiency in wireless communication networks, where the secondary user (SU) allows the licensed primary users (PUs). The purpose of this paper is to develop a prediction model for spectrum sensing in CR. Design/methodology/approach This paper proposes a hybrid prediction model, called krill-herd whale optimization-based actor critic neural network and hidden Markov model (KHWO-ACNN-HMM). The spectral bands are determined optimally using the proposed hybrid prediction model for allocating the spectrum bands to the PUs. For better sensing, the eigenvalue based on cooperative sensing used in CR. Finally, a hybrid model is designed by hybridizing KHWO-ACNN and HMM to enhance the accuracy of sensing. The predicted results of KHWO-ACNN and HMM are combined by a fusion model, for which a weighted entropy fusion is employed to determine the free spectrum available in CRs. Findings The performance of the prediction model is evaluated based on metrics, such as probability of detection, probability of false alarm, throughput and sensing time. The proposed spectrum sensing method achieves maximum probability of detection of 0.9696, minimum probability of false alarm rate as 0.78, minimum throughput of 0.0303 and the maximum sensing time of 650.08 s. Research implications The proposed method is useful in various applications, including authentication applications, wireless medical networks and so on. Originality/value A hybrid prediction model is introduced for energy efficient spectrum sensing in CR and the performance of the proposed model is evaluated with the existing models. The proposed hybrid model outperformed the other techniques.

One-Bit Hard Combination Decision Scheme for Cooperative Spectrum Sensing in Cognitive Radio

2015 ◽  
Vol 4 (2) ◽  
pp. 66
Author(s):  
Md. Shamim Hossain ◽  
Md. Ibrahim Abdullah ◽  
Mohammad Alamgir Hossain
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Probability Of False Alarm ◽  
Decision Scheme ◽  
Comparable Performance ◽  
Signal Simulation ◽  
Detection Energy ◽  
Detector Model

<p>In this paper, the performance of 1-bit hard combination decision scheme for cooperative spectrum sensing in Cognitive Radio has been studied to maximize the probability of primary user detection. Energy detector model is used to observe the presence of primary user signal. Simulation result shows that the probability of missed detection is decreasing for both conventional and 1-bit hard combination OR rule with increasing the probability of false alarm correspondingly. It also has demonstrated that 1-bit hard combination decision scheme exhibits comparable performance with the conventional one-bit scheme and thus achieves a good tradeoff between performance and complexity.</p>

scholarly journals Performance of p-Norm Detector in Cognitive Radio Networks with Cooperative Spectrum Sensing in Presence of Malicious Users

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Nandita Lavanis ◽  
Devendra Jalihal
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Random Variable ◽  
Energy Detection ◽  
Primary User ◽  
Test Statistic ◽  
Secondary Users ◽  
Probability Of False Alarm ◽  
Standard Energy

A cognitive radio network (CRN) with a cooperative spectrum sensing scheme is considered. This CRN has a primary user and multiple secondary users, some of which are malicious secondary users (MSUs). Energy detection at each SU is performed using a p-norm detector with p≥2, where p=2 corresponds to the standard energy detector. The MSUs are capable of perpetrating spectrum sensing data falsification (SSDF) attacks. At the fusion center (FC), an algorithm is used to suppress these MSUs which could be either an adaptive weighing algorithm or one of the following: Tietjen-Moore (TM) test or Peirce’s criterion. This is followed by computation of a test statistic (TS) which is a random variable. In this paper, we assume TS to have either a Gamma or a Gaussian distribution and calculate the threshold accordingly. We provide closed-form expressions of probability of false alarm and probability of miss-detection under both assumptions. We show that Gaussian assumption of TS is more suited in presence of an SSDF attack when compared with the Gamma assumption. We also compare the detection performance for various values of p and show that p=3 along with the Gaussian assumption is the best amongst all the cases considered.

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