International Journal of Advancements in Technology
Open Access

Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, New York, USA

Publications

• Research Article   
  Deep Learning-Based Vehicular Channel Estimator in High Mobility Environments
  Author(s): Lara Gregorians*, Pablo Fernández Velasco, Fiona Zisch and Hugo J Spiers
  
  In recent years, deep learning has almost invaded the world of telecom electronics and other fields, given the spectacular results it achieves in terms of improving the performance of digital processing chains. Wireless Access in Vehicle Environments (WAVE) technology has been developed, and IEEE 802.11p defines the Physical Layer (PHY) and Media Access Control (MAC) layer in the WAVE standard. However, the IEEE 802.11p frame structure, which has a low pilot density, makes it difficult to predict wireless channel properties in a vehicle environment with high vehicle speeds (high Doppler frequency), thus system performance are degraded in realistic vehicle environments. The motivation of this article is to improve channel estimation and tracking performance without modifying the IEEE 802.11p frame structure. Therefore, we propose a channel estimation technique base.. View More»
  DOI: 10.35248/0976-4860.22.13.206

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