238 citations · 802 across the 40 of their papers we have counts for
9 papers · 1 filter
Anonymous Jamming Detection in 5G with Bayesian Network Model Based Inference Analysis
Ying Wang, Shashank Jere, Soumya Banerjee +3
Jamming and intrusion detection are critical in 5G research, aiming to maintain reliability, prevent user experience degradation, and avoid infrastructure failure. This paper intro…
Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning
Kian Hamedani, Lingjia Liu, Jithin Jagannath +2
Smart grids are vulnerable to cyber-attacks. This paper proposes a game-theoretic approach to evaluate the variations caused by an attacker on the power measurements. Adversaries c…
Differential Privacy Meets Federated Learning under Communication Constraints
Nima Mohammadi, Jianan Bai, Qiang Fan +3
The performance of federated learning systems is bottlenecked by communication costs and training variance. The communication overhead problem is usually addressed by three communi…
Harnessing Tensor Structures -- Multi-Mode Reservoir Computing and Its Application in Massive MIMO
Zhou Zhou, Lingjia Liu, Jiarui Xu
In this paper, we introduce a new neural network (NN) structure, multi-mode reservoir computing (Multi-Mode RC). It inherits the dynamic mechanism of RC and processes the forward p…
Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks
Zhou Zhou, Yan Xin, Hao Chen +2
In this paper, we consider jointly optimizing cell load balance and network throughput via a reinforcement learning (RL) approach, where inter-cell handover (i.e., user association…
Learning for Integer-Constrained Optimization through Neural Networks with Limited Training
Zhou Zhou, Shashank Jere, Lizhong Zheng +1
In this paper, we investigate a neural network-based learning approach towards solving an integer-constrained programming problem using very limited training. To be specific, we in…
Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond
Hao-Hsuan Chang, Lingjia Liu, Yang Yi
Deep reinforcement learning (DRL) has been shown to be successful in many application domains. Combining recurrent neural networks (RNNs) and DRL further enables DRL to be applicab…
Big Data Meet Cyber-Physical Systems: A Panoramic Survey
Rachad Atat, Lingjia Liu, Jinsong Wu +3
The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world {via} creating new services and applications in a var…
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Hao-Hsuan Chang, Hao Song, Yang Yi +3
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to share radio spectrum among different networks. As a secondary user (SU), a DSA device will fac…