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Efficient beam allocation strategy for statistical beamforming-based massive multiple-input–multiple-output downlink systems

Efficient beam allocation strategy for statistical beamforming-based massive multiple-input–multiple-output downlink systems

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This study focuses on an efficient fairness aware beam allocation strategy which is based on user position approach. The proposed algorithm is efficient to cope with the effects of user position uncertainties and imperfect channel state information (CSI). It allocates beam to individual users based on directivity and user position with the objective of serving many users simultaneously. On the basis of the user position, individual data rate requirements are also considered in the proposed scheme which is very much important for practical systems thereby considering the fairness issue amongst the users. The proposed scheme is best suited for a system with covariance-based beamforming, where statistical CSI is highly preferred under high dense deployments and the channel coherence time is short. It also requires low average feedback load with less multiuser interference and is of low complexity compared with the searching-based beam allocation strategy. The simulation results are given to show the advantage of the proposed beam allocation on comparing with the prevailing schemes.

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