scholarly journals Enhanced Sensing and Sum-Rate Analysis in a Cognitive Radio-Based Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2525 ◽  
Author(s):  
Md. Sipon Miah ◽  
Kazi Mowdud Ahmed ◽  
Md. Khairul Islam ◽  
Md. Ashek Raihan Mahmud ◽  
Md. Mahbubur Rahman ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Uncertain Environment ◽  
Detection Techniques ◽  
Leibler Divergence ◽  
Local Decision ◽  
Sum Rate ◽  
Sensing Performance

Spectrum sensing plays a vital role in cognitive radio networks (CRNs) for identifying the spectrum hole. However, an individual cognitive radio user in a CRN does not obtain sufficient sensing performance and sum rate of the primary and secondary links to support the future Internet of Things (IoT) using conventional detection techniques such as the energy detection (ED) technique in a noise-uncertain environment. In an environment comprising noise uncertainty, the performance of conventional energy detection techniques is significantly degraded owing to the noise fluctuation caused by the noise temperature, interference, and filtering. To mitigate this problem, we present a cooperative spectrum sensing technique that comprises the use of the Kullback–Leibler divergence (KLD) in cognitive radio-based IoT (CR-IoT). In the proposed method, each unlicensed IoT device that is capable of spectrum sensing, which is called a CR-IoT user, makes a local decision using the KLD technique. The spectrum sensing performed with the KLD requires a smaller number of samples than other conventional approaches, e.g., energy detection, for reliable sensing even in a noise uncertain environment. After the local decision is made, each CR-IoT user sends its own local decision result to the corresponding fusion center, which makes a global decision using the soft fusion rule. The results obtained through simulations show that the proposed KLD scheme achieves a better sensing performance, i.e., higher detection and lower false-alarm probabilities, enhances the sum rate, and reduces the total time as compared to the conventional ED scheme under various fading channels.

scholarly journals An Energy Efficient Cooperative Spectrum Sensing for Cognitive Radio-Internet of Things with Interference Constraints

2021 ◽  
Author(s):  
Md Sipon Miah ◽  
Mohammad Amzad Hossain ◽  
Kazi Mowdud Ahmed ◽  
Md. Mahbubur Rahman ◽  
Ali Calhan
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Final Decision ◽  
Weight Factor ◽  
Interference Constraints ◽  
Leibler Divergence ◽  
Local Decision

Abstract Spectrum sensing plays a very important role in Cognitive Radio based Internet of Things (CR-IoT) networks for utilization of the licensed spectrum accurately. However, the performance of the conventional Energy Detector (ED) method is compromised in a noise-uncertain environment owing to interference constraints, i.e. the CR-IoT user interference with the licensed Primary User (PU) on the same licensed band. To overcome this drawback, we proposed an energy efficient Cooperative Spectrum Sensing (CSS) for a CR-IoT network with interference constraints using a novel ED method. In this method, each CR-IoT user is capable of spectrum sensing that makes both the local decision and the weight factor based on the sequential approach; we calculate the weight factor against each CR-IoT user based on the Kullback Leibler Divergence award score. After the local decision and the weight factor are made, each CR-IoT user transmits its measured both the local decisions, and the weight factor to a Fusion Center (FC), which is made a final decision about the PU activities based on the hard fusion rule. The simulation results demonstrates that the proposed ED method obtains an improved detection performance, an enhanced sum rate, a spectral efficiency, an energy efficiency, and a lower global error probability when compared to other conventional ED methods under time varying environments.

A Dynamic Threshold Optimization Algorithm for Spectrum Sensing with Energy Detection in Cognitive Radio

2012 ◽  
Vol 236-237 ◽  
pp. 917-922
Author(s):  
Wei Ran Wang ◽  
Shu Bin Wang ◽  
Xin Yan Zhao
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Optimization Algorithm ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Dynamic Threshold ◽  
Threshold Optimization ◽  
Sensing Performance

In order to improve an efficiency of energy detection for a spectrum sensing in cognitive radio (CR), this paper proposes a dynamic threshold optimization algorithm. The traditional energy detection algorithm uses a fixed threshold, and can't guarantee always the optimal sensing performance in any environment. The improvement for sensing performance need to minimize the undetected probability and the probability of false alarm, and it is dissimilar for different CR users to accept these two errors. We improve the traditional energy detection algorithm, and firstly introduce a preference factor to characterize CR users’ different requirements for these two errors, then, propose a dynamic threshold optimization algorithm by minimizing integrated detection error for different signal-to-noise ratio (SNR). The simulation results show that the proposed algorithm effectively reduces the integrated spectrum sensing error, and increases the probability of detection, especially in low SNR.

scholarly journals IMPROVEMENT OF ENERGY CONSUMPTION IN SPECTRUM SENSING COGNITIVE RADIO NETWORKS USING AN EFFICIENT TWO STAGE SENSING METHOD

2017 ◽  
Vol 57 (4) ◽  
pp. 235 ◽  
Author(s):  
Hikmat Najem Abdullah ◽  
Hadeel Sami Abed
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Minimum Energy ◽  
Energy Detection ◽  
Primary User ◽  
Low Snr ◽  
Local Decision ◽  
Two Stages

