کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4944392 | 1437989 | 2017 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Dynamic propagation characteristics estimation and tracking based on an EM-EKF algorithm in time-variant MIMO channel
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
In cognitive radio (CR), it is important to understand the multi-dimension and multi-scale characteristics of the dynamic multiple-input multiple-output (MIMO) channels obtained from observations. In this paper, to estimate and track propagation path parameters in time-variant MIMO channels, we propose an expectation maximization-extended Kalman filter (EM-EKF) in the frequency domain. The proposed algorithm can capture the dynamic channel with a high accuracy and a low time consumption. We use the EKF in the frequency domain to detect existed paths and to continue to track how the paths evolve over time. Then, we formulate a frequency-domain EM method to estimate the new paths in the dynamic propagation channel. Simulation results demonstrate that the proposed approach has an improved performance in terms of parametric estimation and a lower time consumption compared with the comparative space-alternating generalized expectation-maximization algorithm (SAGE).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 408, October 2017, Pages 70-83
Journal: Information Sciences - Volume 408, October 2017, Pages 70-83
نویسندگان
Yuhao Wang, Kangliang Chen, Jiangnan Yu, Naixue Xiong, Henry Leung, Huilin Zhou, Li Zhu,