6G for intelligent transportation systems: standards, technologies, and challenges

Jha, Amitkumar V.; Appasani, Bhargav; Khan, Mohammad S.; Zeadally, Sherali; Katib, Iyad

doi:10.1007/s11235-024-01126-5

Telecommun Syst

2024

DOI: 10.1007/s11235-024-01126-5

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6G for intelligent transportation systems: standards, technologies, and challenges

Amitkumar V. Jha,

Bhargav Appasani,

Mohammad S. Khan

et al.

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2024

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Cited by 5 publications

References 58 publications

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An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directions

Loutfi,

Shayea,

Tureli

et al. 2024

Results in Engineering

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An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directions

Loutfi,

Shayea,

Tureli

et al. 2024

Results in Engineering

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Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications

Mehmood,

Muhammad,

Mehmood

et al. 2024

Mathematics

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In future 6G networks, real-time and accurate vehicular data are key requirements for enhancing the data-driven multi-access edge computing (MEC) applications. Existing estimation techniques to forecast vehicle position aim to meet the real-time data needs but compromise accuracy due to a lack of context awareness. While algorithms such as the Kalman filter improve estimation accuracy by considering certainty-grading and current-state estimate of measurements, they do not include the road context, which is vital for more accurate predictions. Unfortunately, current implementations of linear Kalman filters are not road-aware and struggle to predict a two-dimensional movement accurately. To this end, we propose a significant road-aware rectification-assisted prediction mechanism that enhances the modified Kalman filter predictions by incorporating road awareness. The parameters used for the Kalman filter include vehicle location, angle, speed, and time. In contrast, road-aware location rectification incorporates predicted location and lane shape, increasing the accuracy and precision of vehicle location predictions, reaching up to 99.9%. Performance is evaluated by comparing actual, predicted, and rectified vehicular traces at different speeds. The results demonstrate that the prediction error is approximately 0.005, while the proposed rectification process further reduces the error to 0.001, highlighting the effectiveness of the proposed approach. Overall, results support the idea of provisioning accurate, proactive, and real-time vehicular location data at the edge using a road-aware approach, thereby revolutionizing 6G vehicle location provisioning in MEC.

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Balancing Technological Innovation and Environmental Sustainability: A Lifecycle Analysis of 6G Wireless Communication Technology

Chauhan,

Mewada,

Gondalia

et al. 2024

Sustainability

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Wireless communication has revolutionized the evolution of humankind. The rapid growth and development of mobile communication has created an ecosystem better than what has been before. However, issues such as ample energy consumption and resulting carbon emissions, a lack of proper disposal mechanisms for large amounts of electronic waste, and the recycling of electronic materials interrupt growth. When the world is waiting for the implementation of 6G mobile communication technology, it is mandatory to resolve these issues for the sustainability of 6G technology. In this review, we present the superiority of 6G over previous generations accompanied by issues that cause extensive damage to the environment. To mitigate this adverse effect, we present a lifecycle analysis of 6G wireless communication technology from production to disposal, focusing on issues surrounding electronic waste, energy consumption, and environmental impact. This study explains the intricacies of electronic parts, toxic compounds, and the dangers of incorrect disposal techniques. It also investigates energy consumption issues specific to 6G technology, such as manufacturing processes and network infrastructures that require considerable energy. We also present a quantitative evaluation of the 6G lifecycle in detail. In addition, we present a comprehensive strategy and insights to make 6G sustainable. Furthermore, we suggest an ecological policy for all stakeholders for the sustainability of 6G. We also present political and commercial implications for 6G. As the process of 6G development continues, we show the impact of network fragmentation on standardization, which helps improve sustainability. Finally, we conclude that while the existing research has made significant advances in 6G, there is a need for correct disposal techniques to refine the key government policies for managing e-waste. New cooling technologies and renewable energy sources must be adopted to reduce the current greenhouse emission of 200 g of CO2 and energy consumption of 2.5 kWh per GB for 6G networks.

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6G for intelligent transportation systems: standards, technologies, and challenges

Cited by 5 publications

References 58 publications

An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directions

An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directions

Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications

Balancing Technological Innovation and Environmental Sustainability: A Lifecycle Analysis of 6G Wireless Communication Technology

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