State Estimation in Cognitive Radio Environment

Abstract

With the advancement of wireless technology there has been increased need for bandwidth. For the uninterrupted communication users are licensed to particular bandwidth but this has lead to under utilization of bandwidth when licensed user is not using the bandwidth so cognitive radio provides opportunity for the access of underutilized bandwidth. In cognitive environment spectrum is sensed if primary user is present or not.

We will study kalman filtering based state estimation problem in cyber physical systems (CPS) where the different parts of the system are distributed and each sensor transmits its measures its measurements and then transmits to state estimator. But sensing may be imperfect or other environment factor like fading can cause packet loss. Hence by considering channel state condition, environment condition stability condition is calculated.

Kalman filtering state estimation has been used as it gives least estimation error due to recursive technique of kalman filter. We divide licensed part into two part in which one group contains dedicated sensors where partial packet loss takes place while other group is also having licensed channel to access. Other group is accessed randomly when first group channel is busy. First group sensors are independent of each other so when they will transmit simultaneously to other group and senses channel to be idle then there may be packet loss, so collision probability is taken into account. Whole system is analyzed by with the help of two transmission process sequential transmission and partial packet losses.