Recast Subspace Pursuit-based Channel Estimation for Hybrid Beamforming NarrowBand Millimeter-Wave Massive MIMO Systems

Millimeter wave (mmWave) wireless communication systems with hybrid beamforming require reliable estimation of channel state information to perform optimally. Though the combined high-speed analog-to-digital converters (ADCs) and hybrid precoder/combiner architecture of this system ameliorate the pr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE Vehicular Technology Conference S. 1 - 6
1. Verfasser: Oyerinde, Olutayo Oyeyemi
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2022
Schlagworte:
Array signal processing
Channel estimation
Estimation
hybrid precoder
millimeter wave
Millimeter wave technology
narrowband channel
Simulation
Vehicular and wireless technologies
Wireless communication
ISSN:2577-2465
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Millimeter wave (mmWave) wireless communication systems with hybrid beamforming require reliable estimation of channel state information to perform optimally. Though the combined high-speed analog-to-digital converters (ADCs) and hybrid precoder/combiner architecture of this system ameliorate the problem of high-power consumption, they make channel estimation to become cumbersome. The paper proposed a channel estimation scheme that is based on a conventional subspace pursuit algorithm. The proposed estimator is named Recast Subspace Pursuit (ReSP)-based channel estimator. Besides taking advantage of the inherent sparsity in the mmWave Massive MIMO channel, the ReSP-based estimator also exploits the a-priori knowledge of channel matrix support-set as side information for the estimation procedure. Simulation results confirm that the proposed ReSP-based channel estimator can exhibit improved performance than some traditional and earlier proposed channel estimation schemes.
ISSN:2577-2465
DOI:10.1109/VTC2022-Spring54318.2022.9861018