Abstract
This paper deals with the under-determined problems caused by channel estimations using insufficient nonorthogonal pilot sequences for large multi-user multi-input multi-output (MU-MIMO) detection in probabilistic data association (PDA). To avoid the above under-determined problems, data associated iterative channel estimation is effective, where tentatively detected data (soft symbols) based on iterative detection is utilized as additional pilot sequences. However, the detection capability of PDA is severely degraded by modeling errors which are caused by decision errors included in soft value and the non-orthogonality of additional pilot sequences. For mitigating the negative impacts of the modeling errors, a novel covariance matrix for MU detection (MUD) is designed according to the incompleteness of tentative pilots. Finally, we verify the validity of the proposed method in terms of the suppression of the bit error rate (BER) floor.
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