The time of arrival (ToA) and received signal strength (RSS) estimation errors are modelled based on channel measurements in a non-line-of-sight indoor environment. It is found interesting that their errors are largely independent. Suboptimal hybrid ToA/RSS ranging estimators are derived in closed form based on the obtained error models, and shown to achieve near-optimal performance. The performance of all the estimators improves as the bandwidth increases.Introduction: State-of-the-art ranging systems exploit the time of arrival (ToA) or the received signal strength (RSS) of wireless signals [1]. Owing to the weak direct path and rich scattering, it is a challenging task to design and evaluate the performance of indoor ranging systems under non-line-of-sight (NLoS) scenarios. To the best of our knowledge, ToA and RSS error models have been studied separately [2, 3], but never jointly, through real-world measurement under NLoS scenarios.In this Letter, we study the ToA-and/or RSS-based ranging performance in a typical NLoS indoor environment, under the OFDM system assumption. Our main contributions are: (i) a channel measurement campaign, taking both the ToA-and the RSS-based ranging into account, was carried out in the indoor environment; (ii) the ToA and the RSS estimation errors are modelled into functions of the bandwidth based on the measurement; (iii) suboptimal hybrid ToA/RSS ranging estimators are derived in closed form and shown to achieve near-optimal performance, especially when the bandwidth is large.
This study reported the establishment of a highly-efficient In2O3@g-C3N4 heterostructure with intimate contact for photocatalyzed H2 evolution by incorporating the g-C3N4 ultrathin nanosheets on the surface of MOFs-derived hexagonal In2O3...
Abstract-In this paper, we address the problem of interference mitigation with data pre-processing in the 4G uplink systems, and propose to use the Grubbs/Wright algorithm to detect and remove the interference contaminated data. The Malikov algorithm is also applied to correct the system errors. The pre-processed data are used for channel estimation and data detection in base stations.
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