A Quick Overview of Different Spectrum Sensing Techniques

2019 ◽  
pp. 52-69
Author(s):  
Pooja Joshi ◽  
Ashish Bagwari ◽  
Ashish Negi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Practical Implementation ◽  
Cooperative Sensing ◽  
Shadow Fading ◽  
Wireless Technology ◽  
Next Generation ◽  
Wireless Technologies ◽  
Advantages And Disadvantages ◽  
Spectrum Holes

The next generation of emerging wireless technology is dealing with spectrum shortage. For appropriate and practical implementation of latest wireless technologies, the sufficient amount of frequency is needed. Cognitive radio (CR) is introduced as a proficient nominee to manage spectral undersupply problem, as it rapidly increases the use of underutilize spectrum via spectrum sensing. This chapter introduces brief start about spectrum holes in addition to spectrum sensing framework. Further, the chapter explains the issues in spectrum sensing and how the cooperative sensing technique is fit to overcome these issues like shadow fading and receiver uncertainty. Consequently, the various non-cooperative sensing techniques are also discussed including their test statics. The advantages and disadvantages of different sensing techniques is exhibited at the end.

SPECTRUM SENSING TECHNIQUES FOR NEXT GENERATION WIRELESS TECHNOLOGIES

2020 ◽  
Vol 79 (13) ◽  
pp. 1149-1166
Author(s):  
Parnika Kansal ◽  
A. Kumar ◽  
M. Gangadharappa
Keyword(s):  
Spectrum Sensing ◽  
Next Generation ◽  
Wireless Technologies

Performance Evaluation of SDR Blade RF using Wide-band Monopole Antenna for Spectrum Sensing Applications

2021 ◽  
Vol 36 (4) ◽  
pp. 419-424
Author(s):  
Ahmed Ibrahim ◽  
Wael Ali ◽  
Hassan Aboushady
Keyword(s):  
Performance Evaluation ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Ground Plane ◽  
Wide Band ◽  
Monopole Antenna ◽  
Antenna Design ◽  
Wireless Technologies ◽  
Sensing Applications

A spectrum-sensing algorithm is used to detect the available and the occupied frequency bands. The wideband antenna design approach is used for a microstrip fed monopole antenna that can be used for various wireless technologies such as GSM, UMTS, LTE, and WiFi operating at different frequencies from 1.25 to 3 GHz. The antenna is constructed from two copper layers of rectangular radiator and a partial ground plane. These layers are printed on an RO4003 substrate with dimensions 60 x 80 mm2. The antenna is experimentally fabricated to verify the simulation predictions and good matching between simulated and measured results is achieved. The wide-band antenna is tested by connecting it to the receiver of the Blade-RF Software Defined Radio (SDR) platform. A matlab script is then used to control the SDR board and to perform Spectrum Sensing for Cognitive Radio Applications.

Deep Cooperative Spectrum Sensing Utilizing Recurrent Convolutional Neural Networks

2020 ◽  
Author(s):  
Rahil Sarikhani ◽  
Farshid Keynia
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Recurrent Neural Network ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Secondary Users ◽  
Spectrum Holes

Abstract Cognitive Radio (CR) network was introduced as a promising approach in utilizing spectrum holes. Spectrum sensing is the first stage of this utilization which could be improved using cooperation, namely Cooperative Spectrum Sensing (CSS), where some Secondary Users (SUs) collaborate to detect the existence of the Primary User (PU). In this paper, to improve the accuracy of detection Deep Learning (DL) is used. In order to make it more practical, Recurrent Neural Network (RNN) is used since there are some memory in the channel and the state of the PUs in the network. Hence, the proposed RNN is compared with the Convolutional Neural Network (CNN), and it represents useful advantages to the contrast one, which is demonstrated by simulation.

scholarly journals Spectrum Sensing for Cognitive Vehicular Networks over Composite Fading

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Haroon Rasheed ◽  
Nandana Rajatheva
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Large Scale ◽  
Vehicular Networks ◽  
Multipath Fading ◽  
Energy Detection ◽  
Shadow Fading ◽  
Radio System ◽  
Composite Fading ◽  
Hidden Terminal

Recent advancement in vehicular wireless applications is also a major contributing factor in spectrum scarcity. Cognitive radio system is a mechanism which allows unlicensed cognitive users (CUs) to utilize idle unused bands. Fast and reliable detection of primary legacy user is the key component of cognitive radio networks. However, hidden terminal and low SNR problems due to shadow fading put fundamental limit to the sensing performance and practical entailments in design of the cognitive vehicular networks. Extensive modeling is being carried out to specify varying channel characteristics, particularly multipath fading and shadowing. Energy detection-(ED-) based spectrum sensing is a viable choice for many vehicle-to-vehicle (V2V) and vehicle to-road-side infrastructure (V2I) communications. This paper examines the performance of spectrum sensing using ED over Gamma-shadowed Nakagami-m composite fading channel to cater for both small-and-large scale fading. The results highlight the notable impact of shadowing spread and fading severity on detection performance. The relevant simulation results are presented to support our analytical results for average detection probability. Furthermore, these results are investigated and compared to other compound and classical channels.

