6 citations · 17 across the 8 of their papers we have counts for
9 papers
Constrained Deep Reinforcement Learning for Cognitive Radar Resource Management
Ziyang Lu, M. Cenk Gursoy, Chilukuri K. Mohan +1
In this paper, multi-target tracking and scanning are considered in a radar system operating in the track-while-scan mode. Specifically, time allocation for radar scanning and trac…
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…
Dynamic Channel Access via Meta-Reinforcement Learning
Ziyang Lu, M. Cenk Gursoy
In this paper, we address the channel access problem in a dynamic wireless environment via meta-reinforcement learning. Spectrum is a scarce resource in wireless communications, es…
Dynamic Channel Access and Power Control in Wireless Interference Networks via Multi-Agent Deep Reinforcement Learning
Ziyang Lu, Chen Zhong, M. Cenk Gursoy
Due to the scarcity in the wireless spectrum and limited energy resources especially in mobile applications, efficient resource allocation strategies are critical in wireless netwo…
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…