2021
DOI: 10.3390/s21062015
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Wideband Channel Characterization for 6G Networks in Industrial Environments

Abstract: Wireless data traffic has increased significantly due to the rapid growth of smart terminals and evolving real-time technologies. With the dramatic growth of data traffic, the existing cellular networks including Fifth-Generation (5G) networks cannot fully meet the increasingly rising data rate requirements. The Sixth-Generation (6G) mobile network is expected to achieve the high data rate requirements of new transmission technologies and spectrum. This paper presents the radio channel measurements to study th… Show more

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Cited by 22 publications
(13 citation statements)
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“…An extension in [42] introduces a hybrid indoor THz channel model combining both RT and statistical methods. In [43], measurement-based sub-THz (107 − 109 GHz) channel characteristics are captured for industrial environments.…”
Section: Introductionmentioning
confidence: 99%
“…An extension in [42] introduces a hybrid indoor THz channel model combining both RT and statistical methods. In [43], measurement-based sub-THz (107 − 109 GHz) channel characteristics are captured for industrial environments.…”
Section: Introductionmentioning
confidence: 99%
“…The frequency band (95 GHz-3 THz) has been assigned for the next wireless technology sixth generation (6G) research to fulfill the huge demands for future data traffic according to Federal Communications Commission (FCC) [9,10]. Nevertheless, one of the main technical problems of deploying 6G systems is to overcome the high propagation and atmospheric absorption of THz frequencies, which require a new design for the transceiver [11,12]. Many researchers recently consider optical wireless communication (OWC) including ultraviolet (UV), infrared (IR) and visible light (VL) as an attractive complementary and alternative technique of RF.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, UAV flying is a limited battery capacity during coverage services in disaster scenarios [12]. Furthermore, gathering data from the Internet of Things (IoT) using UAVs also suffers from data processing and transferring due to limited battery charge [13], [14]. Therefore, the authors of [15] applied an artificial neural network for predicting the signal strength over IoT devices in smart environments based on optimized location and UAV trajectory.…”
Section: Introductionmentioning
confidence: 99%