An Improved Optimal Channel Sensing Algorithm in Cognitive Radio Networks Used for Video Surveillance

Authors

  • Ranjita Joon JC Bose university of Science & Technology, YMCA, Faridabad, India
  • Parul Tomar JC Bose university of Science & Technology, YMCA, Faridabad, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1927

Keywords:

cognitive radio networks, Q Learning, Double DQN, Energy Detection, Signal to Noise Ratio

Abstract

With a rapid rise in the number of wireless devices and gadgets, a shortage in the spectrum bands for wireless communications has been observed. To overcome this problem of shortage of spectrum bands, a new technology called Cognitive Radio Networks (CRNs) was adopted. CRNs help us utilize the spectrum bands which are currently being underutilized by opportunistically and intelligently switching to these underutilized white spaces. Thus, CRNs aim to use the frequency spectrum in an opportunistic manner by allowing different users to operate in available frequency bands without interference. In this paper, Double Q Learning (DQN) with prioritized experience relay approach has been used to study the throughput of the network at different parameters and to draw a relationship between throughput and Probability of Undetectable User Transmission. Double Q Learning (DQN) with prioritized experience relay is a reinforcement learning based method that adds backward exploration to the forward exploration of Q Learning method. Both forward and backward exploration are used to update the Q values. Since the sensor nodes in the cognitive environment have limited energy, and sensing the spectrum band involves energy consumption, so the technique for sensing should be energy efficient so that the sensor nodes can be effectively used for various operations of video surveillance.

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Author Biographies

Ranjita Joon, JC Bose university of Science & Technology, YMCA, Faridabad, India

Ranjita Joon, Assistant Professor in computer science department at Pt. JLN Government College, Faridabad. Her areas of interest include cognitive radio networks, wireless sensor networks, and data mining. She is currently pursuing her Phd degree in the area of cognitive radio networks at J.C.Bose University of Science & Technology, Faridabad.

Parul Tomar, JC Bose university of Science & Technology, YMCA, Faridabad, India

Parul Tomar, Associate Professor in department of computer engineering at JC Bose University of Science & Technology, YMCA, Faridabad. Her areas of interst are Database, IoT, Adhoc Networks and security. She is having more than 18 years of experience. She has authored more than 50 papers in various journals of repute.

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https://medium.com/@parsa_h_m/deep-reinforcement-learning-dqn-double-dqn-dueling-dqn-noisy-dqn-and-dqn-with-prioritized-551f621a9823

Published

2022-11-15

Issue

Section

New Trends in Real-Time Image and Video Processing for Surveillance and Security