scholarly journals Spectrum Efficiency Optimization for UAV-Based Cognitive Radio Network

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hongwei Zhang ◽  
Xinyu Da ◽  
Hang Hu ◽  
Lei Ni ◽  
Yu Pan
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Time Slot ◽  
Primary User ◽  
Spectrum Efficiency ◽  
Frame Structure ◽  
Radio Network ◽  
Aerial Vehicle

Unmanned aerial vehicle- (UAV-) assisted communication has great potential to provide on-demand wireless services and improve the outdoor link throughput. In this paper, a UAV-based cognitive radio network (CRN) is investigated in which the UAV works as a secondary user (SU). Considering the overlay spectrum sensing mode, the UAV can operate on the licensed spectrum bands of primary user (PU) only when PU is idle. In each working frame structure, both sensing time slot and transmission time slot are analysed in radians. Specifically, our objective is to maximize the spectrum efficiency (SE) of the UAV by jointly optimizing the sensing radian and the number of radians. For the single-radian and multiradian schemes, the dichotomy and alternative iterative optimization (AIO) algorithm are proposed to solve the SE optimization problem. Simulation results show that the proposed multiradian cooperative spectrum sensing (CSS) scheme can achieve better performance on ensuring the quality-of-service (QoS) of the PU, and it can significantly enhance the SE of the UAV especially in the severe channel environments.

scholarly journals Throughput Maximization by Optimizing Secondary Users in a Cooperative Cognitive Radio Network using Hard Fusion Rules

2020 ◽  
Vol 9 (7) ◽  
pp. 801-804
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Spectrum Efficiency ◽  
Throughput Maximization ◽  
Radio Network ◽  
Secondary Users ◽  
Fusion Rules ◽  
Channel Throughput

Cognitive radio network is a promising technology for enabling secondary users to utilize the licensed spectrum of the primary user without causing interference. The data trans- mitted by the secondary users through primary channel without affecting the primary user is known as channel throughput. In cooperative spectrum sensing(CSS) as the number of secondary users increases the channel throughput increases which in turn reduces the spectrum efficiency due to more spectrum wastage. Therefore in this paper, channel throughput is maximized by optimizing secondary users proposed and throughput for variable secondary users for OR and AND fusion rules is investigated. The optimal secondary users is estimated mathematically and simulation results shows the variation of throughput for variable number of secondaryusers

scholarly journals Efficient Utilization of Cooperative Spectrum Sensing (CSS) in Cognitive Radio Network (CRN) Using Non-Orthogonal Multiple Access (NOMA)

2021 ◽  
Author(s):  
BALACHANDER T ◽  
Mukesh Krishnan M B
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Multiple Access ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
The Novel ◽  
Radio Network ◽  
Secondary Users

Abstract In the recent past, efficient cooperative spectrum sensing and usage are playing a vital role in wireless communication because of the significant progress of mobile devices. There is a recent surge and interest on Non-Orthogonal Multiple Access (NOMA) focused on communication powered by wireless mode. In modern research, more attention has been focused on efficient and accurate Non-Orthogonal Multiple Access (NOMA). NOMA wireless communication is highly adapted with Cognitive Radio Network (CRN) for improving performance. In the existing cognitive radio network, the secondary users could be able to access the idle available spectrum while primary users are engaged. In the traditional CRN, the primary user’s frequency bands are sensed as free, the secondary users could be utilized those bands of frequency resources. In this research, the novel methodology is proposed for cooperative spectrum sensing in CRN for 5G wireless communication using NOMA. The higher cooperative spectrum efficiency can be detected in the presence of channel noise. Cooperative spectrum sensing is used to improve the efficient utilization of spectrum. The spectrum bands with license authority primary user are shared by Secondary Users (SU) by simultaneously transmitting information with Primary Users (PU). The cooperative spectrum sensing provides well under the circumstances that the different channel interference to the primary user can be guaranteed to be negligible than an assured thresholding value. The Noisy Channel State Information (CSI) like AWGN and Rayleigh fading channels are considered as wireless transmission mediums for transmitting a signal using Multiple-Input-Multiple-Output (MIMO) NOMA to increase the number of users. The proposed NOMA is fascinated with significant benefits in CRN is an essential wireless communication method for upcoming 5G technology. From experimental results it has been proved that the novel methodology performance is efficient and accurate than existing methodologies by showing graphical representations and tabulated parameters.

scholarly journals Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Hiep Vu-Van ◽  
Insoo Koo
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Goodness Of Fit ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Harmful Effect ◽  
Radio Network ◽  
Measured Distance ◽  
Simulation Results ◽  
Sample Set

Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.

scholarly journals Cooperative Spectrum Sensing Based on Multi-Features Combination Network in Cognitive Radio Network

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 129
Author(s):  
Mingdong Xu ◽  
Zhendong Yin ◽  
Yanlong Zhao ◽  
Zhilu Wu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Primary User ◽  
Radio Spectrum ◽  
Local Information ◽  
Channel State ◽  
Single Node

cognitive radio, as a key technology to improve the utilization of radio spectrum, acquired much attention. Moreover, spectrum sensing has an irreplaceable position in the field of cognitive radio and was widely studied. The convolutional neural networks (CNNs) and the gate recurrent unit (GRU) are complementary in their modelling capabilities. In this paper, we introduce a CNN-GRU network to obtain the local information for single-node spectrum sensing, in which CNN is used to extract spatial feature and GRU is used to extract the temporal feature. Then, the combination network receives the features extracted by the CNN-GRU network to achieve multifeatures combination and obtains the final cooperation result. The cooperative spectrum sensing scheme based on Multifeatures Combination Network enhances the sensing reliability by fusing the local information from different sensing nodes. To accommodate the detection of multiple types of signals, we generated 8 kinds of modulation types to train the model. Theoretical analysis and simulation results show that the cooperative spectrum sensing algorithm proposed in this paper improved detection performance with no prior knowledge about the information of primary user or channel state. Our proposed method achieved competitive performance under the condition of large dynamic signal-to-noise ratio.

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