scholarly journals Spectrum Occupancy Information in Support of Adaptive Spectrum Sensing for Cognitive Radio

2014 ◽  
Vol 6 (1) ◽  
pp. 76 ◽  
Author(s):  
Kishor Puna Patil ◽  
Snehal Barge ◽  
Knud Erik Skouby ◽  
Ramjee Prasad
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Occupancy

scholarly journals Optimization of Spectrum Sensing Schemes in Cognitive Sensor Networks

2021 ◽  
Author(s):  
Amir Sepasi Zahmati
Keyword(s):  
Markov Chain ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Power Consumption ◽  
Spectrum Sensing ◽  
Optimization Problems ◽  
Hybrid Approach ◽  
Specific Method ◽  
Spectrum Occupancy ◽  
Cognitive Sensor Networks

The currently dominant spectrum allocation policy is reported to be inefficient. Cognitive radio, therefore, has been proposed in the literature to improve the spectrum usage efficiency. This dissertation proposes the optimization of spectrum sensing schemes in cognitive sensor networks. The modeling of the spectrum occupancy is a prerequisite for cognitive radio analysis. We describe the radio spectrum occupancy as a continuous- time Markov chain, and mathematically define the model by deriving the transition rate matrix and the probability state vector. The dissertation addresses an important aspect of spectrum sensing that has been often overlooked in the literature. While the cognitive radio is supposed to be aware of its surroundings, existing work does not consider the characteristics of unlicensed users for finding the optimum sensing period. In this work, we propose an application- specific method that finds the optimal sensing period according to the characteristics of both secondary and primary networks. According to the unlicensed user’s state in the Markov chain, two optimization problems are formulated to derive the optimum sensing periods. The secondary network’s throughput and power consumption are also studied and the corresponding parameters are derived. By numerical and simulation analyses, it is elaborated that the proposed method increases the secondary network’s throughput by up to 11% and significantly decreases the power consumption of the secondary network by as low as 33% of the non-hybrid approach. In addition, we study cooperative spectrum sensing in cognitive sensor networks and address two important issues. First, an optimization problem is solved to obtain the minimum required number of cognitive users. Second, we define a metric for sensing ac- curacy and propose a novel energy-aware secondary user selection method that identifies the most eligible cognitive users through a probability-based approach. The network’s lifetime is compared at several sensing accuracy thresholds and the trade-off between sensing accuracy and network lifetime is studied. Finally, the effects of several fusion rules on the proposed method are studied through simulation and numerical analyses. It is discussed that the Majority rule has the best performance among the examined rules. i

scholarly journals Optimization of Spectrum Sensing Schemes in Cognitive Sensor Networks

2021 ◽  
Author(s):  
Amir Sepasi Zahmati
Keyword(s):  
Markov Chain ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Power Consumption ◽  
Spectrum Sensing ◽  
Optimization Problems ◽  
Hybrid Approach ◽  
Specific Method ◽  
Spectrum Occupancy ◽  
Cognitive Sensor Networks

The currently dominant spectrum allocation policy is reported to be inefficient. Cognitive radio, therefore, has been proposed in the literature to improve the spectrum usage efficiency. This dissertation proposes the optimization of spectrum sensing schemes in cognitive sensor networks. The modeling of the spectrum occupancy is a prerequisite for cognitive radio analysis. We describe the radio spectrum occupancy as a continuous- time Markov chain, and mathematically define the model by deriving the transition rate matrix and the probability state vector. The dissertation addresses an important aspect of spectrum sensing that has been often overlooked in the literature. While the cognitive radio is supposed to be aware of its surroundings, existing work does not consider the characteristics of unlicensed users for finding the optimum sensing period. In this work, we propose an application- specific method that finds the optimal sensing period according to the characteristics of both secondary and primary networks. According to the unlicensed user’s state in the Markov chain, two optimization problems are formulated to derive the optimum sensing periods. The secondary network’s throughput and power consumption are also studied and the corresponding parameters are derived. By numerical and simulation analyses, it is elaborated that the proposed method increases the secondary network’s throughput by up to 11% and significantly decreases the power consumption of the secondary network by as low as 33% of the non-hybrid approach. In addition, we study cooperative spectrum sensing in cognitive sensor networks and address two important issues. First, an optimization problem is solved to obtain the minimum required number of cognitive users. Second, we define a metric for sensing ac- curacy and propose a novel energy-aware secondary user selection method that identifies the most eligible cognitive users through a probability-based approach. The network’s lifetime is compared at several sensing accuracy thresholds and the trade-off between sensing accuracy and network lifetime is studied. Finally, the effects of several fusion rules on the proposed method are studied through simulation and numerical analyses. It is discussed that the Majority rule has the best performance among the examined rules. i

In-band Spectrum Sensing without Quiet Period for OFDM System in Cognitive Radio

2011 ◽  
Vol 30 (11) ◽  
pp. 2638-2641
Author(s):  
Dong Chen ◽  
Jian-dong Li ◽  
Ji-yong Pang ◽  
Jing Ma
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Band Spectrum ◽  
Quiet Period ◽  
Ofdm System

An Energy Efficient Spectrum Aware Routing for Cognitive Radio Networks (CRNs)

2020 ◽  
Vol 10 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Jijesh J J ◽  
Mahaveer Penna ◽  
Shiva Shankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Research Work ◽  
Spectrum Management ◽  
Residual Energy ◽  
Radio Networks ◽  
Traffic Load ◽  
The Impact

Back Ground/ Aims:: Now-a-days in the Wireless Communications some of the spectrum bands are underutilized or unutilized; the spectrum can be utilized properly by using the Cognitive Radio Techniques using the Spectrum Sensing mechanisms. Objectives:: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods:: The detection of the spectrum hole plays a vital role in the routing of Cognitive Radio Networks (CRNs). While detecting the spectrum holes and the routing, sensing is impacted by the hidden node issues and exposed node issues. The impact of sensing is improved by incorporating the Cooperative Spectrum Sensing (CSS) techniques. Along with these issues the spectrum resources changes time to time in the routing. Results:: All the issues are addressed with An Energy Efficient Spectrum aware Routing (EESR) protocol which improves the timeslot and the routing schemes. The overall network life time is improved with the aid of residual energy concepts and the overall network performance is improved. Conclusion:: The proposed protocol (EESR) is an integrated system with spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it improves the Network Lifetime of the Overall Network and the Individual CR user, along with this the performance of the proposed protocol outperforms the conventional state of art routing protocols.

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