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http://dx.doi.org/10.11003/JPNT.2022.11.2.91

Computational Complexity Analysis of Cascade AOA Estimation Algorithm Based on FMCCA Antenna  

Kim, Tae-yun (Institute of AI Convergence, Chosun University)
Hwang, Suk-seung (Interdisciplinary Program in IT-Bio Convergence System, School of Electronic Engineering, Chosun University)
Publication Information
Journal of Positioning, Navigation, and Timing / v.11, no.2, 2022 , pp. 91-98 More about this Journal
Abstract
In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.
Keywords
AOA estimation; cascade estimation; flexible massive concentric circular array antenna; computational complexity;
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Times Cited By KSCI : 2  (Citation Analysis)
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