Optimal Spectrum Sensing in MIMO-Based Cognitive Radio Wireless Sensor Network (CR-WSN) Using GLRT With Noise Uncertainty at Low SNR

2021 ◽  
pp. 153741
Author(s):  
Ramsha Ahmed ◽  
Yueyun Chen ◽  
Bilal Hassan
Keyword(s):  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Wireless Sensor ◽  
Noise Uncertainty ◽  
Low Snr

Novel Spectrum Sensing Technique and Its Evaluation for Cognitive Radio Wireless Sensor Network

2020 ◽  
Vol 20 (03) ◽  
pp. 2050009
Author(s):  
GARIMA MAHENDRU ◽  
ANIL K. SHUKLA ◽  
L. M. PATNAIK
Keyword(s):  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Dynamic Spectrum Access ◽  
Substantial Reduction ◽  
Wireless Sensor ◽  
Low Snr ◽  
Double Threshold

Cognitive Radio based Wireless Sensor Network is a novel concept that integrates the dynamic spectrum access capability of cognitive radio into wireless sensor networks for the futuristic sensor networks and wireless communication technology. Spectrum sensing plays a quintessential role in a cognitive radio network but is a major constraint for a battery powered sensor with stringent energy limitations. The spectrum sensing algorithms are expected to yield acceptable detection probability at low SNR under noise uncertainty with minimum power consumption in a WSN. In this paper, a new spectrum sensing method has been proposed to overcome sensing failure under low SNR environment. The proposed technique is based on adaptive double threshold theory which improves the detection performance by 39.63 and 27.22% at SNR = −10dB as compared to the conventional energy detection and available double threshold-based method respectively. Furthermore, the proposed method of spectrum sensing is evaluated for its deployment into a CR-WSN using the evaluation metrics: Time and Sample Complexity. The comparative evaluation of the spectrum sensing method in a WSN through simulations shows that the proposed technique offers substantial reduction in sample and time complexity of the wireless sensor nodes.

scholarly journals A Low-Power Multi Resolution Spectrum Sensing Architecture for a Wireless Sensor Network with Cognitive Radio

2011 ◽  
Vol E94-A (11) ◽  
pp. 2287-2294 ◽  
Author(s):  
Toshihiro KONISHI ◽  
Shintaro IZUMI ◽  
Koh TSURUDA ◽  
Hyeokjong LEE ◽  
Takashi TAKEUCHI ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Low Power ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Wireless Sensor

scholarly journals SenPUI: Solutions for Sensing and Primary User Interference in Cognitive Radio Implementation of a Wireless Sensor Network

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Kedir Mamo Besher ◽  
Juan-Ivan Nieto-Hipolito ◽  
Mabel Vazquez Briseno ◽  
Raymundo Buenrostro Mariscal
Keyword(s):  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Spectrum Sharing ◽  
Primary User ◽  
Spectrum Management ◽  
Wireless Sensor ◽  
Battery Lifetime ◽  
Base Solution ◽  
User Interference

After an introduction of cognitive radio (CR) technology in communication, the hot research topics are sensing, Primary User Interference (PUI), spectrum management, security, spectrum sharing, and environmental sensing. Among the listed, sensing and Primary User Interference are the bold ones. The base query for these two problems lays finding a means for which and what channel at a particular time is available and avoiding interference with Primary Users (PU). This article presents a novel cognitive radio algorithm called SenPUI for both mentioned main challenges, sensing and PUI. First, energy scan during the inactive portion of communication which is dynamic is done. Second, application packet based primary user identification for PUI avoidance is proposed as base solution. Both techniques described in this work are implemented and resulted in a significant reduction of the target problems estimated around 10-30% reduction in average. Main limitations of Wireless Sensor Network (WSN) such as memory, battery lifetime, and size are considered during the design and implementation of our solutions.

scholarly journals Design of utility functions for game-based channel allocation in cognitive radio wireless sensor network

2021 ◽  
Vol 22 (2) ◽  
pp. 1013
Author(s):  
Prativa Rai ◽  
Mrinal Kanti Ghose ◽  
Hiren Kumar Deva Sarma
Keyword(s):  
Game Theory ◽  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Utility Function ◽  
Sensor Network ◽  
Channel Allocation ◽  
High Growth ◽  
Utility Functions ◽  
Wireless Sensor ◽  
Allocation Algorithm

Cognitive radio enabled wireless sensor network is capable of reducing the spectrum scarcity problem of the wireless networks. Looking at the scarcity of available bandwidth, and the high growth in the number of communication devices in recent times, cognitive radio technology has proven to be a promising technology for the days to come. The application of Game Theory in cognitive radio networks has been visible in recent research works. However, only limited literature is available in which possibilities of applying the game-theory based approaches for the challenging task of channel assignment in cognitive radio wireless sensor are available in the literature. It is understood that the crux of the solution to the problem of scheming games for allocation of the channel is centered on the selection of the utility function in order to increase the efficiency of the channel allocation algorithm. Accordingly, the study regarding the influence of several utility functions on the performance of the corresponding channel allocation algorithm is important.  Such a study enables designers to arrive at the optimal utility function to be used in game-theory based channel allocation algorithms, and the same is explored to the best extent, in this paper. The detailed procedure of allocating channels to all the contending nodes through game-based channel allocation has been discussed in this paper. Moreover, the performance of six different utility functions proposed which can be used for channel allocation using game theory has been evaluated for respective performances through MATLAB-based simulations.

scholarly journals Application of Wireless Sensor Network Technology in Security Control of Intelligent Buildings

2018 ◽  
Vol 14 (05) ◽  
pp. 93
Author(s):  
Jin Wang ◽  
Hua Shao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Information Integration ◽  
Large Scale ◽  
Wireless Sensor ◽  
Signal Spectrum ◽  
Support Vector ◽  
Security Monitoring ◽  
Task Coordination

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-GB; mso-bidi-language: AR-SA;" lang="EN-GB">When a wireless sensor network is used to perform real-time security monitoring inside a building, there are drawbacks like multi-path signal fading and difficulty in spectrum sensing. In light of these problems, this paper proposes an improved signal spectrum sensing algorithm based on support vector machine (SVM), which inhibits the impacts brought by the low signal-noise-ratio (SNR) environment in the transmission process of wireless sensor signals through the embedded cyclostationary characteristic parameters. Based on this, considering the low efficiency and poor fault tolerance of multi-task monitoring and scheduling inside the building, this paper also proposes a multi-task coordination and scheduling algorithm based on physical information integration, which achieves multi-task scheduling and execution through intelligent breakdown and prioritization of general tasks. The simulation test shows that, compared with the artificial neural network (ANN) algorithm and the maximum-minimum eigenvalue (MME) algorithm, the proposed algorithm has much better spectrum sensing effect under low SNR, takes less computation time, and achieves higher accuracy in large-scale multi-task coordination and scheduling. The research conclusions can provide new ideas for the application of wireless sensor network in intelligent building security monitoring.</span>

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