Detection Reliability and Throughput Analysis for Cooperative Spectrum Sensing in Cognitive Radio Networks

2012 ◽  
Vol 457-458 ◽  
pp. 668-674
Author(s):  
Hong Du ◽  
Zai Xue Wei ◽  
Yu Wang ◽  
Da Cheng Yang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
High Reliability ◽  
Radio Networks ◽  
Shadow Fading ◽  
Sensing Technology ◽  
The Impact ◽  
Cooperative Algorithm

In cognitive radio networks (CRNs), cooperative spectrum sensing technology could overcome the impact from shadow fading and noise uncertainty; however, cognitive radio users with different signal-to-noise ratios (SNRs) would cause the unreliable detection performance when making a decision in the information fusion center. Therefore, a novel cooperative spectrum sensing scheme which focus on the reliability of cognitive radio users is presented. The proposed approach does not select all of the cognitive radio users but the ones whose SNR is beyond the average SNR of the whole users for high reliability. Moreover, the detection and throughput performance is investigated. Simulation results illustrate this approach could enhances the detection probability by comparing to the conventional cooperative algorithm. Besides, it also could lead to higher throughput within a short spectrum sensing time.

scholarly journals A Classification of the Spectrum Sensing Techniques for Cognitive Radio

2019 ◽  
Vol 8 (4) ◽  
pp. 11586-11595
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Prior Information ◽  
Primary User ◽  
Probability Of Detection ◽  
Coherent Detection ◽  
Main Function ◽  
Advantages And Disadvantages ◽  
Wideband Spectrum Sensing

Cognitive radio is a solution to the problem of radio spectrum scarcity. It gives the opportunity to a secondary user to exploit the spectrum allocated toa primary user. The main function of cognitive radio is spectrum sensing whichhas gained new aspects in the last decades to determine opportunistic spectrum holes. There are many spectrumsensing methods proposed in the literature. The Performance of thesetechniques may vary in different situations; it can be described by probability of detection, probability of false alarm, and sensing time. It is therefore important to compare and indicate the best scheme for a specified scenario. In this paper, we propose a classification of the main approaches of single user spectrum sensing based on its synchronization requirement into two main categories: coherent detection and non-coherent detection. The coherent detection needs some or full prior information about the primary user signal for detecting it, where the non-coherent detection does not need any prior information about the primary user signal for detecting it. In addition, we highlight the advantages and disadvantages of narrowband and wideband spectrum sensing procedures along with the challenges involved in their implementation.Furthermore, we introduce the concept and basics of cooperative sensing and interference based sensing.This paper helps the designer to be familiar with all the techniques used to achieve spectrum sensing.

Throughput optimization for dual collaborative spectrum sensing with dynamic scheduling

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740089 ◽  
Author(s):  
Cuimei Cui ◽  
Dezhi Yang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Optimization Algorithm ◽  
Ad Hoc ◽  
Dynamic Scheduling ◽  
Throughput Optimization ◽  
Shadow Fading ◽  
Average Throughput ◽  
Collaborative Spectrum Sensing ◽  
Sensing Time

Cognitive radio technology is envisaged to alleviate both spectrum inefficiency and spectrum scarcity problems by exploiting the existing licensed spectrum opportunistically. However, cognitive radio ad hoc networks (CRAHNs) impose unique challenges due to the high dynamic scheduling in the available spectrum, diverse quality of service (QOS) requirements, as well as hidden terminals and shadow fading issues in a harsh radio environment. To solve these problems, this paper proposes a dynamic and variable time-division multiple-access scheduling mechanism (DV-TDMA) incorporated with dual collaborative spectrum sensing scheme for CRAHNs. This study involves the cross-layered cooperation between the Physical (PHY) layer and Medium Access Control (MAC) layer under the consideration of average sensing time, sensing accuracy and the average throughput of cognitive radio users (CRs). Moreover, multiple-objective optimization algorithm is proposed to maximize the average throughput of CRs while still meeting QOS requirements on sensing time and detection error. Finally, performance evaluation is conducted through simulations, and the simulation results reveal that this optimization algorithm can significantly improve throughput and sensing accuracy and reduce average sensing time.

Spectrum Sensing Techniques

2019 ◽  
pp. 125-132 ◽  
Author(s):  
Rajib Biswas
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Future Challenges ◽  
Spectrum Holes

Cognitive radio has come a long way in the recent years with the advent of improved algorithms and instrumentation. However, for ease and efficient working of cognitive radio, there is a need to have effective detection of spectrum sensing. The objective of spectrum sensing techniques is to find spectrum holes which can be accessible by the users of cognitive radio. The deployment of suitable sensing techniques reduces undesirable congestion in traffic and enhancement of spectrum usage. All these require sensing techniques whose main goal is oriented towards efficient identification and subsequent deployment of spectrum. This chapter is aimed to give a brief overview of some spectrum sensing techniques. An attempt is made to give the characteristics of the highly deployable sensing schemes. Accordingly, the merits and demerits are comprehensively highlighted. Further, emphasis has been given to relevant future challenges.

Sensing Techniques for Next Generation Cognitive Radio Networks

2019 ◽  
pp. 108-124
Author(s):  
Dhaya R. ◽  
Rajeswari A. ◽  
Kanthavel R.
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Spectrum Sharing ◽  
Spectrum Management ◽  
Radio Networks ◽  
Maximum Throughput ◽  
Spectrum Mobility ◽  
Static Allocation ◽  
Spectrum Holes

Cognitive radio is the technology used to solve the problem of spectrum underutilization by performing spectrum sensing, spectrum management, spectrum sharing, and spectrum mobility. The primary goal of cognitive radio is open spectrum sharing. Spectrum is a scarce and valuable natural resource that has to be used very effectively. The static allocation of spectrum to the licensed users will lead to wastage of resources when the spectrum is unused by the licensed user. Spectrum sensing methodology helps in detecting the spectrum holes and enables the unlicensed users to access the unused bands in the licensed spectrum effectively without interfering the licensed users. Cognitive thinking takes wireless communication to the next level by sensing the electromagnetic environment and dynamically adjusts its operating parameters in order to achieve maximum throughput, mitigate interference, facilitate interoperability, etc. The chapter presents the basics of cognitive radio networks, its architecture, its application, and advantages of cognitive radio networks.

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