Game theory and reinforcement learning in cognitive radar game modeling and algorithm research: A review
B He, N Yang, X Zhang, W Wang - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Cognitive radar (CR) systems have garnered significant attention for their ability to adapt
and optimize radar performance in dynamic and uncertain environments. Game theory (GT) …
and optimize radar performance in dynamic and uncertain environments. Game theory (GT) …
Data-driven Integrated Sensing and Communication: Recent Advances, Challenges, and Future Prospects
Integrated Sensing and Communication (ISAC), combined with data-driven approaches, has
emerged as a highly significant field, garnering considerable attention from academia and …
emerged as a highly significant field, garnering considerable attention from academia and …
A Survey of Graph-Based Resource Management in Wireless Networks-Part I: Optimization Approaches
The evolution of wireless communications and networking technologies has led significantly
expansion of the dimensionality of network resources, which compels innovations in …
expansion of the dimensionality of network resources, which compels innovations in …
Edge intelligence oriented integrated sensing and communication: A multi-cell cooperative approach
Integrated sensing and communication (ISAC) and edge intelligence are essential
components for the next generation wireless networks. ISAC provides a spectrum-efficient …
components for the next generation wireless networks. ISAC provides a spectrum-efficient …
Optimal Resource Allocation for Integrated Sensing and Communications in Internet of Vehicles: A Deep Reinforcement Learning Approach
Integrated sensing and communications (ISAC) technology is identified as a breakthrough in
optimizing resource allocation and pursuing mutual benefits between radar sensing and …
optimizing resource allocation and pursuing mutual benefits between radar sensing and …
Efficient Spectrum Sharing Between Coexisting OFDM Radar and Downlink Multiuser Communication Systems
This paper investigates the problem of joint subcarrier and power allocation in the
coexistence of radar and multi-user communication systems. Specifically, in our research …
coexistence of radar and multi-user communication systems. Specifically, in our research …
Jointly Optimizing Terahertz based Sensing and Communications in Vehicular Networks: A Dynamic Graph Neural Network Approach
In this paper, the problem of vehicle service mode selection (sensing, communication, or
both) and vehicle connections within terahertz (THz) enabled joint sensing and …
both) and vehicle connections within terahertz (THz) enabled joint sensing and …
Graph Neural Networks for Next-Generation-IoT: Recent Advances and Open Challenges
Graph Neural Networks (GNNs) have emerged as a critical tool for optimizing and managing
the complexities of the Internet of Things (IoT) in next-generation networks. This survey …
the complexities of the Internet of Things (IoT) in next-generation networks. This survey …
Joint Deep Reinforcement Learning and Unfolding for Sensing and Communication Function Selection in Vehicular Networks
X Shen, H Zheng, J Lin, X Feng - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the exponential advancement of vehicle networking applications and autonomous
driving technology, the demand for efficient and secure autonomous vehicles (AVs) is …
driving technology, the demand for efficient and secure autonomous vehicles (AVs) is …
A Cognitive Multi-Carrier Radar for Communication Interference Avoidance via Deep Reinforcement Learning
Spectrum sharing between the radar and communication systems has become increasingly
prevalent in recent years, therefore reducing the communication interference is a critical …
prevalent in recent years, therefore reducing the communication interference is a critical …