Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10997
Title: A Simple Cascade Channel Estimation Method for UAV RIS-Enabled Millimeter Wave Transmissions
Authors: Iren, K.T.
Girici, T.
Keywords: Channel Estimation; LDPC; Overhead; Reconfigurable intel-ligent surfaces; Unmanned aerial vehicle
Channel estimation; Millimeter waves; Mobile telecommunication systems; Terahertz waves; Vehicle transmissions; Aerial vehicle; Channel estimation method; Low-density parity-check; Millimeter wave transmission; Overhead; Reconfigurable; Reconfigurable intel-ligent surface; Simple++; Unmanned aerial vehicle; Wireless communications; Antennas
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Reconfigurable Intelligent Surfaces (RIS) is an emerging concept in Sixth Generation (6G) technologies. RIS can manipulate the wireless communication environment and provide virtual Line of Sight (LOS) links between a Base Station(BS) and User Equipment (UE) by controlling the coefficients of passive reflecting elements. RIS is a promising concept with its passive and low-cost nature. However, RIS-enabled transmission experiences double scattering and high path loss. Besides, it requires a massive number of elements in the millimeter-wave(mmWave) and sub-TeraHertz(THz), which makes channel estimation a complicated problem. There are quite a number of diverse methods in recent literature. In this work we assume a Unmanned Aerial Vehicle(UAV)-mounted RIS that provides a line of sight. We propose a simple cascade channel estimation method and compare its performance with that of a recently proposed channel estimation scheme. We perform comparisons, taking the overhead caused by Fifth Generation (5G) Low Density Parity Check (LDPC) coding and channel estimation overhead into account. Simulations show that our proposal achieves a much better spectral efficiency. © 2023 IEEE.
Description: 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023 -- 26 October 2023 through 28 October 2023 -- 194643
URI: https://doi.org/10.1109/WINCOM59760.2023.10322913
https://hdl.handle.net/20.500.11851/10997
ISBN: 9798350329674
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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