Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

Zhang, Zhaolei; Liu, Yu; Huang, Jie; Zhang, Jingfan; Li, Jingquan; He, Ruisi

doi:10.3390/s23114998

Cited by 8 publications

(9 citation statements)

References 37 publications

(58 reference statements)

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“…The lowest number of autonomous vehicles was observed during the very early hours of the morning. Within the simulated region, an array of base station categories was deployed, including terahertz [52], NLOS-FSOC [53], and sub-6 GHz [54]. These base stations were strategically positioned to cater to the bandwidth requisites of the streaming applications.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Application of Bidirectional Long Short-Term Memory to Adaptive Streaming for Internet of Autonomous Vehicles

Huang,

Hu,

Cheng

2023

Biomimetics

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It is expected that interconnected networks of autonomous vehicles, especially during peak traffic, will face congestion challenges. Moreover, the existing literature lacks discussions on integrating next-generation wireless communication technologies into connected vehicular networks. Hence, this paper introduces a tailored bandwidth management algorithm for streaming applications of autonomous vehicle passengers. It leverages cutting-edge 6G wireless technology to create a network with high-speed transmission and broad coverage, ensuring smooth streaming application performance. The key features of bandwidth allocation for diverse streaming applications in this work include bandwidth relay and pre-loading of video clips assisted by vehicle-to-vehicle communication. Through simulations, this research effectively showcases the algorithm’s ability to fulfill the bandwidth needs of diverse streaming applications for autonomous vehicle passengers. Specifically, during periods of peak user bandwidth demand, it notably increases the bandwidth accessible for streaming applications. On average, users experience a substantial 55% improvement in the bandwidth they can access. This validation affirms the viability and promise of the proposed approach in efficiently managing the intricate complexities of bandwidth allocation issues for streaming services within the connected autonomous vehicular networks.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Application of Bidirectional Long Short-Term Memory to Adaptive Streaming for Internet of Autonomous Vehicles

Huang,

Hu,

Cheng

2023

Biomimetics

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“…Three types of base stations, including THz [ 28 ], mmWave [ 67 ], and sub-6 GHz [ 68 ], were set up in the simulated area to provide the bandwidth required for the video applications. Table 4 shows the bandwidth and transmission distance that can be provided by the three types of base stations.…”

Section: Resultsmentioning

confidence: 99%

An Adaptive Bandwidth Management Algorithm for Next-Generation Vehicular Networks

Huang,

Hu,

Cheng

2023

Sensors

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The popularity of video services such as video call or video on-demand has made it impossible for people to live without them in their daily lives. It can be anticipated that the explosive growth of vehicular communication owing to the widespread use of in-vehicle video infotainment applications in the future will result in increasing fragmentation and congestion of the wireless transmission spectrum. Accordingly, effective bandwidth management algorithms are demanded to achieve efficient communication and stable scalability in next-generation vehicular networks. To the best of our current knowledge, a noticeable gap remains in the existing literature regarding the application of the latest advancements in network communication technologies. Specifically, this gap is evident in the lack of exploration regarding how cutting-edge technologies can be effectively employed to optimize bandwidth allocation, especially in the realm of video service applications within the forthcoming vehicular networks. In light of this void, this paper presents a seamless integration of cutting-edge 6G communication technologies, such as terahertz (THz) and visible light communication (VLC), with the existing 5G millimeter-wave and sub-6 GHz base stations. This integration facilitates the creation of a network environment characterized by high transmission rates and extensive coverage. Our primary aim is to ensure the uninterrupted playback of real-time video applications for vehicle users. These video applications encompass video conferencing, live video, and on-demand video services. The outcomes of our simulations convincingly indicate that the proposed strategy adeptly addresses the challenge of bandwidth competition among vehicle users. Moreover, it notably boosts the efficient utilization of bandwidth from less crowded base stations, optimizes the fulfillment of bandwidth prerequisites for various video applications, and elevates the overall video quality experienced by users. Consequently, our findings serve as a successful validation of the practicality and effectiveness of the proposed methodology.

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“…To alleviate the propagation challenges of mmWave bands, a three-dimensional (3D) network architecture could be adopted by installing access points (APs) on unmanned aerial vehicles (UAVs) that can be easily controlled and relocated to achieve LoS connectivity and enhance coverage and throughput [9]. Such an approach coincides with the vision of 6G, which is expected to integrate aerial elements, such as UAVs, with terrestrial networks to provide high-quality and cost-efficient mobile services [10].…”

Section: Introductionmentioning

confidence: 99%

Customized Millimeter Wave Channel Model for Enhancement of Next-Generation UAV-Aided Internet of Things Networks

Altheeb,

Elshafiey,

Altamimi

et al. 2024

Sensors

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The success of next-generation Internet of Things (IoT) applications could be boosted with state-of-the-art communication technologies, including the operation of millimeter-wave (mmWave) bands and the implementation of three-dimensional (3D) networks. With some access points (APs) mounted on unmanned aerial vehicles (UAVs), the probability of line-of-sight (LoS) connectivity to IoT nodes could be augmented to address the high path loss at mmWave bands. Nevertheless, system optimization is essential to maintaining reliable communication in 3D IoT networks, particularly in dense urban areas with elevated buildings. This research adopts the implementation of a geometry-based stochastic channel model. The model customizes the standard clustered delay line (CDL) channel profile based on the environmental geometry of the site to obtain realistic performance and optimize system design. Simulation validation is conducted based on the actual maps of highly dense urban areas to demonstrate that the proposed approach is comprehensive. The results reveal that the use of standard channel models in the analysis introduces errors in the channel quality indicator (CQI) that can exceed 50% due to the effect of the environmental geometry on the channel profile. The results also quantify accuracy improvements in the wireless channel and network performance in terms of the CQI and downlink (DL) throughput.

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Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios

Cited by 8 publications

References 37 publications

Application of Bidirectional Long Short-Term Memory to Adaptive Streaming for Internet of Autonomous Vehicles

Application of Bidirectional Long Short-Term Memory to Adaptive Streaming for Internet of Autonomous Vehicles

An Adaptive Bandwidth Management Algorithm for Next-Generation Vehicular Networks

Customized Millimeter Wave Channel Model for Enhancement of Next-Generation UAV-Aided Internet of Things Networks

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