DOA Estimation Based on Hybrid Digital and Analog Phase Alignment With Polynomial Rooting Approaches for Hybrid Massive MIMO Receive Array.
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| Title: | DOA Estimation Based on Hybrid Digital and Analog Phase Alignment With Polynomial Rooting Approaches for Hybrid Massive MIMO Receive Array. |
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| Authors: | Chang, Tsui-Ping1 (AUTHOR) applechang@nutc.edu.tw, Meng, Chao-Li2 (AUTHOR), Bagwari, Ashish (AUTHOR) ashishbagwari@gmail.com |
| Source: | International Journal of Distributed Sensor Networks. 4/28/2025, Vol. 2025, p1-9. 9p. |
| Subjects: | Multiple Signal Classification, Cost functions, Derivatives (Mathematics), Computer simulation, Polynomials |
| Abstract: | This paper introduces a novel approach for direction of arrival (DOA) estimation utilizing hybrid digital and analog phase alignment (HDAPA) tailored for hybrid analog and digital massive multiple‐input multiple‐output (MIMO) receive arrays. To address the inherent high complexity associated with traditional HDAPA and analog phase alignment methods—primarily due to exhaustive linear spectrum searching with small step sizes—a more efficient method has been developed. This new approach leverages polynomial rooting techniques instead of conventional spectral searching. However, this polynomial rooting method tends to be less effective in environments with significant noise. To overcome this limitation, the paper proposes an enhanced polynomial rooting estimation method grounded in the cost function of the multiple signal classification (MUSIC) algorithm, which demonstrates increased robustness in low signal‐to‐noise ratio conditions. The key innovation lies in directly taking the root of the first‐order derivative of the cost function. The effectiveness of the proposed method is validated through various computer simulations. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | This paper introduces a novel approach for direction of arrival (DOA) estimation utilizing hybrid digital and analog phase alignment (HDAPA) tailored for hybrid analog and digital massive multiple‐input multiple‐output (MIMO) receive arrays. To address the inherent high complexity associated with traditional HDAPA and analog phase alignment methods—primarily due to exhaustive linear spectrum searching with small step sizes—a more efficient method has been developed. This new approach leverages polynomial rooting techniques instead of conventional spectral searching. However, this polynomial rooting method tends to be less effective in environments with significant noise. To overcome this limitation, the paper proposes an enhanced polynomial rooting estimation method grounded in the cost function of the multiple signal classification (MUSIC) algorithm, which demonstrates increased robustness in low signal‐to‐noise ratio conditions. The key innovation lies in directly taking the root of the first‐order derivative of the cost function. The effectiveness of the proposed method is validated through various computer simulations. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15501329 |
| DOI: | 10.1155/dsn/6577686 |
