Long Term Evolution (LTE) is a project within the third generation Partnership (3GPP) in order to improve the UMTS (Universal Mobile Telecommunication system) mobile phone standard such that future requirements can be met. The good aspect of 3GPP is the centralization of the standards, and it is a step toward the 4th generation (4G) of radio technologies with increasing data rates on every application of mobile technology. MIMO has been adopted in the 3GPP LTE which achieves high capacity by transmitting independent information over different antennas simultaneously .Traditional MIMO techniques have been already thoroughly investigated  and are deployed in many existing wireless systems.
When the users become highly mobile the channel becomes time variant and frequency selective within one OFDM symbol and the most challenging problem is the estimation of the channel in very fast moving conditions. For rapidly varying channels Doppler spread occurs which leads to loss in orthogonality of the subcarriers and the noise is assumed to be white Gaussian. But in rapidly varying channel noise is often caused by a strong interferer, which color in nature . Therefore estimating the channel with the effect of color noise is very much important and the existing channel estimation techniques assuming time invariant channel with white Gaussian cannot be used for high mobility systems moving at a speed of 120 km/h. Considering the channel estimation for time-varying multipath fading channels the estimation is performed by applying hybrid frequency/time domain channel estimation algorithm where it does not suits for high mobility systems [7, 8].
In the existing system, at the receiver side after removing the guard band, …
…the performance of Adaptive channel estimation with interference cancellation scheme and color noise removal for a high-mobility environment. Adaptive channel estimation technique has larger applications in LTE systems, user with highly mobile.
The rest of the paper is organized as follows. Firstly, introduction the system model with the presence of color noise  in section II. In section III the proposed adaptive channel estimation with the removal of color noise and interference cancellation is done. A -explains the estimation of the channel, B – removal of color noise is obtained and C – interference cancellation is done and remaining part explains the adaption of estimation to the threshold rate. In section IV performance analysis is done and the simulation results are presented to demonstrate the performance. Finally, the conclusion is drawn in section v.