Joint Estimation for Time Delay and Direction of Arrival in Reconfigurable Intelligent Surface with OFDM

Recently, the joint estimation for time delay (TD) and direction of arrival (DOA) has suffered from the high complexity of processing multi-dimensional signal models and the ineffectiveness of correlated/coherent signals. In order to improve this situation, a joint estimation method using orthogonal...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-09, Vol.22 (18), p.7083
Main Authors: Du, Jinzhi, Cui, Weijia, Ba, Bin, Jian, Chunxiao, Zhang, Liye
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analysis
Asymmetry
channel frequency response
Coherence
Covariance matrix
Direction of arrival
direction of arrival (DOA)
Frequency response
joint estimation
Localization
Orthogonal Frequency Division Multiplexing
reconfigurable intelligent surface (RIS)
Reconfiguration
Signal processing
Signal to noise ratio
Subspaces
tensor
time delay (TD)
Time lag
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Summary:Recently, the joint estimation for time delay (TD) and direction of arrival (DOA) has suffered from the high complexity of processing multi-dimensional signal models and the ineffectiveness of correlated/coherent signals. In order to improve this situation, a joint estimation method using orthogonal frequency division multiplexing (OFDM) and a uniform planar array composed of reconfigurable intelligent surface (RIS) is proposed. First, the time-domain coding function of the RIS is combined with the multi-carrier characteristic of the OFDM signal to construct the coded channel frequency response in tensor form. Then, the coded channel frequency response covariance matrix is decomposed by CANDECOMP/PARAFAC (CPD) to separate the signal subspaces of TD and DOA. Finally, we perform a one-dimensional (1D) spectral search for TD values and a two-dimensional (2D) spectral search for DOA values. Compared to previous efforts, this algorithm not only enhances the adaptability of coherent signals, but also greatly decreases the complexity. Simulation results indicate the robustness and effectiveness for the proposed algorithm in independent, coherent, and mixed multipath environments and low signal-to-noise ratio (SNR) conditions.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22187083