Joint Optimization of Spectrum Sensing and Energy Harvesting for Cognitive Radio Network

2017 ◽  
Author(s):  
Fu Jiang ◽  
Wenni Yi ◽  
Shuo Li ◽  
Baolin Zhu ◽  
Wentao Yu
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Joint Optimization ◽  
Radio Network

scholarly journals Throughput Optimization of Parallel Sensing and Energy Harvesting Cognitive Radio Network

2021 ◽  
Vol 38 (3) ◽  
pp. 739-745
Author(s):  
Anitha Bujunuru ◽  
Srinivasulu Tadisetty
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Secondary User ◽  
Throughput Optimization ◽  
Radio Network ◽  
Parallel Operation ◽  
Harvesting Technique ◽  
Reduction Of Energy Consumption

In cognitive radio, throughput of secondary user (SU) will depend on spectrum sensing performance and available power of secondary user to transmits data. As the secondary user dissipates energy for spectrum sensing operation and to maintain cooperation among multiple SUs can results in reduction of transmission power. To compensate this energy, an energy harvesting technique has introduced in cognitive radio by which SU can harvest energy from primary (PU) signal and this harvested energy will be utilized to transmit its data and increases the lifetime. In a traditional Energy Harvesting Cognitive Radio Network (EHCRN), SU can perform sensing and harvesting in separate slots which decrease the transmission time of secondary user results in reduction in throughput. To enhance the throughput of secondary user, a parallel operation of spectrum sensing and energy harvesting has been discussed. This parallel operation results in reduction of energy consumption and increases harvested energy that makes more energy to be available for transmission, which results in an increase of SU throughput. Simulation results using MATLAB shows that the proposed Parallel Sensing and Energy Harvesting CRN have improved the throughput compared to Traditional Energy Harvesting CRN and are analyzed with different parameters.

Optimal Energy Harvesting-based Weighed Cooperative Spectrum Sensing in Cognitive Radio Network

2016 ◽  
Vol 21 (6) ◽  
pp. 908-919 ◽  
Author(s):  
Xin Liu ◽  
Kunqi Chen ◽  
Junhua Yan ◽  
Zhenyu Na
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Radio Network ◽  
Optimal Energy

Secrecy and throughput performance of an energy harvesting hybrid cognitive radio network with spectrum sensing

2019 ◽  
Vol 26 (2) ◽  
pp. 1301-1314 ◽  
Author(s):  
Pranabesh Maji ◽  
Kuldeep Yadav ◽  
Sanjay Dhar Roy ◽  
Sumit Kundu
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Throughput Performance

Analysis of Spectrum Sensing Error and Spectrum Handoff for Non-Uniform Unlicensed Users in Cognitive Radio Network

2018 ◽  
Vol 11 (2) ◽  
pp. 143-154
Author(s):  
Kandasamy Subramanian Preetha ◽  
Shanmugam Kalaivani ◽  
Thangappa Velmurugan
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Spectrum Handoff

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.

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