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 Transmission protocols in Cognitive Radio Mesh Networks

2015 ◽  
Vol 5 (6) ◽  
pp. 1446
Author(s):  
Anusha M ◽  
Srikanth Vemuru ◽  
T Gunasekhar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Mesh Networks ◽  
Dynamic Spectrum ◽  
Mac Protocols ◽  
Radio Network ◽  
Medium Access ◽  
Primary Users

A Cognitive Radio (CR) is a radio that can adjust its transmission limit based on available spectrum in its operational surroundings. Cognitive Radio Network (CRN) is made up of both the licensed users and unlicensed users with CR enable and disabled radios. CR’S supports to access dynamic spectrum and supports secondary user to access underutilized spectrum efficiently, which was allocated to primary users. In CRN’S most of the research was done on spectrum allocation, spectrum sensing and spectrum sharing. In this literature, we present various Medium Access (MAC) protocols of CRN’S. This study would provide an excellent study of MAC strategies.

scholarly journals Modeling Study on Dynamic Spectrum Sharing System Under Interference Temperature Constraints in Underground Coal Mines

2015 ◽  
Vol 8 (1) ◽  
pp. 140-148
Author(s):  
Chen Guizhen ◽  
Ding Enjie ◽  
Wang Gang ◽  
Xue Xue
Keyword(s):  
Spectrum Sharing ◽  
Dynamic Spectrum Access ◽  
Coal Mines ◽  
Dynamic Spectrum ◽  
Utilization Efficiency ◽  
Spectrum Access ◽  
Secondary Users ◽  
Dynamic Spectrum Sharing ◽  
Interference Temperature ◽  
Access System

This paper proposes a dynamic spectrum access system for underground wireless communication——a dynamic spectrum sharing system under interference temperature constrains. It can make the best of spectrum resources and improve the utilization efficiency. Then, a multi-dimensional Markov chain is used to model the system. On the basis, the secondary users’ performance under interference temperature constrains is obtained. As two important performance indexes to measure secondary users’ performance, cognitive users’ interrupting probability and blocking probability are calculated. Finally, cognitive users’ performance under different users’ access is analyzed, and the performances in dynamic spectrum access system and overlay access system are compared. Simulation results indicate that the dynamic spectrum sharing access system under interference temperature constrains is superior to the overlay access system and helpful to improve the spectrum sharing system in coal mines.

scholarly journals ESTUDO PRÉ-PROSPECTIVO PARA ROADMAP TECNOLÓGICO SOBRE RÁDIO COGNITIVO: EVOLUÇÃO CIENTÍFICO-PATENTÁRIA ENTRE 1970-2017

2018 ◽  
Vol 11 (3) ◽  
pp. 861
Author(s):  
Andrade José Luiz Andrade ◽  
David Fernandes Cruz Moura Moura ◽  
Suzana Borschiver Borschiver Borschiver
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Smart Antenna ◽  
Dynamic Spectrum ◽  
White Space ◽  
Dynamic Spectrum Sharing

<p>Avanços tecnológicos como digitalização das camadas físicas nos meios de comunicação tem promovido grande impacto na sociedade mundial em curto período de tempo. Nos últimos anos, complexos desafios propostos pela Era do Conhecimento incluem equilibrar o aumento exponencial de novos usuários a um espectro eletromagnético limitado se utilizado de forma convencional, como ocorre na atualidade. O Rádio Cognitivo emerge como uma tecnologia habilitadora para o uso eficiente e dinâmico do espectro, capaz de elevar os parâmetros de qualidade do serviço, ampliar o grau de confiabilidade e de plena utilização espectral. Este artigo explora tendências apontadas pelo estudo finlandês, <em>Trial Cognitive Radio Innovation Landscape, </em>no período 1970-2011 e monitora a evolução tecnológica entre 2012 e 2017. A análise bibliométrica permite antecipar crescente maturidade em domínios como <em>spectrum sensing, cognitive &amp; Spectrum sensing</em> e <em>dynamic spectrum sharing/management</em> e intenso esforço inovativo em <em>white space &amp; LTE, cognitive &amp; LTE </em>e<em> </em><em>cognitive &amp; smart antenna.</em></p>

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.

Basic Spectrum Sensing Techniques

2019 ◽  
pp. 70-84
Author(s):  
Bhuvaneswari P. T. V. ◽  
Bino J.
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Spectrum ◽  
Spectrum Management ◽  
Radio Network ◽  
Spectrum Band ◽  
Radio Systems ◽  
Networking Technology

Cognitive radio network (CRN) is an upcoming networking technology that can utilize both radio spectrum and wireless resources efficiently based on the information gathered from the past experience. There are two types of users in CRN, namely primary and secondary. PUs (PU) have the license to operate in certain spectrum band while the secondary (SU) or cognitive radio (CR) users do not have the license to operate in the desired band. However, they can opportunistically utilize the unused frequency bands. Spectrum sensing, spectrum management, spectrum sharing, and spectrum mobility are the four major functions of cognitive radio systems. The main objective of spectrum sensing is to provide better spectrum access to CR users, without causing any harmful interference to PUs. Sensing accuracy is considered as the most important factor to determine the performance of cognitive radio network. In this chapter, the challenges and requirement involved in spectrum sensing are detailed. Further, various spectrum sensing basic techniques are also discussed in detail.

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.

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