6 papers
Adaptive Resource Management in Cognitive Radar via Deep Deterministic Policy Gradient
Ziyang Lu, M. Cenk Gursoy, Chilukuri K. Mohan +1
In this paper, scanning for target detection, and multi-target tracking in a cognitive radar system are considered, and adaptive radar resource management is investigated. In parti…
Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning
Ziyang Lu, M. Cenk Gursoy, Chilukuri K. Mohan +1
Deep reinforcement learning has been extensively studied in decision-making processes and has demonstrated superior performance over conventional approaches in various fields, incl…
Multi-Objective Reinforcement Learning for Cognitive Radar Resource Management
Ziyang Lu, Subodh Kalia, M. Cenk Gursoy +2
The time allocation problem in multi-function cognitive radar systems focuses on the trade-off between scanning for newly emerging targets and tracking the previously detected targ…
Learning-Based Resource Management in Integrated Sensing and Communication Systems
Ziyang Lu, M. Cenk Gursoy, Chilukuri K. Mohan +1
In this paper, we tackle the task of adaptive time allocation in integrated sensing and communication systems equipped with radar and communication units. The dual-functional radar…
A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access
Chen Zhong, Ziyang Lu, M. Cenk Gursoy +1
To make efficient use of limited spectral resources, we in this work propose a deep actor-critic reinforcement learning based framework for dynamic multichannel access. We consider…
Actor-Critic Deep Reinforcement Learning for Dynamic Multichannel Access
Chen Zhong, Ziyang Lu, M. Cenk Gursoy +1
We consider the dynamic multichannel access problem, which can be formulated as a partially observable Markov decision process (POMDP). We first propose a model-free actor-critic d…