In the indoor distributed antenna system (DAS), base station transmits signals with even power via the distributed antennas. Thus, single reference signal received power (RSRP) from the receiver will result in accurate localization. In response to this compelling problem, we utilize the pedestrian dead reckoning, which is based on consecutive signals in collected RSRP sequences as the template sequences, to achieve high-performance location estimation. Specifically, the main idea of the proposed localization algorithm is calculating the correlation between the on-site sequence and each pre-constructed template sequence, which is labeled with human movement coordinates. Then, the prediction location is considered as the template sequence label that is with the largest approximation to the on-site sequence. Experiments are conducted with real time division long-term evolution signals in indoor DAS, and the corresponding experimental results demonstrate that the proposed approach can not only solve the problem of positioning in DAS, but also provide satisfactory localization accuracy.
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Liu et al. (2017) studied this question.
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