Detection of Primary and Secondary Users in Multipath Fading Channel Using Kalman Filters for Cognitive Radios
Now a day’s, wireless communication is becoming a wide research area in the communication field. In this paper, we have analyzed the Kalman Filter for linear and non-linear systems, it will be helpful for spectrum sensing in a quit accurate way. Kalman Filter (KF) is the most important technique for estimating the state of engineering systems. In this paper, we have implemented KF and EKF with and without Rayleigh Fading effects using Matlab. A tabular comparison has been made between the estimated values and true state values of the KF and EKF with and without Rayleigh Fading effects. The gain is also calculated for KF and EKF. The estimation comparison has been made between KF and EKF to show which filter is best suitable for the estimation. Finally, KF is applied to the OFDM system.
KeywordsExtended Kalman Filter (EKF) Kalman Filter (KF) Primary users (PU’s) Secondary users (SU’s) Unscented Kalman Filter (UKF)
The satisfaction that accompanies the successful completion of any task would be incomplete without mentioning those, who made it possible, whose constant guidance and encouragement crowned our efforts with success. We take this opportunity to express our deepest gratitude and appreciation to all those who have helped us.
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