1 research outputs found
Probability Density Function Estimation in OFDM Transmitter and Receiver in Radio Cognitive Networks based on Recurrent Neural Network
The most important problem in telecommunication is bandwidth limitation due
to the uncontrolled growth of wireless technology. Deploying dynamic spectrum
access techniques is one of the procedures provided for efficient use of
bandwidth. In recent years, cognitive radio network introduced as a tool for
efficient use of spectrum. These radios are able to use radio resources by
recognizing surroundings via sensors and signal operations that means use these
resources only when authorized users do not use their spectrum. Secondary users
are unauthorized ones that must avoid from interferences with primary users
transmission. Secondary users must leave channel due to preventing damages to
primary users whenever these users discretion. In this article, spectrum
opportunities prediction based on Recurrent Neural Network for bandwidth
optimization and reducing the amount of energy by predicting spectrum holes
discovery for quality of services optimization proposed in OFDM-based cognitive
radio network based on probability density function. The result of the
simulation represent acceptable value of SNR and bandwidth optimization in
these networks that allows secondary users to taking spectrum and sending data
without collision and overlapping with primary users.Comment: OFDM, Cognitive Radio Networks, Recurrent Neural Network, Probability
Density Functio