An overview on position location: Past, present, future
Prior to the 21st century, positioning technologies had limited applications including air
traffic control, air and sea navigation, satellite communications and related military uses …
traffic control, air and sea navigation, satellite communications and related military uses …
AI-based resource provisioning of IoE services in 6G: A deep reinforcement learning approach
Currently, researchers have motivated a vision of 6G for empowering the new generation of
the Internet of Everything (IoE) services that are not supported by 5G. In the context of 6G …
the Internet of Everything (IoE) services that are not supported by 5G. In the context of 6G …
Demand-driven deep reinforcement learning for scalable fog and service placement
The increasing number of Internet of Things (IoT) devices necessitates the need for a more
substantial fog computing infrastructure to support the users' demand for services. In this …
substantial fog computing infrastructure to support the users' demand for services. In this …
Location-Enabled IoT (LE-IoT): A survey of positioning techniques, error sources, and mitigation
The Internet of Things (IoT) has started to empower the future of many industrial and mass-
market applications. Localization techniques are becoming key to add location context to IoT …
market applications. Localization techniques are becoming key to add location context to IoT …
Opportunistic uav deployment for intelligent on-demand iov service management
H Sami, R Saado, A El Saoudi… - … on Network and …, 2023 - ieeexplore.ieee.org
Due to the current improvement in self-driving cars and the extensive focus and research on
the topic of the Internet of Vehicles (IoV), the near future may behold a great revolution in the …
the topic of the Internet of Vehicles (IoV), the near future may behold a great revolution in the …
Wireless fingerprinting uncertainty prediction based on machine learning
Although wireless fingerprinting has been well researched and widely used for indoor
localization, its performance is difficult to quantify. Therefore, when wireless fingerprinting …
localization, its performance is difficult to quantify. Therefore, when wireless fingerprinting …
A machine learning approach for GPS code phase estimation in multipath environments
M Orabi, J Khalife, AA Abdallah… - 2020 IEEE/ION …, 2020 - ieeexplore.ieee.org
A neural network (NN)-based delay-locked loop (DLL) for multipath mitigation in Global
Positioning System (GPS) receivers is developed. The NN operates on equally-spaced …
Positioning System (GPS) receivers is developed. The NN operates on equally-spaced …
A novel RSSI fingerprint positioning method based on virtual AP and convolutional neural network
S Wu, W Huang, M Li, K Xu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Indoor Wi-Fi positioning based on Received Signal Strength Indicator (RSSI) has been
widely used in all kinds of location-based services. However, the accuracy of positioning is …
widely used in all kinds of location-based services. However, the accuracy of positioning is …
A survey of machine learning in pedestrian localization systems: Applications, open issues and challenges
With the popularization of machine learning (ML) techniques and the increased chipset's
performance, the application of ML to pedestrian localization systems has received …
performance, the application of ML to pedestrian localization systems has received …
Neural network-based ranging with LTE channel impulse response for localization in indoor environments
A neural network (NN)-based approach for indoor localization via cellular long-term
evolution (LTE) signals is proposed. The approach estimates, from the channel impulse …
evolution (LTE) signals is proposed. The approach estimates, from the channel impulse …