no code implementations • 15 May 2024 • Feng Wang, M. Cenk Gursoy, Senem Velipasalar
In this paper, we propose feature-based federated transfer learning as a novel approach to improve communication efficiency by reducing the uplink payload by multiple orders of magnitude compared to that of existing approaches in federated learning and federated transfer learning.
no code implementations • 11 Dec 2023 • Xueyuan Wang, M. Cenk Gursoy, Tugba Erpek, Yalin E. Sagduyu
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks, and determining collision-free trajectory in multi-UAV non-cooperative scenarios while collecting data from distributed Internet of Things (IoT) nodes is a challenging task.
no code implementations • 11 Dec 2023 • Xueyuan Wang, M. Cenk Gursoy
We address three different practical scenarios, including single UAV path planning, UAV swarm path planning, and single UAV path planning in the presence of an intelligent mobile UAV jammer.
no code implementations • 10 Dec 2023 • Zixi Wang, M. Cenk Gursoy
Several differential privacy (DP) mechanisms have been proposed to provide provable privacy guarantees by introducing randomness into the framework, and majority of these mechanisms rely on injecting additive noise.
no code implementations • 30 Nov 2023 • Geethu Joseph, Chen Zhong, M. Cenk Gursoy, Senem Velipasalar, Pramod K. Varshney
Our objective is to design a sequential selection policy that dynamically determines which processes to observe at each time with the goal to minimize the delay in making the decision and the total sensing cost.
no code implementations • 19 Nov 2023 • Feng Wang, M. Cenk Gursoy, Senem Velipasalar
We evaluate the performance of the proposed policy ensemble algorithm by applying on the network slicing agents and the jammer agent in simulations to show its effectiveness.
1 code implementation • 30 Oct 2023 • Feng Wang, Senem Velipasalar, M. Cenk Gursoy
MKOR only requires the server to send secretly modified parameters to clients and can efficiently and inconspicuously reconstruct the input images from clients' gradient updates.
1 code implementation • 12 Sep 2022 • Feng Wang, M. Cenk Gursoy, Senem Velipasalar
In order to improve the communication efficiency, we in this paper propose the feature-based federated transfer learning as an innovative approach to reduce the uplink payload by more than five orders of magnitude compared to that of existing approaches.
no code implementations • 3 Jan 2022 • Geethu Joseph, M. Cenk Gursoy, Pramod K. Varshney
Based on the received observations, the decisionmaker first determines whether to declare that the number of anomalies has exceeded the threshold or to continue taking observations.
no code implementations • 24 Dec 2021 • Ziyang Lu, M. Cenk Gursoy
In this paper, we address the channel access problem in a dynamic wireless environment via meta-reinforcement learning.
no code implementations • 8 Dec 2021 • Geethu Joseph, Chen Zhong, M. Cenk Gursoy, Senem Velipasalar, Pramod K. Varshney
In this setting, we develop an anomaly detection algorithm that chooses the processes to be observed at a given time instant, decides when to stop taking observations, and declares the decision on anomalous processes.
no code implementations • 29 Sep 2021 • Saikiran Bulusu, Geethu Joseph, M. Cenk Gursoy, Pramod Varshney
Further, we prove that ${O}(\frac{1}{\epsilon p^4}\log\frac{d}{\delta})$ samples are sufficient for our algorithm to estimate the NN parameters within an error of $\epsilon$ with probability $1-\delta$ when the probability of a sample being uncorrupted is $p$ and the problem dimension is $d$.
no code implementations • 12 May 2021 • Geethu Joseph, Chen Zhong, M. Cenk Gursoy, Senem Velipasalar, Pramod K. Varshney
In this paper, we address the anomaly detection problem where the objective is to find the anomalous processes among a given set of processes.
no code implementations • 12 May 2021 • Geethu Joseph, M. Cenk Gursoy, Pramod K. Varshney
In this setting, we develop an anomaly detection algorithm that chooses the process to be observed at a given time instant, decides when to stop taking observations, and makes a decision regarding the anomalous processes.
no code implementations • 12 May 2021 • Feng Wang, M. Cenk Gursoy, Senem Velipasalar
Deep reinforcement learning (DRL) has recently been used to perform efficient resource allocation in wireless communications.
no code implementations • 9 Apr 2021 • Xueyuan Wang, M. Cenk Gursoy, Tugba Erpek, Yalin E. Sagduyu
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks.
no code implementations • 3 Apr 2021 • Xueyuan Wang, M. Cenk Gursoy
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks, and determining collision-free trajectories for multiple UAVs while satisfying requirements of connectivity with ground base stations (GBSs) is a challenging task.
no code implementations • 14 Jan 2021 • Yi Shi, Yalin E. Sagduyu, Tugba Erpek, M. Cenk Gursoy
In this paper, reinforcement learning (RL) for network slicing is considered in NextG radio access networks, where the base station (gNodeB) allocates resource blocks (RBs) to the requests of user equipments and aims to maximize the total reward of accepted requests over time.
Networking and Internet Architecture
no code implementations • 28 Sep 2020 • Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
In order to improve the detection accuracy and reduce the delay in detection, we introduce a buffer zone in the operation of the proposed GAN-based detector.
no code implementations • 13 Aug 2020 • Xueyuan Wang, M. Cenk Gursoy
Beamforming is one of the key techniques in millimeter wave (mmWave) multi-input multi-output (MIMO) communications.
no code implementations • 12 Jul 2020 • Feng Wang, Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
As the applications of deep reinforcement learning (DRL) in wireless communications grow, sensitivity of DRL based wireless communication strategies against adversarial attacks has started to draw increasing attention.
no code implementations • 26 May 2020 • Geethu Joseph, M. Cenk Gursoy, Pramod K. Varshney
Our objective is to design a sequential sensor selection policy that dynamically determines which processes to observe at each time and when to terminate the detection algorithm.
no code implementations • 22 Mar 2020 • Ziyi Zhao, Zhao Jin, Wentian Bai, Wentan Bai, Carlos Caicedo, M. Cenk Gursoy, Qinru Qiu
In this paper, a deep learning-based UAS instantaneous density prediction model is presented.
no code implementations • 28 Aug 2019 • Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
Anomaly detection is widely applied in a variety of domains, involving for instance, smart home systems, network traffic monitoring, IoT applications and sensor networks.
no code implementations • 20 Aug 2019 • Chen Zhong, Ziyang Lu, M. Cenk Gursoy, Senem Velipasalar
We consider both a single-user case and a scenario in which multiple users attempt to access channels simultaneously.
no code implementations • 13 May 2019 • Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
The growing demand on high-quality and low-latency multimedia services has led to much interest in edge caching techniques.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 31 Mar 2019 • Chuang Ye, M. Cenk Gursoy, Senem Velipasalar
Dynamic programming is employed to implement the optimal offline and the initial online power control policies that minimize the transmit power consumption in the communication session.
no code implementations • 16 Oct 2018 • Chuang Ye, M. Cenk Gursoy, Senem Velipasalar
In this paper, wireless video transmission to multiple users under total transmission power and minimum required video quality constraints is studied.
no code implementations • 8 Oct 2018 • Chen Zhong, Ziyang Lu, M. Cenk Gursoy, Senem Velipasalar
We consider the dynamic multichannel access problem, which can be formulated as a partially observable Markov decision process (POMDP).