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To reap the benefits of reconfigurable intelligent surfaces (RIS), channel state information (CSI) is generally required. However, CSI acquisition in RIS systems is challenging and often results in very large pilot overhead, especially in unstructured channel environments. Consequently, the RIS channel estimation problem has attracted a lot of interest and also been a subject of intense study in recent years. In this paper, we propose a decision-directed RIS channel estimation framework for general unstructured channel models. The employed RIS contains some hybrid elements that can simultaneously reflect and sense the incoming signal. We show that with the help of the hybrid RIS elements, it is possible to accurately recover the CSI with a pilot overhead proportional to the number of users. Therefore, the proposed framework substantially improves the system spectral efficiency compared to systems with passive RIS arrays since the pilot overhead in passive RIS systems is proportional to the number of RIS elements times the number of users. We also perform a detailed spectral efficiency analysis for both the pilot-directed and decision-directed frameworks. Our analysis takes into account both the channel estimation and data detection errors at both the RIS and the BS. Finally, we present numerous simulation results to verify the accuracy of the analysis as well as to show the benefits of the proposed decision-directed framework.
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Spectrally Efficient Pilot Structure and Channel Estimation for Multiuser FBMC Systems
In this paper, we consider channel estimation problem in the uplink of filter bank multicarrier (FBMC) systems. We propose a pilot structure and a joint multiuser channel estimation method for FBMC. Opposed to the available solutions in the literature, our proposed technique does not rely on the flat-channel condition over each subcarrier band or any requirement for placing guard symbols between different users’ pilots. Our proposed pilot structure reduces the training overhead by interleaving the users’ pilots in time and frequency. Thus, we can accommodate a larger number of training signals within the same bandwidth and improve the spectral efficiency. Furthermore, this pilot structure inherently leads to a reduced peak-to-average power ratio (PAPR) compared with the solutions that use all the subcarriers for training. We analytically derive the Cramér-Rao lower bound (CRLB) and mean square error (MSE) expressions for our proposed method. We show that these expressions are the same. This confirms the optimality of our proposed method, which is numerically evaluated through simulations. Relying on its improved spectral efficiency, our proposed method can serve a large number of users and relax pilot contamination problem in FBMC-based massive MIMO systems. This is corroborated through simulations in terms of sum-rate performance for both single cell and multicell scenarios.
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- Award ID(s):
- 1824558
- PAR ID:
- 10188062
- Date Published:
- Journal Name:
- ICC 2020 - 2020 IEEE International Conference on Communications (ICC)
- Page Range / eLocation ID:
- 1 to 7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICC40277.2020.9148851
