تقرير
Spatial Non-Stationary Dual-Wideband Channel Estimation for XL-MIMO Systems
| العنوان: | Spatial Non-Stationary Dual-Wideband Channel Estimation for XL-MIMO Systems |
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| المؤلفون: | Tang, Anzheng, Wang, Jun-Bo, Pan, Yijin, Wu, Tuo, Chang, Chuanwen, Chen, Yijian, Yu, Hongkang, Elkashlan, Maged |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | In this paper, we investigate the channel estimation problem for extremely large-scale multi-input and multi-output (XL-MIMO) systems, considering the spherical wavefront effect, spatially non-stationary (SnS) property, and dual-wideband effects. To accurately characterize the XL-MIMO channel, we first derive a novel spatial-and-frequency-domain channel model for XL-MIMO systems and carefully examine the channel characteristics in the angular-and-delay domain. Based on the obtained channel representation, we formulate XL-MIMO channel estimation as a Bayesian inference problem. To fully exploit the clustered sparsity of angular-and-delay channels and capture the inter-antenna and inter-subcarrier correlations, a Markov random field (MRF)-based hierarchical prior model is adopted. Meanwhile, to facilitate efficient channel reconstruction, we propose a sparse Bayesian learning (SBL) algorithm based on approximate message passing (AMP) with a unitary transformation. Tailored to the MRF-based hierarchical prior model, the message passing equations are reformulated using structured variational inference, belief propagation, and mean-field rules. Finally, simulation results validate the convergence and superiority of the proposed algorithm over existing methods. Comment: This paper has been submitted to IEEE journal for possible publication |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.05643 |
| رقم الأكسشن: | edsarx.2407.05643 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |