Abstract
In this paper, we propose a user selection scheme based on location-aided interference prediction to reduce the training overhead in a non-orthogonal multiple access (NOMA) system. First, we cluster the users based on their location information, enabling the use of non-orthogonal pilot sequence within a cluster and orthogonal pilot sequence between different clusters to reduce the uplink pilot training length. Secondly, we exploit the location information in the computation of the covariance matrices, enabling the prediction of the interference between users. The predicted interference is employed to select the set of users with minimum interference for uplink channel estimation and downlink NOMA data transmission. Finally, the achievable sum-rate of the massive multiple-input multiple-output millimeter wave NOMA system is analyzed. The analytical and numerical results reveal that the location information can be exploited for user selection to reduce the effect of pilot contamination, enhancing the uplink channel estimation and downlink achievable sum-rate.
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