Cognitive Radio Networks with Non-Ideal Spectrum Sensing and Multiple Classes of Secondary Users

2018 ◽  
pp. 160-167
Author(s):  
Yuan Zhao ◽  
Wuyi Yue
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Secondary Users

Interference Modeling and Analysis in Cognitive Radio Networks

2013 ◽  
Vol 4 (4) ◽  
pp. 1-15
Author(s):  
Yanxiao Zhao ◽  
Bighnaraj Panigrahi ◽  
Kazem Sohraby ◽  
Wei Wang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Critical Role ◽  
Radio Networks ◽  
Secondary Users ◽  
Idle State ◽  
Modeling And Analysis ◽  
Interference Modeling ◽  
Primary Users

Cognitive radio networks (CRNs) have received considerable attention and viewed as a promising paradigm for future wireless networking. Its major difference from the traditional wireless networks is that secondary users are allowed to access the channel if they pose no harmful interference to primary users. This distinct feature of CRNs has raised an essential and challenging question, i.e., how to accurately estimate interference to the primary users from the secondary users? In addition, spectrum sensing plays a critical role in CRNs. Secondary users have to sense the channel before they transmit. A two-state sensing model is commonly used, which classifies a channel into either busy or idle state. Secondary users can only utilize a channel when it is detected to be in idle state. In this paper, we tackle the estimation of interference at the primary receiver due to concurrently active secondary users. With the spectrum sensing, secondary users are refrained from transmitting once an active user falls into their sensing range. As a result, the maximum number of simultaneously interfering secondary users is bounded, typically ranging from 1 to 4. This significant conclusion considerably simplifies interference modeling in CRNs. The authors present all the cases with possible simultaneously interfering secondary users. Moreover, the authors derive the probability for each case. Extensive simulations are conducted and results validate the effectiveness and accuracy of the proposed approach.

Fuzzy guided integrative factors-based spectrum decision-making in cognitive radio networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Suneetha Ch ◽  
Srinivasa Rao S ◽  
K.S. Ramesh
Keyword(s):  
Cognitive Radio ◽  
Service Quality ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Quality Factors ◽  
Secondary Users ◽  
Content Type ◽  
Primary Users ◽  
Spectrum Band

PurposeElectronic devices aid communication during new communication phases and the scope of cognitive radio networks has changed communication paradigms through efficient use of spectrums. The communication prototype of cognitive radio networks defines user roles as primary user and secondary user in the context of the spectrum allocation and use. The users who have licensed authority of the spectrum are denoted as primary users, while other eligible users who access the corresponding spectrum are secondary users.Design/methodology/approachThe multiple factors of transmission service quality can have a negative influence due to improper scheduling of spectrum bands between primary users and secondary users. There are considerable contributions in contemporary literature concerning spectrum band scheduling under spectrum sensing. However, the majority of the scheduling models are intended to manage a limited number of transmission service quality factors. Moreover, these service quality factors are functional and derived algorithmically from the current corresponding spectrum. However, there is evidence of credible performance deficiency regarding contemporary spectrum sensing methodsFindingsThis article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.Originality/valueThis article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

Secondary Data Transmissions with Two-Way Relay in Cognitive Radio Networks

2013 ◽  
Vol 336-338 ◽  
pp. 1650-1655
Author(s):  
Yuan Gao ◽  
Chang Ping Zhu ◽  
Yi Bin Tamg
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Secondary Data ◽  
Primary User ◽  
Radio Networks ◽  
Secondary Users ◽  
Step Model ◽  
Spectrum Hole ◽  
User Protection

For improving the spectrum hole utilization in cognitive radio networks, two-way relaying is used in this paper to assist two secondary users in exchanging information. The 2-step and 3-step two-way relaying models are respectively discussed with imperfect spectrum sensing. Moreover, the closed-form expressions of outage probability for the two models are derived with a primary user protection constraint. Simulation shows that 3-step model outperforms 2-step in terms of the outage performance.

Efficient Cooperative Spectrum Sensing with Minimum Sensing Error Probability in Heterogeneous Cognitive Radio Networks

Frequenz ◽  
2012 ◽  
Vol 66 (7-8) ◽  
Author(s):  
Hang Hu ◽  
Ning Li ◽  
Youyun Xu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Error Probability ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Decision Threshold ◽  
Cognitive Network ◽  
Secondary Users ◽  
Sensing Performance

AbstractTo improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. We focus on the optimization of cooperative spectrum sensing in which multiple secondary users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in heterogeneous cognitive radio (CR) networks. Rayleigh fading and Nakagami fading are considered respectively in cognitive network I and cognitive network II. For each cognitive network, we derive the optimal randomized rule for different decision threshold. Then, the optimal decision threshold is derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each secondary user which is randomly distributed in the heterogeneous cognitive radio networks.

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