Fast Beam Discovery and Adaptive Transmission under Frequency Selective Attenuations in Sub-Terahertz Bands

Published

February 6, 2023

Author(s)

junliang yi, Hamid Gharavi, Bin Hu

Abstract

Sub-THz-based communication needs ultra-large antenna arrays to generate pencil-like beams under the stringent requirements of line-of-sight (LoS) to overcome the effect of the rapid attenuation of signal strength, including atmospheric attenuation. In addition, the complexity of attaining narrower beamwidth, which also requires fast and perfect alignment between the TX-RX pair, makes the sector sweeping-based beam discovery approach no longer suitable. To solve these challenging problems, in this paper we propose a leaky waveguide (LWG)-assisted, high-resolution codebook-based beam discovery, precoding, and combining scheme together with an adaptive frequency hopping spread spectrum (FHSS) for a network with relays and small base stations (SBS). The proposed method can help the transmitter quickly determine a suitable beam pattern for an LoS path requiring only limited feedback information. In the beam discovery phase, we use LWG to attain valuable information about the angle of departure (AoD) and angle of arrival (AoA). LWG has also been used to identify frequency selective attenuated regions, which can change from time to time depending on the local atmospheric moisture conditions. To mitigate the impact of such attenuations, we opt for an adaptive Frequency Hopping Spread Spectrum (FHSS). The simulation results indicate that our beam discovery and FHSS based method can achieve a much higher performance than baseline methods.

Citation

IEEE Transactions on Signal Processing

Volume

71

Pub Type

Journals

Download Paper

https://doi.org/10.1109/TSP.2023.3236166

Local Download

Keywords

Sub-THz, Relay, Leaky wave guide, Beam discovery

Citation

yi, J. , Gharavi, H. and Hu, B. (2023), Fast Beam Discovery and Adaptive Transmission under Frequency Selective Attenuations in Sub-Terahertz Bands, IEEE Transactions on Signal Processing, [online], https://doi.org/10.1109/TSP.2023.3236166, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936109 (Accessed May 4, 2024)