Cognitive radio (CR) is a wireless technology developed to improve the usage in the spectrum frequency. Energy consumption is considered as a big problem in this technology, especially during a spectrum sensing. In this paper, we propose an algorithm to improve the energy consumption during the spectrum sensing. The theoretical analysis to calculate the amount of energy consumption, using the proposed method during sensing stage as well as the transmission stage during transmitting a local decision to the fusion center FC, are derived. The proposed algorithm is using energy detection technique to detect the presence or absence of the primary user (PU). The proposed algorithm consists of two stages: the coarse sensing stage and fine sensing stage. In the coarse sensing stage, all the channels in the band are sensed shortly and the channel that have maximum (or minimum) energy is identified to make a dense fine sensing for confirming the presence of the PU signal (or hole). The performance of the proposed algorithm is evaluated in two scenarios: non-cooperative, and cooperative in both the AWGN and Rayleigh fading channels. The simulation results show that the proposed method improves the energy consumption by about 40% at a low SNR values, when compared with the traditional methods based on a single sensing stage and more advanced method based on censoring and sequential censoring algorithms.

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 Spectrum Sensing in Cognitive Radio using Frequency Domain

2019 ◽  
Vol 9 (2) ◽  
pp. 3475-3477
Keyword(s):  
Cognitive Radio ◽  
Frequency Domain ◽  
Spectrum Sensing ◽  
Bandwidth Allocation ◽  
Dynamic Spectrum Access ◽  
Signal To Noise Ratio ◽  
Wide Band ◽  
Energy Detection ◽  
Secondary Users ◽  
Sensing Applications

An efficient bandwidth allocation and dynamic bandwidth access away from its previous limits is referred as cognitive radio (CR).The limited spectrum with inefficient usage requires the advances of dynamic spectrum access approach, where the secondary users are authorized to utilize the unused temporary licensed spectrum. For this reason it is essential to analyze the absence/presence of primary users for spectrum usage. So spectrum sensing is the main requirement and developed to sense the absence/ presence of a licensed user. This paper shows the design model of energy detection based spectrum sensing in frequency domain utilizing Binary Symmetric Channel (BSC) ,Additive white real Gaussian channel (AWGN), Rayleigh fading channel users for 16-Quadrature Amplitude Modulation(QAM) which is utilized for the wide band sensing applications at low Signal to noise Ratio(SNR) level to reduce the false error identification. The spectrum sensing techniques has least computational complexity. Simulink model for the energy detection based spectrum sensing using frequency domain in MATLAB 2014a.

scholarly journals Spectrum sensing based on energy of unknown deterministic signals over fading channels

2014 ◽  
Vol 17 (1) ◽  
pp. 17-31
Author(s):  
Tu Thanh Nguyen ◽  
Khoa Le Dang ◽  
Thu Thi Hong Nguyen ◽  
Phuong Huu Nguyen
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Radio Network ◽  
Essential Components ◽  
Spectrum Hole ◽  
The Impact

In cognitive radio network, how to minimize the impact of secondary user on primary user’s signal plays a very important and complex role. Therefore, spectrum sensing is one of the most essential components of cognitive radio. Therefore, the effect of spectrum sensing algorithms plays a key role to the system’s performance. In this paper, we concentrate on spectrum sensing algorithms in order to find out spectrum hole or while hole for reusing it. Specifically, we will highlight the energy detector algorithm of unknown deterministic signals over fading channels. The numerical results match well with theoretical analysis. The system’s performance of energy detection in AWGN channel is acceptable in case of relatively low signal to noise ratio (SNR). However, the performance of system will be degraded remarkable over fading environments.

scholarly journals Energy Detection-based Spectrum Sensing In Cognitive Radio Networks

2020 ◽  
Vol 3 (1) ◽  
pp. 576-582
Author(s):  
Anıl Merve Ay
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Detection ◽  
Radio Networks

Bugüne kadar kablosuz iletişim teknolojileri sabit spektrum atama prensibi ile hazırlanmış ve kullanılmıştır. Sabit spektrum atama prensibine göre belirli frekans bandı sadece birincil (lisanslı) kullanıcılara ayrılmakta, birincil kullanıcılar tarafından kullanılmıyor olsa dahi ikincil (lisanssız) kullanıcıya tahsis edilememektedir. Bu ilke, frekans spektrumunun verimsiz kullanılmasına neden olmaktadır. Günümüzde kablosuz iletişim teknolojilerinin devamlı gelişmesi ve yaygın kullanımıyla beraber, sınırlı olan frekans spektrumu yetersiz kalmaktadır. Bilişsel Radyo Teknolojisi, dinamik spektrum erişim tekniğini kullanarak frekans spektrumun verimli kullanılmasını amaçlamaktadır. Bu bildiride Bilişsel Radyo Teknolojisi ile boş frekans bandları tespit edilerek birincil kullanıcılar tarafından kullanılmayan bandların ikincil kullanıcılara tahsis edilmesi, Enerji Tespiti ile Spektrum Algılama Yöntemi kullanılarak simülasyon ortamında incelenmiş ve sonuçları verilmiştir.

Sign in / Sign up

Export Citation Format

Share Document