scholarly journals Secrecy Performance Analysis of a Cognitive Network for IoT over k - μ Channels

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Junxia Li ◽  
Hui Zhao ◽  
Michael Johnson
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Effective Solution ◽  
Secondary Users ◽  
Limit Values ◽  
Single Antenna ◽  
Secondary Networks

With the development of Internet of Things (IoTs), devices are now connecting and communicating together on a heretofore unheard-of scale, forming huge heterogeneous networks of mobile IoT-enabled devices. For beyond 5G- (B5G-) enabled networks, this raises concerns in terms of spectral resource allocation and associated security. Cognitive radio is one effective solution to such a spectrum sharing issue which can be adopted to these B5G networks, which works on the principle of sharing spectrum between primary and secondary users. In this paper, we develop the confidentiality of cognitive radio network (CRNs) for IoT over k - μ fading channels, with the information transmitted between secondary networks with multiple cooperative eavesdroppers, under the constraint of the maximum interference that the primary users can tolerate. All considered facilities use a single-antenna receiver. Of particular interest, the minimum limit values of secure outage probability (SOP) and the probability of strictly positive secrecy capacity (SPSC) are developed for this model in a concise form. Finally, the Monte Carlo simulations for the system are provided to support the theoretical analysis presented.

scholarly journals A Graph Convolutional Network-Based Deep Reinforcement Learning Approach for Resource Allocation in a Cognitive Radio Network

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5216
Author(s):  
Di Zhao ◽  
Hao Qin ◽  
Bin Song ◽  
Beichen Han ◽  
Xiaojiang Du ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Model Learning ◽  
Secondary Users ◽  
Convolutional Network ◽  
Optimal Resource

Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can effectively achieve spectrum sharing and co-channel interference (CCI) mitigation. In this paper, we propose a joint channel selection and power adaptation scheme for the underlay cognitive radio network (CRN), maximizing the data rate of all secondary users (SUs) while guaranteeing the quality of service (QoS) of primary users (PUs). To exploit the underlying topology of CRNs, we model the communication network as dynamic graphs, and the random walk is used to imitate the users’ movements. Considering the lack of accurate channel state information (CSI), we use the user distance distribution contained in the graph to estimate CSI. Moreover, the graph convolutional network (GCN) is employed to extract the crucial interference features. Further, an end-to-end learning model is designed to implement the following resource allocation task to avoid the split with mismatched features and tasks. Finally, the deep reinforcement learning (DRL) framework is adopted for model learning, to explore the optimal resource allocation strategy. The simulation results verify the feasibility and convergence of the proposed scheme, and prove that its performance is significantly improved.

scholarly journals Heuristic Greedy Method for Spectrum Sensing in Cognitive Radio Network

2019 ◽  
Vol 9 (2) ◽  
pp. 1454-1459
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Dynamic Spectrum Access ◽  
Cognitive Radio Network ◽  
Dynamic Spectrum ◽  
Radio Network ◽  
Secondary Users ◽  
Dynamic Spectrum Sharing ◽  
Radio Frequency Spectrum

In recent years, radio frequency spectrum in wireless communication is not effectively utilized. To utilize the spectrum effectively, an optimistic technology called “Cognitive Radio network” used. It is the best preferable next generation wireless networks. Using DSA (Dynamic Spectrum Access) approaches, it shares the spectrum effectively between the primary and secondary users. It allows the secondary users to use the spectrum by dynamic spectrum sharing algorithms. When the primary users and secondary users are using same frequency band and transmitting simultaneously, there is a spectrum underlay problem in the network. A novel heuristic greedy algorithm proposed for improving the performance parameters of cognitive radio network using co-operative spectrum sensing.

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 Secure Beamforming in 5G-Based Cognitive Radio Network

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1260
Author(s):  
Hyils Sharon Magdalene Antony ◽  
Thulasimani Lakshmanan
Keyword(s):  
Cognitive Radio ◽  
Information Exchange ◽  
Cognitive Radio Network ◽  
Multiple Input Multiple Output ◽  
Primary User ◽  
Radio Network ◽  
Secrecy Rate ◽  
Secondary Users ◽  
Input Multiple Output ◽  
The Impact

Cognitive radio network (CRN) and non-orthogonal multiple-access (NOMA) is a significant system in the 5G wireless communication system. However, the system is an exceptional way for the cognitive users to secure a communication from the interferences in multiple-input multiple-output (MIMO)-NOMA-based cognitive radio network. In this article, a new beamforming technique is proposed to secure an information exchange within the same cells and neighboring cells from all intervened users. The interference is caused by an imperfect spectrum sensing of the secondary users (SUs). The SUs are intended to access the primary channels. At the same time, the primary user also returns to the channel before the SUs access ends. This similar way of accessing the primary channel will cause interference between the users. Thus, we predicted that the impact of interferences would be greatly reduced by the proposed technique, and that the proposed technique would maximize the entire secrecy rate in the 5G-based cognitive radio network. The simulation result provides better evidence for the performance of the proposed technique.

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