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Performance Evaluation of Different Channel Estimation Techniques Using OFDM System on Large and Small Scale Fading Channel Model


 
The development of internet related applications and their increasing demands have led to advancement in high speed communication systems. For the accomplishment of these increasing demands MIMO channels with multiple transmitting and receiving antennas have been devised. MIMO systems enhance the capacity using spatial multiplexing and interference reduction through spatial dimensioning. Furthermore, MIMO systems mutual with orthogonal frequency division multiplexing (MIMO-OFDM) improves system capacity and mitigation against fading. These systems are the basis of 4G and beyond wireless communication standards. This research work focus on improvement in channel estimation performance using various techniques on standard communication models. Semi blind channel estimation technique is employed for channel estimation, which includes use of training sequence in form of pilots. Block type arrangement is being used, since it’s based on frequency selective channels. LSE and MMSE estimations are the two basic estimation techniques which can be efficiently used to estimate channels in OFDM systems. For MMSE implementation information of noise variance and channel covariance is required. Furthermore it is extremely complex than LSE estimator. DFT and DCT based channel estimation methods are employed to increase the performance and diminish the complexity. Different interpolation methods are been used and analyzed for better performance. Number of subcarriers which also have an impact on estimation performance has also been discussed. Overall channel estimation performance have been examined for both large and small scale fading channel models.
