Sparse code multiple access (SCMA) is the most prominent non-orthogonal multiple access (NOMA) scheme considered as massive connectivity. Because SCMA users transmit information using the same time-frequency resources, properly estimating each user's channel information is a challenging issue. In this paper, we propose a channel estimator in the uplink SCMA system. We design a pilot structure based on a cyclically shifted Zadoff-Chu (ZC) sequence. The proposed algorithm using the autocorrelation property of the ZC sequence separates each user's channel information and estimates each user's channel frequency response. In addition, we calculate the number of required training blocks and prove that the number of training blocks in the proposed algorithm is lower than the number of needed in conventional channel estimation techniques. In simulation results, we compare the mean squared error (MSE) of the proposed algorithm with conventional approaches.


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    Title :

    Channel Estimation for Uplink SCMA Systems with Reduced Training Blocks


    Contributors:
    Heo, Jehyun (author) / Jung, Insik (author) / Kim, Taehyung (author) / Kim, Hyunsoo (author) / Hong, Daesik (author)


    Publication date :

    2018-06-01


    Size :

    220881 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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