English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Millimeter wave (mmWave) has been claimed to be the only viable solution forhigh-bandwidth vehicular communications. However, frequent channel estimationand beamforming required to provide a satisfactory quality of service limitsmmWave for vehicular communications. In this paper, we propose a novel channelestimation and beam tracking framework for mmWave communications in a vehicularnetwork setting. For channel estimation, we propose an algorithm termed robustadaptive multi-feedback (RAF) that achieves comparable estimation performanceas existing channel estimation algorithms, with a significantly smaller numberof feedback bits. We derive upper and lower bounds on the probability ofestimation error (PEE) of the RAF algorithm, given a number of channelestimations, whose accuracy is verified through Monte Carlo simulations. Forbeam tracking, we propose a new practical model for mmWave vehicularcommunications. In contrast to the prior works, the model is based on position,velocity, and channel coefficient, which allows a significant improvement ofthe tracking performance. Focused on the new beam tracking model, we re-derivethe equations for Jacobian matrices, reducing the complexity for vehicularcommunications. An extensive number of simulations is conducted to show thesuperiority of our proposed channel estimation method and beam trackingalgorithm in comparison with the existing algorithms and models. Oursimulations suggest that the RAF algorithm can achieve the desired PEE, whileon average, reducing the feedback overhead by 75.5% and the total channelestimation time by 14%. The beam tracking algorithm is also shown tosignificantly improve beam tracking performance, allowing more room for datatransmission.

Fast Channel Estimation and Beam Tracking for Millimeter Wave Vehicular Communications