Abstract
Estimation of the channel has been one of the major concerns in any communication system. Although various channel estimation techniques are available for MIMO (Multiple Input Multiple Output) systems, the problem of wastage of bandwidth due to the transmission of training sequences prior to the transmission of actual data exists. Use of superimposed pilot sequence that accomplishes transmission of both the pilot and data simultaneously has been proposed as an effective alternative. The work carried out includes both simulation and real-time implementation of channel models and channel estimation techniques. Appropriate channel models chosen include shadowing model and Markov model to address large-scale fading effects, and Rician model for small-scale fading effects. Employing channel estimation techniques for the above listed channel models is the novel idea aimed for satellite applications. Also different algorithms for channel estimation like least square (LS), minimum mean square error (MMSE), and linear minimum mean square Error (LMMSE) have been compared. Furthermore, merits and demerits of superimposed and conventional pilots are analyzed by making performance comparisons. Hardware implementation is done using Universal Software Radio Peripheral (USRP).
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Acknowledgements
We would like to extend special sense of gratitude to our project advisor Dr. S. Kirthiga for her wonderful and immense support throughout the completion of the project. We also thank Mr. R. Gandhiraj for helping us understand the whereabouts of USRP. We also thank our friends who assisted in every aspect of the work. We finally thank the department for giving us the necessary platform for carrying out the project successfully.
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Sarayu, S., Radhakrishnan, J., Kirthiga, S. (2017). Superimposed Pilot Based Channel Estimation for MIMO Systems. In: Dash, S., Vijayakumar, K., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-10-3174-8_11
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DOI: https://doi.org/10.1007/978-981-10-3174-8_11
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