36 citations · 98 across the 12 of their papers we have counts for
14 papers
Large Language Models-Empowered Wireless Networks: Fundamentals, Architecture, and Challenges
Latif U. Khan, Maher Guizani, Sami Muhaidat +1
The rapid advancement of wireless networks has resulted in numerous challenges stemming from their extensive demands for quality of service towards innovative quality of experience…
Robust Federated Learning on Edge Devices with Domain Heterogeneity
Huy Q. Le, Latif U. Khan, Choong Seon Hong
Federated Learning (FL) allows collaborative training while ensuring data privacy across distributed edge devices, making it a popular solution for privacy-sensitive applications.…
Metaverse for Wireless Systems: Architecture, Advances, Standardization, and Open Challenges
Latif U. Khan, Mohsen Guizani, Dusit Niyato +2
The growing landscape of emerging wireless applications is a key driver toward the development of novel wireless system designs. Such a design can be based on the metaverse that us…
Machine Learning for Wireless Metaverse: Fundamentals, Use Case, and Future Directions
Latif U. Khan, Ibrar Yaqoob, Khaled Salah +4
Today's wireless systems are posing key challenges in terms of quality of service and quality of physical experience. Metaverse has the potential to reshape, transform, and add inn…
Federated Learning for Digital Twin-Based Vehicular Networks: Architecture and Challenges
Latif U. Khan, Ehzaz Mustafa, Junaid Shuja +4
Emerging intelligent transportation applications, such as accident reporting, lane change assistance, collision avoidance, and infotainment, will be based on diverse requirements (…
Metaverse for Wireless Systems: Vision, Enablers, Architecture, and Future Directions
Latif U. Khan, Zhu Han, Dusit Niyato +2
Recently, significant research efforts have been initiated to enable the next-generation, namely, the sixth-generation (6G) wireless systems. In this article, we present a vision o…
Digital Twin of Wireless Systems: Overview, Taxonomy, Challenges, and Opportunities
Latif U. Khan, Zhu Han, Walid Saad +3
Future wireless services must be focused on improving the quality of life by enabling various applications, such as extended reality, brain-computer interaction, and healthcare. Th…
A Dispersed Federated Learning Framework for 6G-Enabled Autonomous Driving Cars
Latif U. Khan, Yan Kyaw Tun, Madyan Alsenwi +3
Sixth-Generation (6G)-based Internet of Everything applications (e.g. autonomous driving cars) have witnessed a remarkable interest. Autonomous driving cars using federated learnin…
Digital-Twin-Enabled 6G: Vision, Architectural Trends, and Future Directions
Latif U. Khan, Walid Saad, Dusit Niyato +2
Internet of Everything (IoE) applications such as haptics, human-computer interaction, and extended reality, using the sixth-generation (6G) of wireless systems have diverse requir…
Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
Latif U. Khan, Walid Saad, Zhu Han +2
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning algorithms for both network and application management. However, given the presence of massiv…
Dispersed Federated Learning: Vision, Taxonomy, and Future Directions
Latif U. Khan, Walid Saad, Zhu Han +1
The ongoing deployment of the Internet of Things (IoT)-based smart applications is spurring the adoption of machine learning as a key technology enabler. To overcome the privacy an…
Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism
Latif U. Khan, Shashi Raj Pandey, Nguyen H. Tran +4
Recent years have witnessed a rapid proliferation of smart Internet of Things (IoT) devices. IoT devices with intelligence require the use of effective machine learning paradigms.…
Energy Harvesting in 5G Networks: Taxonomy, Requirements, Challenges, and Future Directions
Muhammad Imran, Latif U. Khan, Ibrar Yaqoob +3
Consciousness of energy saving is increasing in fifth-generation (5G) wireless networks due to the high energy consumption issue. Energy harvesting technology is a possible appeali…
Edge-Computing-Enabled Smart Cities: A Comprehensive Survey
Latif U. Khan, Ibrar Yaqoob, Nguyen H. Tran +3
Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which dem…