Near-Field Channel Modeling for Electromagnetic Information Theory
arxiv(2024)
摘要
Electromagnetic information theory (EIT) is one of the important topics for
6G communication due to its potential to reveal the performance limit of
wireless communication systems. For EIT, the research foundation is reasonable
and accurate channel modeling. Existing channel modeling works for EIT in
non-line-of-sight (NLoS) scenario focus on far-field modeling, which can not
accurately capture the characteristics of the channel in near-field. In this
paper, we propose the near-field channel model for EIT based on electromagnetic
scattering theory. We model the channel by using non-stationary Gaussian random
fields and derive the analytical expression of the correlation function of the
fields. Furthermore, we analyze the characteristics of the proposed channel
model, e.g., the sparsity of the model in wavenumber domain. Based on the
sparsity of the model, we design a channel estimation scheme for near-field
scenario. Numerical analysis verifies the correctness of the proposed scheme
and shows that it can outperform existing schemes like least square (LS) and
orthogonal matching pursuit (OMP).
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