An Algorithm of Searching Non-uniform Linear Antenna Array Configurations with High Degrees of Freedom

碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 103 === The design of non-uniform linear array (NLA) configurations have drawn plenty of attention in recent years due to their potential for increasing obtainable degrees of freedom (DOF) in smart antenna arrays. The extra DOF give NLA the ability to detect more n...

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Bibliographic Details
Main Authors: Hsiao, Po-Chung, 蕭博仲
Other Authors: Chen, Sau-Gee
Format: Others
Language:en_US
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/924w5h
Description
Summary:碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 103 === The design of non-uniform linear array (NLA) configurations have drawn plenty of attention in recent years due to their potential for increasing obtainable degrees of freedom (DOF) in smart antenna arrays. The extra DOF give NLA the ability to detect more number of signals than that of the sensors in the array while detectable number of sources must be smaller than that of antennas when uniform linear array (ULA) configuration is applied. That makes NLA an appealing structure for the upcoming 5G wireless communication standard for the reason that the applications of a massive amount of antennas are of great interest in the new standard. This thesis proposes an algorithm of finding an improved non-uniform linear array configuration based on spacing-constrained array, which is able to provide higher obtainable DOF than existing NLA configurations. We exploit the second-order statistics of the received signals to make use of the additional DOF we gain from the proposed structure. Furthermore, a mixture of spatial smoothing and array interpolation is applied to show that great performance can be achieved even without having Vandermonde structure. Simulation results show that our structure outperforms most of the existing structures in applications such as DOA estimations and receive beamforming in terms of root mean square error (RMSE) and signal to interference-plus-noise ratio (SINR), respectively.