Maximum likelihood approach to DoA estimation using lens antenna array

Massive antenna array has been proposed to improve the spectral efficiency and link reliability in wireless communication systems. However, using large antenna arrays incurs additional cost in terms of signal processing and hardware complexity. The electromagnetic (EM) lens-focusing antennas are int...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:EURASIP journal on wireless communications and networking 2019-10, Vol.2019 (1), p.1-7, Article 242
Hauptverfasser: Jiang, Zheng-Ming, Zhang, Peichang, Rihan, Mohamed, Huang, Lei, Zhang, Jihong
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Massive antenna array has been proposed to improve the spectral efficiency and link reliability in wireless communication systems. However, using large antenna arrays incurs additional cost in terms of signal processing and hardware complexity. The electromagnetic (EM) lens-focusing antennas are introduced as a promising technique to reduce the hardware complexity and cost. On the other hand, determining the location of users in terms of their direction-of-arrival (DoA) using these lens array becomes of great interest for different 5G services. This paper addresses the issue of DoA estimation by adopting lens antenna array (LNA). We firstly derive an expression for the received signal with the adoption of LNA, and then a maximum likelihood (ML) estimator for the DoA has been obtained. Depending on the ability of the lens array to focus the signal power on a subset of antennas as a function of DoA. We propose using the antenna selection (AS) technology to select an antenna subset aiming to reduce the number of radio frequency (RF) chains and accordingly reducing the hardware cost. The simulation results show the the capability of the proposed method to avoid the phase ambiguity problem and provide high accurate DoA estimation of signals.
ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-019-1549-3